From a5e93f2d6ca079a4ba460d144a80171d73810c92 Mon Sep 17 00:00:00 2001 From: Mugume Twinamatsiko Atwine Date: Thu, 5 Mar 2020 15:27:20 +0300 Subject: [PATCH 01/29] Deleted --- .github/workflows/e_kariuki.yaml | 17 ----------------- 1 file changed, 17 deletions(-) delete mode 100644 .github/workflows/e_kariuki.yaml diff --git a/.github/workflows/e_kariuki.yaml b/.github/workflows/e_kariuki.yaml deleted file mode 100644 index e54d08b..0000000 --- a/.github/workflows/e_kariuki.yaml +++ /dev/null @@ -1,17 +0,0 @@ -name: CI - -on: [push] - -jobs: - build: - - runs-on: ubuntu-latest - - steps: - - uses: actions/checkout@v2 - - name: Run a one-line script - run: echo Hello, world! - - name: Run a multi-line script - run: | - echo Add other actions to build, - echo test, and deploy your project. From 9d5e6290d93338d29f21181869f602e0aba9e0a5 Mon Sep 17 00:00:00 2001 From: Jupiter Marina Date: Thu, 5 Mar 2020 18:00:19 +0300 Subject: [PATCH 02/29] code that is predicting one class --- Assignment Colab/Jupiter Marina.ipynb | 1 + 1 file changed, 1 insertion(+) create mode 100644 Assignment Colab/Jupiter Marina.ipynb diff --git a/Assignment Colab/Jupiter Marina.ipynb b/Assignment Colab/Jupiter Marina.ipynb new file mode 100644 index 0000000..2f0b44b --- /dev/null +++ b/Assignment Colab/Jupiter Marina.ipynb @@ -0,0 +1 @@ +{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\nimport matplotlib as plot\nimport seaborn as sns\nimport sklearn\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n for filename in filenames:\n print(os.path.join(dirname, filename))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Importing data"},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"# Importing data\ntest_data = pd.read_csv(\"/kaggle/input/ace-class-assignment/Test.csv\", header=0, sep=\",\")\namp_train = pd.read_csv(\"/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\", header=0, sep=\",\")\nprint(amp_train)\n#print(test)\n\n\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"amp_train.columns","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#test_amp =amp_train[['FULL_Charge', 'FULL_AcidicMolPerc','FULL_OOBM850104','FULL_DAYM780201', 'AS_MeanAmphiMoment','CLASS']]\n#print(test_amp)\n#test_data=test_data[['FULL_Charge', 'FULL_AcidicMolPerc','FULL_OOBM850104','FULL_DAYM780201', 'AS_MeanAmphiMoment']]\n#X=test_amp.drop(\"CLASS\",axis=1)\n#Y=test_amp.CLASS\n#model=GaussianNB() \n#model.fit(X,Y)\n#kj_results=model.predict(test_data)\n\n#print(test_data2)\n#kj_results","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## General data attributes and descriptive statistics"},{"metadata":{"trusted":true},"cell_type":"code","source":"#Describing general data attributes\ntrain_dim=amp_train.shape #gets the dimensions of the tranining dataset\ntest_dim= test_data.shape #gets the dimensions of the tesing dataset\nprint(train_dim)\nprint(test_dim)\n\natr_types=amp_train.dtypes #gets the data type for each column in training dataset\nprint(atr_types)\namp_train.isnull().sum() # gets the sum of the missing values/observations in each column\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Descriptive statistics \nstats=amp_train.describe()\nprint(stats)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Class distributions\n\nSometimes, observations from the different classes may not be equal, these may need special handling, so its important to note the class distributions, as if they are uneven, they may bias our model"},{"metadata":{"trusted":true},"cell_type":"code","source":"# CLass distibutions \ncdists= amp_train.groupby('CLASS').size() # groups the observation by the column of class, and counts all the observations including null values\nprint(cdists)\n\n#plots to visualize the class distribution\namp_train.groupby('CLASS').size().plot(kind=\"pie\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"The observations from each class seem to be equal"},{"metadata":{},"cell_type":"markdown","source":"# Correlation between the different attributes\nBasically, we need to examine our attributes for correlation as highly correlated attributes present the same data to the algorithm. Removing one may speed learning of the algorithm (less dimensions more speed)"},{"metadata":{"trusted":true},"cell_type":"code","source":"# Correlation between attributes \ncorrelations = amp_train.corr(method=\"pearson\") # calculates pairwaise correlation for the attributes \nprint(correlations)\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"FULL_AURR980107 and FULL_AcidicMolPerc have a correlation coefficent of 0.79, this might mean these two attributes may be some what correlated. Same goes for AS_DAYM780201 and FULL_DAYM780201 (correlation coefficient is 0.894191)"},{"metadata":{"trusted":true},"cell_type":"code","source":"# Plots to visualize the correlations\nfrom matplotlib import rcParams\nsns.heatmap(correlations, annot=True)\nrcParams['figure.figsize'] = 11.7,8.27\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Data skewness\n\nMost machine learning algorithms assume that data from the attributes is normally distributed, so identifying attributes with data that has a left or right skew, can be important as this can be easily corrected"},{"metadata":{"trusted":true},"cell_type":"code","source":"sk = amp_train.skew() # calculates the skew for each attribute\nprint(sk)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Negative values like those of FULL_DAYM780201, FULL_OOBM850104,AS_DAYM780201, AS_FUKS010112, indicate that these attributes have values skewed more to the left\nValues closer to zero are indicative of a less or no skew, while positive values would mean that that particular attribute is skewed more to the right"},{"metadata":{},"cell_type":"markdown","source":" # Visualising data distributions with plots"},{"metadata":{"trusted":true},"cell_type":"code","source":"# Plot one, histogram to show the distributions\nimport matplotlib as plot \nfrom matplotlib import pyplot\namp_train.hist(layout=(4,3), figsize=(16,16))\nplot.pyplot.subplots_adjust(wspace=0.4, hspace=0.5)\npyplot.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Plot two density plots can show the distributions better\namp_train.plot(kind=\"density\",subplots=True,layout=(4,3),sharex=False,sharey=False, figsize=(16,16))\n#amp_train.plot(kind=\"density\",subplots=False,layout=(4,3),sharex=True,sharey=True)\npyplot.show()\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Data transformations\nUsing square roots to transform the attributes with negative values into postives"},{"metadata":{"trusted":true},"cell_type":"code","source":"\nneg1=amp_train.iloc[:,0]\nprint(neg1)\ntneg1=neg1**2\ntneg1.plot(kind=\"density\")\namp_train.iloc[:,0]=tneg1\n\n\n\nneg2=amp_train.iloc[:,5]\nprint(neg2)\ntneg2=neg2**2\ntneg2.plot(kind=\"density\")\namp_train.iloc[:,5]=tneg2\n\n## test\nneg3=test_data.iloc[:,0]\nprint(neg3)\ntneg3=neg3**2\ntneg3.plot(kind=\"density\")\ntest_data.iloc[:,0]=tneg3\n\n\n\nneg4=test_data.iloc[:,5]\nprint(neg4)\ntneg4=neg4**2\ntneg4.plot(kind=\"density\")\ntest_data.iloc[:,5]=tneg4","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"distributions for AS_MeanAmphiMoment,FULL_AcidicMolPerc and NT_EFC195 dont look so good"},{"metadata":{},"cell_type":"markdown","source":"# Feature selection\n\n\n"},{"metadata":{"trusted":true},"cell_type":"code","source":" #test one selecting out features with low variance\nfrom sklearn.feature_selection import VarianceThreshold\nsel = VarianceThreshold(threshold=(.8 * (1 - .8)))\nk=sel.fit_transform(amp_train)\nnames=amp_train.columns[sel.get_support(indices=True)]\nprint(k.shape)\namp_train2=pd.DataFrame(k,columns=names)\nprint(amp_train2)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#test two\nfrom sklearn.feature_selection import SelectKBest\nfrom sklearn.feature_selection import chi2\n\ntest_array = amp_train2.values\n\ntest_atr = test_array[:,0:7]\nclass_atr = test_array[:,7]\n\n\ntest = SelectKBest(score_func=chi2, k=5)\nfit = test.fit(test_atr, class_atr)\n\n\nprint(fit.scores_)\nfeatures = fit.transform(test_atr)\nnames2=amp_train2.columns[fit.get_support(indices=True)]\namp_train3=pd.DataFrame(features,columns=names2)\nprint(amp_train3[5:])\n\n\n\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Test three Recursive feature elimination\n\nfrom sklearn.feature_selection import RFE\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.ensemble import RandomForestClassifier\n\nmodel1 = LogisticRegression()\nmodel2=RandomForestClassifier()\n\nrfe = RFE(model1, 4)\nfit2 = rfe.fit(test_atr, class_atr)\n\nrfe2= RFE(model2, 4)\nfit3 = rfe2.fit(test_atr, class_atr)\n\n\n\n\nnames3=amp_train2.columns[fit2.get_support(indices=True)]\n\nnames4=amp_train2.columns[fit3.get_support(indices=True)]\n\nprint(names3)\nprint(names4)\nprint(names2)\nprint(amp_train.columns)\nprint(amp_train2)\n\n\n\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"test_amp =amp_train.loc[:,['FULL_Charge', 'FULL_AcidicMolPerc',\"FULL_OOBM850104\",'FULL_DAYM780201', 'AS_MeanAmphiMoment','CLASS']]\nprint(test_amp)\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import train_test_split\nfrom sklearn.model_selection import KFold\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.metrics import confusion_matrix\n\n\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.svm import SVC\nfrom sklearn.neighbors import KNeighborsClassifier\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Logistic regression using cross validation"},{"metadata":{"trusted":true},"cell_type":"code","source":"\nX=test_amp.iloc[:,0:5]\nY=test_amp.iloc[:,5]\nfolds=10\nkfold = KFold(n_splits=folds, random_state=7, shuffle=True,)\nmodel = LogisticRegression()\nresults = cross_val_score(model, X, Y, cv=kfold)\n\nprint((\"Accuracy: %.3f%% (%.3f%%)\") % (results.mean()*100.0, results.std()*100.0))\n\n\n\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"test_data = pd.read_csv(\"/kaggle/input/ace-class-assignment/Test.csv\", header=0, sep=\",\")\namp_train = pd.read_csv(\"/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\", header=0, sep=\",\")\ntest_amp =amp_train.loc[:,['FULL_Charge', 'FULL_AcidicMolPerc',\"FULL_OOBM850104\",'FULL_DAYM780201', 'AS_MeanAmphiMoment','CLASS']]","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Logistic regression with a test train split"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.metrics import matthews_corrcoef\ntest_amp=test_amp.values\n#X=test_amp.iloc[:,0:5]\nX=test_amp[:,0:5]\nY=test_amp[:,5]\n\n#Y=test_amp.iloc[:,5]\n#print(Y)\ntest_size = 0.4\nseed = 25\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\nmodel = LogisticRegression()\nmodel.fit(X_train, Y_train)\npredicted = model.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult = model.score(X_test, Y_test)\nprint(\"Accuracy: \", (result*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model.predict(X_test),Y_test))\n#print(test_data)\n\ntest_data2=test_data.loc[:,['FULL_Charge', 'FULL_AcidicMolPerc','FULL_DAYM780201', 'FULL_OOBM850104', 'AS_MeanAmphiMoment']]\ntest_data2=test_data2.values \n#model1 = LogisticRegression() \n#model1.fit(X,Y)\nkj_results=model.predict(test_data2)\n\n#print(test_data2)\nkj_results","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df = pd.DataFrame(kj_results)\ndf.columns = ['CLASS']\ndf.index.name = 'Index'\ndf['CLASS']=df['CLASS'].map({0.0:False,1.0:True})\nprint(df)\n#X=test_amp.iloc[:,0:5]\n#=test_amp.iloc[:,5]\ndf.to_csv(\"kj.csv\")\ndf[\"CLASS\"].unique()\n#print(df.groupby(\"CLASS\").size()[0].sum())\n#print(df.groupby(\"CLASS\").size()[1].sum())\ndf['CLASS'].value_counts()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Gausian/Naive Bayes"},{"metadata":{"trusted":true},"cell_type":"code","source":"model=GaussianNB()\nfrom sklearn.metrics import matthews_corrcoef\ntest_size = 0.4\nseed = 25\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\nrandom_state=seed)\nmodel.fit(X_train, Y_train)\npredicted = model.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult = model.score(X_test, Y_test)\nprint(\"Accuracy: \", (result*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model.predict(X_test),Y_test))\n#print(test_data)\n\nX=test_amp.iloc[:,0:5]\nY=test_amp.iloc[:,5]\nmodel=GaussianNB() \nmodel.fit(X,Y)\nkj_results=model.predict(test_data2)\n\n#print(test_data2)\nkj_results","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Linear Discriminant Analysis"},{"metadata":{"trusted":true},"cell_type":"code","source":"model=LinearDiscriminantAnalysis()\nfolds=10\nkfold = KFold(n_splits=folds, random_state=7, shuffle=True,)\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint((\"Accuracy: %.3f%% (%.3f%%)\") % (results.mean()*100.0, results.std()*100.0))\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Support Vector Machines"},{"metadata":{"trusted":true},"cell_type":"code","source":"model=SVC()\nfolds=10\nkfold = KFold(n_splits=folds, random_state=7, shuffle=True,)\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint((\"Accuracy: %.3f%% (%.3f%%)\") % (results.mean()*100.0, results.std()*100.0))","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4} \ No newline at end of file From 6637b0c1ba99b91b89effbd9dd81f0dc90508a53 Mon Sep 17 00:00:00 2001 From: Atwine Date: Thu, 5 Mar 2020 18:54:49 +0300 Subject: [PATCH 03/29] fit-transform --- .../Jupiter Marina-checkpoint.ipynb | 1786 ++++++++++++++++ Assignment Colab/Jupiter Marina.ipynb | 1787 ++++++++++++++++- 2 files changed, 3572 insertions(+), 1 deletion(-) create mode 100644 Assignment Colab/.ipynb_checkpoints/Jupiter Marina-checkpoint.ipynb diff --git a/Assignment Colab/.ipynb_checkpoints/Jupiter Marina-checkpoint.ipynb b/Assignment Colab/.ipynb_checkpoints/Jupiter Marina-checkpoint.ipynb new file mode 100644 index 0000000..16c3b99 --- /dev/null +++ b/Assignment Colab/.ipynb_checkpoints/Jupiter Marina-checkpoint.ipynb @@ -0,0 +1,1786 @@ +{ + "cells": [ + { + "cell_type": "raw", + "metadata": { + "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", + "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" + }, + "source": [ + "# This Python 3 environment comes with many helpful analytics libraries installed\n", + "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", + "# For example, here's several helpful packages to load in \n", + "\n", + "import numpy as np # linear algebra\n", + "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", + "import matplotlib as plot\n", + "import seaborn as sns\n", + "import sklearn\n", + "\n", + "# Input data files are available in the \"../input/\" directory.\n", + "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", + "\n", + "import os\n", + "for dirname, _, filenames in os.walk('/kaggle/input'):\n", + " for filename in filenames:\n", + " print(os.path.join(dirname, filename))\n", + "\n", + "# Any results you write to the current directory are saved as output." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np # linear algebra\n", + "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", + "import matplotlib as plot\n", + "import seaborn as sns\n", + "import sklearn" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Importing data" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0", + "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a" + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n", + "0 5.0 0.000 0.951 74.842 \n", + "1 4.0 5.405 0.931 71.595 \n", + "2 5.5 5.405 0.873 73.595 \n", + "3 5.0 4.167 0.895 66.250 \n", + "4 7.5 8.537 0.932 64.720 \n", + "\n", + " FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n", + "0 0.975 -3.663 0 0.282 \n", + "1 0.957 -4.011 1 0.600 \n", + "2 0.961 -2.512 0 0.593 \n", + "3 0.999 -1.362 0 0.614 \n", + "4 0.979 -2.091 0 0.616 \n", + "\n", + " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 CLASS \n", + "0 73.444 5.661 1.041 1 \n", + "1 68.222 6.537 1.453 1 \n", + "2 69.444 4.934 1.722 1 \n", + "3 67.222 4.316 1.382 1 \n", + "4 72.944 4.540 1.539 1 " + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Importing data\n", + "test_data = pd.read_csv(\"../AMP Data Sets/Test.csv\", header=0, sep=\",\")\n", + "amp_train = pd.read_csv(\"../AMP Data Sets/AMP_TrainSet.csv\", header=0, sep=\",\")\n", + "#print(amp_train)\n", + "\n", + "\n", + "amp_train.head()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", + " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", + " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", + " 'CLASS'],\n", + " dtype='object')" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "amp_train.columns" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#test_amp =amp_train[['FULL_Charge', 'FULL_AcidicMolPerc','FULL_OOBM850104','FULL_DAYM780201', 'AS_MeanAmphiMoment','CLASS']]\n", + "#print(test_amp)\n", + "#test_data=test_data[['FULL_Charge', 'FULL_AcidicMolPerc','FULL_OOBM850104','FULL_DAYM780201', 'AS_MeanAmphiMoment']]\n", + "#X=test_amp.drop(\"CLASS\",axis=1)\n", + "#Y=test_amp.CLASS\n", + "#model=GaussianNB() \n", + "#model.fit(X,Y)\n", + "#kj_results=model.predict(test_data)\n", + "\n", + "#print(test_data2)\n", + "#kj_results" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## General data attributes and descriptive statistics" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(3038, 12)\n", + "(758, 11)\n", + "FULL_Charge float64\n", + "FULL_AcidicMolPerc float64\n", + "FULL_AURR980107 float64\n", + "FULL_DAYM780201 float64\n", + "FULL_GEOR030101 float64\n", + "FULL_OOBM850104 float64\n", + "NT_EFC195 int64\n", + "AS_MeanAmphiMoment float64\n", + "AS_DAYM780201 float64\n", + "AS_FUKS010112 float64\n", + "CT_RACS820104 float64\n", + "CLASS int64\n", + "dtype: object\n" + ] + }, + { + "data": { + "text/plain": [ + "FULL_Charge 0\n", + "FULL_AcidicMolPerc 0\n", + "FULL_AURR980107 0\n", + "FULL_DAYM780201 0\n", + "FULL_GEOR030101 0\n", + "FULL_OOBM850104 0\n", + "NT_EFC195 0\n", + "AS_MeanAmphiMoment 0\n", + "AS_DAYM780201 0\n", + "AS_FUKS010112 0\n", + "CT_RACS820104 0\n", + "CLASS 0\n", + "dtype: int64" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Describing general data attributes\n", + "train_dim=amp_train.shape #gets the dimensions of the tranining dataset\n", + "test_dim= test_data.shape #gets the dimensions of the tesing dataset\n", + "print(train_dim)\n", + "print(test_dim)\n", + "\n", + "atr_types=amp_train.dtypes #gets the data type for each column in training dataset\n", + "print(atr_types)\n", + "amp_train.isnull().sum() # gets the sum of the missing values/observations in each column\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Note!!\n", + "You can write the code below as\n", + "\n", + "```\n", + "amp_train.describe()\n", + "\n", + "```\n", + "\n", + "It renders properly when you write it like this, Try it!" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201FULL_GEOR030101FULL_OOBM850104NT_EFC195AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CT_RACS820104CLASS
count3038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.000000
mean2.0602378.5215200.97141073.6687600.994007-2.4329270.08854515.68323373.6508285.9113611.2352550.500000
std3.8199297.5866520.1074138.5274890.0313331.7072230.28413311.5756659.1660920.6936890.2100120.500082
min-16.0000000.0000000.68400042.7500000.866000-10.4320000.0000000.04100042.7780003.5330000.7850000.000000
25%0.0000002.5160000.89500068.2940000.974000-3.6060000.0000005.58750067.5560005.4592501.0820000.000000
50%2.0000007.1430000.96300074.0595000.994000-2.2965000.00000014.98850073.6970005.9255001.1840000.500000
75%4.00000013.1580001.04100079.3437501.011000-1.2832500.00000026.80775079.7780006.3820001.3510001.000000
max30.00000046.6670001.451000101.6820001.1960003.5760001.00000051.280000103.1670008.6620002.1920001.000000
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" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n", + "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", + "mean 2.060237 8.521520 0.971410 73.668760 \n", + "std 3.819929 7.586652 0.107413 8.527489 \n", + "min -16.000000 0.000000 0.684000 42.750000 \n", + "25% 0.000000 2.516000 0.895000 68.294000 \n", + "50% 2.000000 7.143000 0.963000 74.059500 \n", + "75% 4.000000 13.158000 1.041000 79.343750 \n", + "max 30.000000 46.667000 1.451000 101.682000 \n", + "\n", + " FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n", + "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", + "mean 0.994007 -2.432927 0.088545 15.683233 \n", + "std 0.031333 1.707223 0.284133 11.575665 \n", + "min 0.866000 -10.432000 0.000000 0.041000 \n", + "25% 0.974000 -3.606000 0.000000 5.587500 \n", + "50% 0.994000 -2.296500 0.000000 14.988500 \n", + "75% 1.011000 -1.283250 0.000000 26.807750 \n", + "max 1.196000 3.576000 1.000000 51.280000 \n", + "\n", + " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 CLASS \n", + "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", + "mean 73.650828 5.911361 1.235255 0.500000 \n", + "std 9.166092 0.693689 0.210012 0.500082 \n", + "min 42.778000 3.533000 0.785000 0.000000 \n", + "25% 67.556000 5.459250 1.082000 0.000000 \n", + "50% 73.697000 5.925500 1.184000 0.500000 \n", + "75% 79.778000 6.382000 1.351000 1.000000 \n", + "max 103.167000 8.662000 2.192000 1.000000 " + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Descriptive statistics \n", + "stats=amp_train.describe()\n", + "#print(stats)\n", + "\n", + "stats\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Class distributions\n", + "\n", + "Sometimes, observations from the different classes may not be equal, these may need special handling, so its important to note the class distributions, as if they are uneven, they may bias our model" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CLASS\n", + "0 1519\n", + "1 1519\n", + "dtype: int64\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# CLass distibutions \n", + "cdists= amp_train.groupby('CLASS').size() # groups the observation by the column of class, and counts all the observations including null values\n", + "print(cdists)\n", + "\n", + "#plots to visualize the class distribution\n", + "amp_train.groupby('CLASS').size().plot(kind=\"pie\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The observations from each class seem to be equal" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Correlation between the different attributes\n", + "Basically, we need to examine our attributes for correlation as highly correlated attributes present the same data to the algorithm. Removing one may speed learning of the algorithm (less dimensions more speed)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201FULL_GEOR030101FULL_OOBM850104NT_EFC195AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CT_RACS820104CLASS
FULL_Charge1.000000-0.612996-0.490977-0.434603-0.058725-0.2837580.0880680.355477-0.365374-0.0905700.2329290.534602
FULL_AcidicMolPerc-0.6129961.0000000.7947960.5414810.1152010.513344-0.143168-0.4315900.4496210.002334-0.213543-0.598816
FULL_AURR980107-0.4909770.7947961.0000000.5482530.3461390.462712-0.169540-0.4260970.4562600.032958-0.403599-0.584111
FULL_DAYM780201-0.4346030.5414810.5482531.0000000.0101180.334778-0.090058-0.4087930.8941910.055915-0.326792-0.554838
FULL_GEOR030101-0.0587250.1152010.3461390.0101181.0000000.319157-0.230417-0.160269-0.0290850.040480-0.151935-0.260470
FULL_OOBM850104-0.2837580.5133440.4627120.3347780.3191571.000000-0.230561-0.3362970.275640-0.4527690.155304-0.453287
NT_EFC1950.088068-0.143168-0.169540-0.090058-0.230417-0.2305611.0000000.178683-0.0368440.1459240.0808980.260702
AS_MeanAmphiMoment0.355477-0.431590-0.426097-0.408793-0.160269-0.3362970.1786831.000000-0.3223780.0255800.1715240.693552
AS_DAYM780201-0.3653740.4496210.4562600.894191-0.0290850.275640-0.036844-0.3223781.0000000.045562-0.256060-0.437168
AS_FUKS010112-0.0905700.0023340.0329580.0559150.040480-0.4527690.1459240.0255800.0455621.000000-0.4452840.033432
CT_RACS8201040.232929-0.213543-0.403599-0.326792-0.1519350.1553040.0808980.171524-0.256060-0.4452841.0000000.267652
CLASS0.534602-0.598816-0.584111-0.554838-0.260470-0.4532870.2607020.693552-0.4371680.0334320.2676521.000000
\n", + "
" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 \\\n", + "FULL_Charge 1.000000 -0.612996 -0.490977 \n", + "FULL_AcidicMolPerc -0.612996 1.000000 0.794796 \n", + "FULL_AURR980107 -0.490977 0.794796 1.000000 \n", + "FULL_DAYM780201 -0.434603 0.541481 0.548253 \n", + "FULL_GEOR030101 -0.058725 0.115201 0.346139 \n", + "FULL_OOBM850104 -0.283758 0.513344 0.462712 \n", + "NT_EFC195 0.088068 -0.143168 -0.169540 \n", + "AS_MeanAmphiMoment 0.355477 -0.431590 -0.426097 \n", + "AS_DAYM780201 -0.365374 0.449621 0.456260 \n", + "AS_FUKS010112 -0.090570 0.002334 0.032958 \n", + "CT_RACS820104 0.232929 -0.213543 -0.403599 \n", + "CLASS 0.534602 -0.598816 -0.584111 \n", + "\n", + " FULL_DAYM780201 FULL_GEOR030101 FULL_OOBM850104 \\\n", + "FULL_Charge -0.434603 -0.058725 -0.283758 \n", + "FULL_AcidicMolPerc 0.541481 0.115201 0.513344 \n", + "FULL_AURR980107 0.548253 0.346139 0.462712 \n", + "FULL_DAYM780201 1.000000 0.010118 0.334778 \n", + "FULL_GEOR030101 0.010118 1.000000 0.319157 \n", + "FULL_OOBM850104 0.334778 0.319157 1.000000 \n", + "NT_EFC195 -0.090058 -0.230417 -0.230561 \n", + "AS_MeanAmphiMoment -0.408793 -0.160269 -0.336297 \n", + "AS_DAYM780201 0.894191 -0.029085 0.275640 \n", + "AS_FUKS010112 0.055915 0.040480 -0.452769 \n", + "CT_RACS820104 -0.326792 -0.151935 0.155304 \n", + "CLASS -0.554838 -0.260470 -0.453287 \n", + "\n", + " NT_EFC195 AS_MeanAmphiMoment AS_DAYM780201 \\\n", + "FULL_Charge 0.088068 0.355477 -0.365374 \n", + "FULL_AcidicMolPerc -0.143168 -0.431590 0.449621 \n", + "FULL_AURR980107 -0.169540 -0.426097 0.456260 \n", + "FULL_DAYM780201 -0.090058 -0.408793 0.894191 \n", + "FULL_GEOR030101 -0.230417 -0.160269 -0.029085 \n", + "FULL_OOBM850104 -0.230561 -0.336297 0.275640 \n", + "NT_EFC195 1.000000 0.178683 -0.036844 \n", + "AS_MeanAmphiMoment 0.178683 1.000000 -0.322378 \n", + "AS_DAYM780201 -0.036844 -0.322378 1.000000 \n", + "AS_FUKS010112 0.145924 0.025580 0.045562 \n", + "CT_RACS820104 0.080898 0.171524 -0.256060 \n", + "CLASS 0.260702 0.693552 -0.437168 \n", + "\n", + " AS_FUKS010112 CT_RACS820104 CLASS \n", + "FULL_Charge -0.090570 0.232929 0.534602 \n", + "FULL_AcidicMolPerc 0.002334 -0.213543 -0.598816 \n", + "FULL_AURR980107 0.032958 -0.403599 -0.584111 \n", + "FULL_DAYM780201 0.055915 -0.326792 -0.554838 \n", + "FULL_GEOR030101 0.040480 -0.151935 -0.260470 \n", + "FULL_OOBM850104 -0.452769 0.155304 -0.453287 \n", + "NT_EFC195 0.145924 0.080898 0.260702 \n", + "AS_MeanAmphiMoment 0.025580 0.171524 0.693552 \n", + "AS_DAYM780201 0.045562 -0.256060 -0.437168 \n", + "AS_FUKS010112 1.000000 -0.445284 0.033432 \n", + "CT_RACS820104 -0.445284 1.000000 0.267652 \n", + "CLASS 0.033432 0.267652 1.000000 " + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Correlation between attributes \n", + "correlations = amp_train.corr(method=\"pearson\") # calculates pairwaise correlation for the attributes \n", + "\n", + "#print(correlations) #you don't always have to use print()\n", + "\n", + "correlations\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "FULL_AURR980107 and FULL_AcidicMolPerc have a correlation coefficent of 0.79, this might mean these two attributes may be some what correlated. Same goes for AS_DAYM780201 and FULL_DAYM780201 (correlation coefficient is 0.894191)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Plots to visualize the correlations\n", + "from matplotlib import rcParams\n", + "sns.heatmap(correlations, annot=True)\n", + "rcParams['figure.figsize'] = 11.7,8.27\n", + "\n", + "\n", + "## Note!!\n", + "# import matplotlib.pyplot as plt\n", + "# You can use the function: plt.figure(figsize=(x,x))\n", + "# import matplotlib.pyplot as plt --> to do your plotting it gives more choices.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Data skewness\n", + "\n", + "Most machine learning algorithms assume that data from the attributes is normally distributed, so identifying attributes with data that has a left or right skew, can be important as this can be easily corrected" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "FULL_Charge 0.601716\n", + "FULL_AcidicMolPerc 0.994487\n", + "FULL_AURR980107 0.490291\n", + "FULL_DAYM780201 -0.216841\n", + "FULL_GEOR030101 0.883022\n", + "FULL_OOBM850104 -0.207124\n", + "NT_EFC195 2.898124\n", + "AS_MeanAmphiMoment 0.383682\n", + "AS_DAYM780201 -0.070879\n", + "AS_FUKS010112 -0.112632\n", + "CT_RACS820104 0.999487\n", + "CLASS 0.000000\n", + "dtype: float64\n" + ] + } + ], + "source": [ + "sk = amp_train.skew() # calculates the skew for each attribute\n", + "print(sk)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Negative values like those of FULL_DAYM780201, FULL_OOBM850104,AS_DAYM780201, AS_FUKS010112, indicate that these attributes have values skewed more to the left\n", + "Values closer to zero are indicative of a less or no skew, while positive values would mean that that particular attribute is skewed more to the right" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " # Visualising data distributions with plots" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Plot one, histogram to show the distributions\n", + "import matplotlib as plot \n", + "from matplotlib import pyplot\n", + "amp_train.hist(layout=(4,3), figsize=(16,16))\n", + "plot.pyplot.subplots_adjust(wspace=0.4, hspace=0.5)\n", + "pyplot.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Plot two density plots can show the distributions better\n", + "amp_train.plot(kind=\"density\",subplots=True,layout=(4,3),sharex=False,sharey=False, figsize=(16,16))\n", + "#amp_train.plot(kind=\"density\",subplots=False,layout=(4,3),sharex=True,sharey=True)\n", + "pyplot.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Data transformations\n", + "Using square roots to transform the attributes with negative values into postives\n", + "\n", + "\n", + "# Note!\n", + "\n", + "Is there a way to render these side by side such that we will be able to see how the transformation affects the originals" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "```\n", + "neg1=amp_train.iloc[:,0]\n", + "print(neg1) #plot this so that we can see how it looks before\n", + "tneg1=neg1**2\n", + "tneg1.plot(kind=\"density\") #plot side by side to see what the transformation does.\n", + "amp_train.iloc[:,0]=tneg1\n", + "\n", + "```" + ] + }, + { + "cell_type": "raw", + "metadata": {}, + "source": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "neg2=amp_train.iloc[:,5]\n", + "print(neg2)\n", + "tneg2=neg2**2\n", + "tneg2.plot(kind=\"density\")\n", + "amp_train.iloc[:,5]=tneg2\n", + "\n", + "## test\n", + "neg3=test_data.iloc[:,0]\n", + "print(neg3)\n", + "tneg3=neg3**2\n", + "tneg3.plot(kind=\"density\")\n", + "test_data.iloc[:,0]=tneg3\n", + "\n", + "\n", + "\n", + "neg4=test_data.iloc[:,5]\n", + "print(neg4)\n", + "tneg4=neg4**2\n", + "tneg4.plot(kind=\"density\")\n", + "test_data.iloc[:,5]=tneg4" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "distributions for AS_MeanAmphiMoment,FULL_AcidicMolPerc and NT_EFC195 dont look so good" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Feature selection\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(3038, 8)\n" + ] + }, + { + "data": { + "text/html": [ + "
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FULL_ChargeFULL_AcidicMolPercFULL_DAYM780201FULL_OOBM850104AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CLASS
05.00.00074.842-3.6630.28273.4445.6611.0
14.05.40571.595-4.0110.60068.2226.5371.0
25.55.40573.595-2.5120.59369.4444.9341.0
35.04.16766.250-1.3620.61467.2224.3161.0
47.58.53764.720-2.0910.61672.9444.5401.0
\n", + "
" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_DAYM780201 FULL_OOBM850104 \\\n", + "0 5.0 0.000 74.842 -3.663 \n", + "1 4.0 5.405 71.595 -4.011 \n", + "2 5.5 5.405 73.595 -2.512 \n", + "3 5.0 4.167 66.250 -1.362 \n", + "4 7.5 8.537 64.720 -2.091 \n", + "\n", + " AS_MeanAmphiMoment AS_DAYM780201 AS_FUKS010112 CLASS \n", + "0 0.282 73.444 5.661 1.0 \n", + "1 0.600 68.222 6.537 1.0 \n", + "2 0.593 69.444 4.934 1.0 \n", + "3 0.614 67.222 4.316 1.0 \n", + "4 0.616 72.944 4.540 1.0 " + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + " #test one selecting out features with low variance\n", + "from sklearn.feature_selection import VarianceThreshold\n", + "sel = VarianceThreshold(threshold=(.8 * (1 - .8)))\n", + "k=sel.fit_transform(amp_train) #fit the algorithm\n", + "\n", + "names=amp_train.columns[sel.get_support(indices=True)] #mapping the names\n", + "print(k.shape) #dimensions of the new data\n", + "amp_train2=pd.DataFrame(k,columns=names)\n", + "\n", + "amp_train2.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "ename": "ValueError", + "evalue": "Input X must be non-negative.", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mtest\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mSelectKBest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscore_func\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mchi2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 12\u001b[0;31m \u001b[0mfit\u001b[0m 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\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mscore_func\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 350\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscore_func_ret\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mlist\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtuple\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 351\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mscores_\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpvalues_\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mscore_func_ret\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/sklearn/feature_selection/_univariate_selection.py\u001b[0m in \u001b[0;36mchi2\u001b[0;34m(X, y)\u001b[0m\n\u001b[1;32m 214\u001b[0m \u001b[0mX\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcheck_array\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maccept_sparse\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'csr'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 215\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0many\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0missparse\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 216\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Input X must be non-negative.\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 217\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 218\u001b[0m \u001b[0mY\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mLabelBinarizer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit_transform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mValueError\u001b[0m: Input X must be non-negative." + ] + } + ], + "source": [ + "#test two\n", + "from sklearn.feature_selection import SelectKBest\n", + "from sklearn.feature_selection import chi2\n", + "\n", + "test_array = amp_train2.values\n", + "\n", + "test_atr = test_array[:,0:7]\n", + "class_atr = test_array[:,7]\n", + "\n", + "\n", + "test = SelectKBest(score_func=chi2, k=5)\n", + "fit = test.fit(test_atr, class_atr)\n", + "\n", + "\n", + "print(fit.scores_)\n", + "features = fit.transform(test_atr)\n", + "names2=amp_train2.columns[fit.get_support(indices=True)]\n", + "amp_train3=pd.DataFrame(features,columns=names2)\n", + "print(amp_train3[5:])\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Index(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'AS_MeanAmphiMoment',\n", + " 'AS_FUKS010112'],\n", + " dtype='object')\n", + "Index(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_OOBM850104',\n", + " 'AS_MeanAmphiMoment'],\n", + " dtype='object')\n", + "Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201',\n", + " 'FULL_OOBM850104', 'AS_MeanAmphiMoment'],\n", + " dtype='object')\n", + "Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", + " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", + " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", + " 'CLASS'],\n", + " dtype='object')\n", + " FULL_Charge FULL_AcidicMolPerc FULL_DAYM780201 FULL_OOBM850104 \\\n", + "0 25.00 0.000 74.842 13.417569 \n", + "1 16.00 5.405 71.595 16.088121 \n", + "2 30.25 5.405 73.595 6.310144 \n", + "3 25.00 4.167 66.250 1.855044 \n", + "4 56.25 8.537 64.720 4.372281 \n", + "5 25.00 7.692 78.949 9.554281 \n", + "6 9.00 6.897 78.586 12.559936 \n", + "7 4.00 5.882 76.588 34.012224 \n", + "8 49.00 2.632 60.447 0.085264 \n", + "9 81.00 0.000 65.808 15.116544 \n", + "10 4.00 3.448 71.172 13.778944 \n", + "11 6.25 0.000 60.579 1.852321 \n", + "12 9.00 0.000 70.875 12.981609 \n", + "13 9.00 7.143 71.357 18.748900 \n", + "14 6.25 7.692 60.769 13.256881 \n", + "15 36.00 4.348 67.870 2.050624 \n", + "16 4.00 0.000 73.842 24.285184 \n", + "17 16.00 0.000 64.083 24.770529 \n", + "18 20.25 11.111 77.185 0.481636 \n", + "19 4.00 4.167 68.667 9.778129 \n", + "20 4.00 6.667 68.233 11.068929 \n", + "21 9.00 10.345 72.000 22.127616 \n", + "22 12.25 2.703 72.919 13.162384 \n", + "23 1.00 0.000 52.769 21.696964 \n", + "24 1.00 0.000 63.231 16.483600 \n", + "25 30.25 4.348 58.913 22.619536 \n", + "26 42.25 0.000 63.917 11.703241 \n", + "27 1.00 5.556 74.833 15.038884 \n", + "28 42.25 0.000 66.500 17.926756 \n", + "29 56.25 8.333 69.375 3.115225 \n", + "... ... ... ... ... \n", + "3008 36.00 20.000 83.686 2.033476 \n", + "3009 1.00 22.500 77.700 0.045796 \n", + "3010 1.00 12.500 79.708 1.575025 \n", + "3011 0.00 5.263 73.079 2.334784 \n", + "3012 9.00 19.608 83.412 1.058841 \n", + "3013 1.00 12.245 76.122 2.849344 \n", + "3014 1.00 16.667 80.250 0.122500 \n", + "3015 4.00 10.811 67.514 5.017600 \n", + "3016 1.00 8.333 71.000 2.214144 \n", + "3017 0.00 10.256 80.077 1.153476 \n", + "3018 0.00 18.750 88.250 1.726596 \n", + "3019 0.25 16.667 77.729 1.334025 \n", + "3020 0.25 11.429 77.657 0.819025 \n", + "3021 1.00 11.538 78.038 0.040000 \n", + "3022 9.00 0.000 66.769 0.029929 \n", + "3023 4.00 12.000 75.867 2.005056 \n", + "3024 12.25 20.000 73.050 7.823209 \n", + "3025 6.25 10.714 78.071 8.334769 \n", + "3026 0.25 0.000 81.545 0.381924 \n", + "3027 81.00 7.547 77.283 11.682724 \n", + "3028 4.00 18.750 79.938 1.196836 \n", + "3029 20.25 14.286 69.143 1.177225 \n", + "3030 4.00 12.963 72.815 11.874916 \n", + "3031 0.00 17.021 76.234 5.143824 \n", + "3032 0.00 16.667 82.917 4.297329 \n", + "3033 1.00 5.263 67.947 4.626801 \n", + "3034 42.25 21.667 75.433 2.805625 \n", + "3035 2.25 12.500 76.542 0.842724 \n", + "3036 4.00 5.000 73.750 7.409284 \n", + "3037 1.00 15.789 66.158 4.326400 \n", + "\n", + " AS_MeanAmphiMoment AS_DAYM780201 AS_FUKS010112 CLASS \n", + "0 0.282 73.444 5.661 1.0 \n", + "1 0.600 68.222 6.537 1.0 \n", + "2 0.593 69.444 4.934 1.0 \n", + "3 0.614 67.222 4.316 1.0 \n", + "4 0.616 72.944 4.540 1.0 \n", + "5 0.511 78.778 5.992 1.0 \n", + "6 0.385 78.222 6.284 1.0 \n", + "7 0.154 76.588 6.479 1.0 \n", + "8 0.188 64.333 3.849 1.0 \n", + "9 0.361 63.222 6.327 1.0 \n", + "10 0.510 76.389 5.402 1.0 \n", + "11 0.163 61.667 5.627 1.0 \n", + "12 0.263 71.611 6.804 1.0 \n", + "13 0.232 72.778 6.726 1.0 \n", + "14 0.402 60.769 7.112 1.0 \n", + "15 0.187 65.167 5.238 1.0 \n", + "16 0.536 75.667 6.996 1.0 \n", + "17 0.826 65.944 6.038 1.0 \n", + "18 1.100 78.444 6.141 1.0 \n", + "19 1.210 66.944 6.149 1.0 \n", + "20 1.304 73.500 6.604 1.0 \n", + "21 1.726 61.056 5.722 1.0 \n", + "22 1.717 70.833 6.669 1.0 \n", + "23 2.834 52.769 7.426 1.0 \n", + "24 2.980 63.231 6.942 1.0 \n", + "25 2.138 63.444 7.546 1.0 \n", + "26 2.435 62.056 6.801 1.0 \n", + "27 2.044 74.833 6.644 1.0 \n", + "28 2.704 69.444 5.673 1.0 \n", + "29 2.743 65.889 5.242 1.0 \n", + "... ... ... ... ... \n", + "3008 15.452 81.722 6.566 0.0 \n", + "3009 15.625 78.333 5.747 0.0 \n", + "3010 15.502 75.556 5.558 0.0 \n", + "3011 15.676 70.556 5.723 0.0 \n", + "3012 15.813 75.111 6.378 0.0 \n", + "3013 15.774 78.278 6.374 0.0 \n", + "3014 23.502 80.250 5.325 0.0 \n", + "3015 15.974 65.944 5.169 0.0 \n", + "3016 23.550 71.000 5.017 0.0 \n", + "3017 15.781 80.167 6.149 0.0 \n", + "3018 17.666 88.250 6.383 0.0 \n", + "3019 15.838 80.111 6.138 0.0 \n", + "3020 15.867 74.167 5.523 0.0 \n", + "3021 16.209 79.944 5.267 0.0 \n", + "3022 22.477 66.769 6.068 0.0 \n", + "3023 16.444 74.111 5.611 0.0 \n", + "3024 16.495 74.944 6.606 0.0 \n", + "3025 16.513 82.056 5.732 0.0 \n", + "3026 26.931 81.545 5.120 0.0 \n", + "3027 16.517 78.111 5.451 0.0 \n", + "3028 18.119 79.938 6.241 0.0 \n", + "3029 20.625 69.143 5.769 0.0 \n", + "3030 16.256 65.722 6.378 0.0 \n", + "3031 16.365 77.278 5.821 0.0 \n", + "3032 24.497 82.917 5.640 0.0 \n", + "3033 16.706 68.611 5.598 0.0 \n", + "3034 16.897 73.278 6.194 0.0 \n", + "3035 16.918 82.111 5.889 0.0 \n", + "3036 17.131 74.722 6.055 0.0 \n", + "3037 17.151 67.111 5.853 0.0 \n", + "\n", + "[3038 rows x 8 columns]\n" + ] + } + ], + "source": [ + "# Test three Recursive feature elimination\n", + "\n", + "from sklearn.feature_selection import RFE\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.ensemble import RandomForestClassifier\n", + "\n", + "model1 = LogisticRegression()\n", + "model2=RandomForestClassifier()\n", + "\n", + "rfe = RFE(model1, 4)\n", + "fit2 = rfe.fit(test_atr, class_atr)\n", + "\n", + "rfe2= RFE(model2, 4)\n", + "fit3 = rfe2.fit(test_atr, class_atr)\n", + "\n", + "\n", + "\n", + "\n", + "names3=amp_train2.columns[fit2.get_support(indices=True)]\n", + "\n", + "names4=amp_train2.columns[fit3.get_support(indices=True)]\n", + "\n", + "#print(names3)\n", + "#print(names4)\n", + "#print(names2)\n", + "#print(amp_train.columns)\n", + "#print(amp_train2)\n", + "\n", + "#transformer functions\n", + "# When we use a fit function we normally folow with a transformation function.\n", + "# That way we can change our data the same way for the test and train dataset.\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Note\n", + "\n", + "Why not use the transform method to change " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "test_amp =amp_train.loc[:,['FULL_Charge', 'FULL_AcidicMolPerc',\"FULL_OOBM850104\",'FULL_DAYM780201', 'AS_MeanAmphiMoment','CLASS']]\n", + "print(test_amp)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.metrics import confusion_matrix\n", + "\n", + "\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", + "from sklearn.naive_bayes import GaussianNB\n", + "from sklearn.svm import SVC\n", + "from sklearn.neighbors import KNeighborsClassifier\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Logistic regression using cross validation" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "X=test_amp.iloc[:,0:5]\n", + "Y=test_amp.iloc[:,5]\n", + "folds=10\n", + "kfold = KFold(n_splits=folds, random_state=7, shuffle=True,)\n", + "model = LogisticRegression()\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "\n", + "print((\"Accuracy: %.3f%% (%.3f%%)\") % (results.mean()*100.0, results.std()*100.0))\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "test_data = pd.read_csv(\"/kaggle/input/ace-class-assignment/Test.csv\", header=0, sep=\",\")\n", + "amp_train = pd.read_csv(\"/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\", header=0, sep=\",\")\n", + "test_amp =amp_train.loc[:,['FULL_Charge', 'FULL_AcidicMolPerc',\"FULL_OOBM850104\",'FULL_DAYM780201', 'AS_MeanAmphiMoment','CLASS']]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Logistic regression with a test train split" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.metrics import matthews_corrcoef\n", + "test_amp=test_amp.values\n", + "#X=test_amp.iloc[:,0:5]\n", + "X=test_amp[:,0:5]\n", + "Y=test_amp[:,5]\n", + "\n", + "#Y=test_amp.iloc[:,5]\n", + "#print(Y)\n", + "test_size = 0.4\n", + "seed = 25\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\n", + "model = LogisticRegression()\n", + "model.fit(X_train, Y_train)\n", + "predicted = model.predict(X_test)\n", + "matrix = confusion_matrix(Y_test, predicted)\n", + "result = model.score(X_test, Y_test)\n", + "print(\"Accuracy: \", (result*100.0))\n", + "print(matrix)\n", + "print('MCC: ', matthews_corrcoef(model.predict(X_test),Y_test))\n", + "#print(test_data)\n", + "\n", + "test_data2=test_data.loc[:,['FULL_Charge', 'FULL_AcidicMolPerc','FULL_DAYM780201', 'FULL_OOBM850104', 'AS_MeanAmphiMoment']]\n", + "test_data2=test_data2.values \n", + "#model1 = LogisticRegression() \n", + "#model1.fit(X,Y)\n", + "kj_results=model.predict(test_data2)\n", + "\n", + "#print(test_data2)\n", + "kj_results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.DataFrame(kj_results)\n", + "df.columns = ['CLASS']\n", + "df.index.name = 'Index'\n", + "df['CLASS']=df['CLASS'].map({0.0:False,1.0:True})\n", + "print(df)\n", + "#X=test_amp.iloc[:,0:5]\n", + "#=test_amp.iloc[:,5]\n", + "df.to_csv(\"kj.csv\")\n", + "df[\"CLASS\"].unique()\n", + "#print(df.groupby(\"CLASS\").size()[0].sum())\n", + "#print(df.groupby(\"CLASS\").size()[1].sum())\n", + "df['CLASS'].value_counts()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Gausian/Naive Bayes" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "model=GaussianNB()\n", + "from sklearn.metrics import matthews_corrcoef\n", + "test_size = 0.4\n", + "seed = 25\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", + "random_state=seed)\n", + "model.fit(X_train, Y_train)\n", + "predicted = model.predict(X_test)\n", + "matrix = confusion_matrix(Y_test, predicted)\n", + "result = model.score(X_test, Y_test)\n", + "print(\"Accuracy: \", (result*100.0))\n", + "print(matrix)\n", + "print('MCC: ', matthews_corrcoef(model.predict(X_test),Y_test))\n", + "#print(test_data)\n", + "\n", + "X=test_amp.iloc[:,0:5]\n", + "Y=test_amp.iloc[:,5]\n", + "model=GaussianNB() \n", + "model.fit(X,Y)\n", + "kj_results=model.predict(test_data2)\n", + "\n", + "#print(test_data2)\n", + "kj_results" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Linear Discriminant Analysis" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "model=LinearDiscriminantAnalysis()\n", + "folds=10\n", + "kfold = KFold(n_splits=folds, random_state=7, shuffle=True,)\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print((\"Accuracy: %.3f%% (%.3f%%)\") % (results.mean()*100.0, results.std()*100.0))\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Support Vector Machines" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "model=SVC()\n", + "folds=10\n", + "kfold = KFold(n_splits=folds, random_state=7, shuffle=True,)\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print((\"Accuracy: %.3f%% (%.3f%%)\") % (results.mean()*100.0, results.std()*100.0))" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.4" + }, + "varInspector": { + "cols": { + "lenName": 16, + "lenType": 16, + "lenVar": 40 + }, + "kernels_config": { + "python": { + "delete_cmd_postfix": "", + "delete_cmd_prefix": "del ", + "library": "var_list.py", + "varRefreshCmd": "print(var_dic_list())" + }, + "r": { + "delete_cmd_postfix": ") ", + "delete_cmd_prefix": "rm(", + "library": "var_list.r", + "varRefreshCmd": "cat(var_dic_list()) " + } + }, + "types_to_exclude": [ + "module", + "function", + "builtin_function_or_method", + "instance", + "_Feature" + ], + "window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/Assignment Colab/Jupiter Marina.ipynb b/Assignment Colab/Jupiter Marina.ipynb index 2f0b44b..16c3b99 100644 --- a/Assignment Colab/Jupiter Marina.ipynb +++ b/Assignment Colab/Jupiter Marina.ipynb @@ -1 +1,1786 @@ -{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\nimport matplotlib as plot\nimport seaborn as sns\nimport sklearn\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n for filename in filenames:\n print(os.path.join(dirname, filename))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Importing data"},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"# Importing data\ntest_data = pd.read_csv(\"/kaggle/input/ace-class-assignment/Test.csv\", header=0, sep=\",\")\namp_train = pd.read_csv(\"/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\", header=0, sep=\",\")\nprint(amp_train)\n#print(test)\n\n\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"amp_train.columns","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#test_amp =amp_train[['FULL_Charge', 'FULL_AcidicMolPerc','FULL_OOBM850104','FULL_DAYM780201', 'AS_MeanAmphiMoment','CLASS']]\n#print(test_amp)\n#test_data=test_data[['FULL_Charge', 'FULL_AcidicMolPerc','FULL_OOBM850104','FULL_DAYM780201', 'AS_MeanAmphiMoment']]\n#X=test_amp.drop(\"CLASS\",axis=1)\n#Y=test_amp.CLASS\n#model=GaussianNB() \n#model.fit(X,Y)\n#kj_results=model.predict(test_data)\n\n#print(test_data2)\n#kj_results","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## General data attributes and descriptive statistics"},{"metadata":{"trusted":true},"cell_type":"code","source":"#Describing general data attributes\ntrain_dim=amp_train.shape #gets the dimensions of the tranining dataset\ntest_dim= test_data.shape #gets the dimensions of the tesing dataset\nprint(train_dim)\nprint(test_dim)\n\natr_types=amp_train.dtypes #gets the data type for each column in training dataset\nprint(atr_types)\namp_train.isnull().sum() # gets the sum of the missing values/observations in each column\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Descriptive statistics \nstats=amp_train.describe()\nprint(stats)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Class distributions\n\nSometimes, observations from the different classes may not be equal, these may need special handling, so its important to note the class distributions, as if they are uneven, they may bias our model"},{"metadata":{"trusted":true},"cell_type":"code","source":"# CLass distibutions \ncdists= amp_train.groupby('CLASS').size() # groups the observation by the column of class, and counts all the observations including null values\nprint(cdists)\n\n#plots to visualize the class distribution\namp_train.groupby('CLASS').size().plot(kind=\"pie\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"The observations from each class seem to be equal"},{"metadata":{},"cell_type":"markdown","source":"# Correlation between the different attributes\nBasically, we need to examine our attributes for correlation as highly correlated attributes present the same data to the algorithm. Removing one may speed learning of the algorithm (less dimensions more speed)"},{"metadata":{"trusted":true},"cell_type":"code","source":"# Correlation between attributes \ncorrelations = amp_train.corr(method=\"pearson\") # calculates pairwaise correlation for the attributes \nprint(correlations)\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"FULL_AURR980107 and FULL_AcidicMolPerc have a correlation coefficent of 0.79, this might mean these two attributes may be some what correlated. Same goes for AS_DAYM780201 and FULL_DAYM780201 (correlation coefficient is 0.894191)"},{"metadata":{"trusted":true},"cell_type":"code","source":"# Plots to visualize the correlations\nfrom matplotlib import rcParams\nsns.heatmap(correlations, annot=True)\nrcParams['figure.figsize'] = 11.7,8.27\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Data skewness\n\nMost machine learning algorithms assume that data from the attributes is normally distributed, so identifying attributes with data that has a left or right skew, can be important as this can be easily corrected"},{"metadata":{"trusted":true},"cell_type":"code","source":"sk = amp_train.skew() # calculates the skew for each attribute\nprint(sk)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Negative values like those of FULL_DAYM780201, FULL_OOBM850104,AS_DAYM780201, AS_FUKS010112, indicate that these attributes have values skewed more to the left\nValues closer to zero are indicative of a less or no skew, while positive values would mean that that particular attribute is skewed more to the right"},{"metadata":{},"cell_type":"markdown","source":" # Visualising data distributions with plots"},{"metadata":{"trusted":true},"cell_type":"code","source":"# Plot one, histogram to show the distributions\nimport matplotlib as plot \nfrom matplotlib import pyplot\namp_train.hist(layout=(4,3), figsize=(16,16))\nplot.pyplot.subplots_adjust(wspace=0.4, hspace=0.5)\npyplot.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Plot two density plots can show the distributions better\namp_train.plot(kind=\"density\",subplots=True,layout=(4,3),sharex=False,sharey=False, figsize=(16,16))\n#amp_train.plot(kind=\"density\",subplots=False,layout=(4,3),sharex=True,sharey=True)\npyplot.show()\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Data transformations\nUsing square roots to transform the attributes with negative values into postives"},{"metadata":{"trusted":true},"cell_type":"code","source":"\nneg1=amp_train.iloc[:,0]\nprint(neg1)\ntneg1=neg1**2\ntneg1.plot(kind=\"density\")\namp_train.iloc[:,0]=tneg1\n\n\n\nneg2=amp_train.iloc[:,5]\nprint(neg2)\ntneg2=neg2**2\ntneg2.plot(kind=\"density\")\namp_train.iloc[:,5]=tneg2\n\n## test\nneg3=test_data.iloc[:,0]\nprint(neg3)\ntneg3=neg3**2\ntneg3.plot(kind=\"density\")\ntest_data.iloc[:,0]=tneg3\n\n\n\nneg4=test_data.iloc[:,5]\nprint(neg4)\ntneg4=neg4**2\ntneg4.plot(kind=\"density\")\ntest_data.iloc[:,5]=tneg4","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"distributions for AS_MeanAmphiMoment,FULL_AcidicMolPerc and NT_EFC195 dont look so good"},{"metadata":{},"cell_type":"markdown","source":"# Feature selection\n\n\n"},{"metadata":{"trusted":true},"cell_type":"code","source":" #test one selecting out features with low variance\nfrom sklearn.feature_selection import VarianceThreshold\nsel = VarianceThreshold(threshold=(.8 * (1 - .8)))\nk=sel.fit_transform(amp_train)\nnames=amp_train.columns[sel.get_support(indices=True)]\nprint(k.shape)\namp_train2=pd.DataFrame(k,columns=names)\nprint(amp_train2)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#test two\nfrom sklearn.feature_selection import SelectKBest\nfrom sklearn.feature_selection import chi2\n\ntest_array = amp_train2.values\n\ntest_atr = test_array[:,0:7]\nclass_atr = test_array[:,7]\n\n\ntest = SelectKBest(score_func=chi2, k=5)\nfit = test.fit(test_atr, class_atr)\n\n\nprint(fit.scores_)\nfeatures = fit.transform(test_atr)\nnames2=amp_train2.columns[fit.get_support(indices=True)]\namp_train3=pd.DataFrame(features,columns=names2)\nprint(amp_train3[5:])\n\n\n\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Test three Recursive feature elimination\n\nfrom sklearn.feature_selection import RFE\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.ensemble import RandomForestClassifier\n\nmodel1 = LogisticRegression()\nmodel2=RandomForestClassifier()\n\nrfe = RFE(model1, 4)\nfit2 = rfe.fit(test_atr, class_atr)\n\nrfe2= RFE(model2, 4)\nfit3 = rfe2.fit(test_atr, class_atr)\n\n\n\n\nnames3=amp_train2.columns[fit2.get_support(indices=True)]\n\nnames4=amp_train2.columns[fit3.get_support(indices=True)]\n\nprint(names3)\nprint(names4)\nprint(names2)\nprint(amp_train.columns)\nprint(amp_train2)\n\n\n\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"test_amp =amp_train.loc[:,['FULL_Charge', 'FULL_AcidicMolPerc',\"FULL_OOBM850104\",'FULL_DAYM780201', 'AS_MeanAmphiMoment','CLASS']]\nprint(test_amp)\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import train_test_split\nfrom sklearn.model_selection import KFold\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.metrics import confusion_matrix\n\n\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.svm import SVC\nfrom sklearn.neighbors import KNeighborsClassifier\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Logistic regression using cross validation"},{"metadata":{"trusted":true},"cell_type":"code","source":"\nX=test_amp.iloc[:,0:5]\nY=test_amp.iloc[:,5]\nfolds=10\nkfold = KFold(n_splits=folds, random_state=7, shuffle=True,)\nmodel = LogisticRegression()\nresults = cross_val_score(model, X, Y, cv=kfold)\n\nprint((\"Accuracy: %.3f%% (%.3f%%)\") % (results.mean()*100.0, results.std()*100.0))\n\n\n\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"test_data = pd.read_csv(\"/kaggle/input/ace-class-assignment/Test.csv\", header=0, sep=\",\")\namp_train = pd.read_csv(\"/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\", header=0, sep=\",\")\ntest_amp =amp_train.loc[:,['FULL_Charge', 'FULL_AcidicMolPerc',\"FULL_OOBM850104\",'FULL_DAYM780201', 'AS_MeanAmphiMoment','CLASS']]","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Logistic regression with a test train split"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.metrics import matthews_corrcoef\ntest_amp=test_amp.values\n#X=test_amp.iloc[:,0:5]\nX=test_amp[:,0:5]\nY=test_amp[:,5]\n\n#Y=test_amp.iloc[:,5]\n#print(Y)\ntest_size = 0.4\nseed = 25\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\nmodel = LogisticRegression()\nmodel.fit(X_train, Y_train)\npredicted = model.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult = model.score(X_test, Y_test)\nprint(\"Accuracy: \", (result*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model.predict(X_test),Y_test))\n#print(test_data)\n\ntest_data2=test_data.loc[:,['FULL_Charge', 'FULL_AcidicMolPerc','FULL_DAYM780201', 'FULL_OOBM850104', 'AS_MeanAmphiMoment']]\ntest_data2=test_data2.values \n#model1 = LogisticRegression() \n#model1.fit(X,Y)\nkj_results=model.predict(test_data2)\n\n#print(test_data2)\nkj_results","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df = pd.DataFrame(kj_results)\ndf.columns = ['CLASS']\ndf.index.name = 'Index'\ndf['CLASS']=df['CLASS'].map({0.0:False,1.0:True})\nprint(df)\n#X=test_amp.iloc[:,0:5]\n#=test_amp.iloc[:,5]\ndf.to_csv(\"kj.csv\")\ndf[\"CLASS\"].unique()\n#print(df.groupby(\"CLASS\").size()[0].sum())\n#print(df.groupby(\"CLASS\").size()[1].sum())\ndf['CLASS'].value_counts()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Gausian/Naive Bayes"},{"metadata":{"trusted":true},"cell_type":"code","source":"model=GaussianNB()\nfrom sklearn.metrics import matthews_corrcoef\ntest_size = 0.4\nseed = 25\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\nrandom_state=seed)\nmodel.fit(X_train, Y_train)\npredicted = model.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult = model.score(X_test, Y_test)\nprint(\"Accuracy: \", (result*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model.predict(X_test),Y_test))\n#print(test_data)\n\nX=test_amp.iloc[:,0:5]\nY=test_amp.iloc[:,5]\nmodel=GaussianNB() \nmodel.fit(X,Y)\nkj_results=model.predict(test_data2)\n\n#print(test_data2)\nkj_results","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Linear Discriminant Analysis"},{"metadata":{"trusted":true},"cell_type":"code","source":"model=LinearDiscriminantAnalysis()\nfolds=10\nkfold = KFold(n_splits=folds, random_state=7, shuffle=True,)\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint((\"Accuracy: %.3f%% (%.3f%%)\") % (results.mean()*100.0, results.std()*100.0))\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Support Vector Machines"},{"metadata":{"trusted":true},"cell_type":"code","source":"model=SVC()\nfolds=10\nkfold = KFold(n_splits=folds, random_state=7, shuffle=True,)\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint((\"Accuracy: %.3f%% (%.3f%%)\") % (results.mean()*100.0, results.std()*100.0))","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4} \ No newline at end of file +{ + "cells": [ + { + "cell_type": "raw", + "metadata": { + "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", + "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" + }, + "source": [ + "# This Python 3 environment comes with many helpful analytics libraries installed\n", + "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", + "# For example, here's several helpful packages to load in \n", + "\n", + "import numpy as np # linear algebra\n", + "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", + "import matplotlib as plot\n", + "import seaborn as sns\n", + "import sklearn\n", + "\n", + "# Input data files are available in the \"../input/\" directory.\n", + "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", + "\n", + "import os\n", + "for dirname, _, filenames in os.walk('/kaggle/input'):\n", + " for filename in filenames:\n", + " print(os.path.join(dirname, filename))\n", + "\n", + "# Any results you write to the current directory are saved as output." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np # linear algebra\n", + "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", + "import matplotlib as plot\n", + "import seaborn as sns\n", + "import sklearn" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Importing data" + ] + }, + { + "cell_type": "code", + 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" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n", + "0 5.0 0.000 0.951 74.842 \n", + "1 4.0 5.405 0.931 71.595 \n", + "2 5.5 5.405 0.873 73.595 \n", + "3 5.0 4.167 0.895 66.250 \n", + "4 7.5 8.537 0.932 64.720 \n", + "\n", + " FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n", + "0 0.975 -3.663 0 0.282 \n", + "1 0.957 -4.011 1 0.600 \n", + "2 0.961 -2.512 0 0.593 \n", + "3 0.999 -1.362 0 0.614 \n", + "4 0.979 -2.091 0 0.616 \n", + "\n", + " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 CLASS \n", + "0 73.444 5.661 1.041 1 \n", + "1 68.222 6.537 1.453 1 \n", + "2 69.444 4.934 1.722 1 \n", + "3 67.222 4.316 1.382 1 \n", + "4 72.944 4.540 1.539 1 " + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Importing data\n", + "test_data = pd.read_csv(\"../AMP Data Sets/Test.csv\", header=0, sep=\",\")\n", + "amp_train = pd.read_csv(\"../AMP Data Sets/AMP_TrainSet.csv\", header=0, sep=\",\")\n", + "#print(amp_train)\n", + "\n", + "\n", + "amp_train.head()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", + " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", + " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", + " 'CLASS'],\n", + " dtype='object')" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "amp_train.columns" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#test_amp =amp_train[['FULL_Charge', 'FULL_AcidicMolPerc','FULL_OOBM850104','FULL_DAYM780201', 'AS_MeanAmphiMoment','CLASS']]\n", + "#print(test_amp)\n", + "#test_data=test_data[['FULL_Charge', 'FULL_AcidicMolPerc','FULL_OOBM850104','FULL_DAYM780201', 'AS_MeanAmphiMoment']]\n", + "#X=test_amp.drop(\"CLASS\",axis=1)\n", + "#Y=test_amp.CLASS\n", + "#model=GaussianNB() \n", + "#model.fit(X,Y)\n", + "#kj_results=model.predict(test_data)\n", + "\n", + "#print(test_data2)\n", + "#kj_results" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## General data attributes and descriptive statistics" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(3038, 12)\n", + "(758, 11)\n", + "FULL_Charge float64\n", + "FULL_AcidicMolPerc float64\n", + "FULL_AURR980107 float64\n", + "FULL_DAYM780201 float64\n", + "FULL_GEOR030101 float64\n", + "FULL_OOBM850104 float64\n", + "NT_EFC195 int64\n", + "AS_MeanAmphiMoment float64\n", + "AS_DAYM780201 float64\n", + "AS_FUKS010112 float64\n", + "CT_RACS820104 float64\n", + "CLASS int64\n", + "dtype: object\n" + ] + }, + { + "data": { + "text/plain": [ + "FULL_Charge 0\n", + "FULL_AcidicMolPerc 0\n", + "FULL_AURR980107 0\n", + "FULL_DAYM780201 0\n", + "FULL_GEOR030101 0\n", + "FULL_OOBM850104 0\n", + "NT_EFC195 0\n", + "AS_MeanAmphiMoment 0\n", + "AS_DAYM780201 0\n", + "AS_FUKS010112 0\n", + "CT_RACS820104 0\n", + "CLASS 0\n", + "dtype: int64" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Describing general data attributes\n", + "train_dim=amp_train.shape #gets the dimensions of the tranining dataset\n", + "test_dim= test_data.shape #gets the dimensions of the tesing dataset\n", + "print(train_dim)\n", + "print(test_dim)\n", + "\n", + "atr_types=amp_train.dtypes #gets the data type for each column in training dataset\n", + "print(atr_types)\n", + "amp_train.isnull().sum() # gets the sum of the missing values/observations in each column\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Note!!\n", + "You can write the code below as\n", + "\n", + "```\n", + "amp_train.describe()\n", + "\n", + "```\n", + "\n", + "It renders properly when you write it like this, Try it!" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201FULL_GEOR030101FULL_OOBM850104NT_EFC195AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CT_RACS820104CLASS
count3038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.000000
mean2.0602378.5215200.97141073.6687600.994007-2.4329270.08854515.68323373.6508285.9113611.2352550.500000
std3.8199297.5866520.1074138.5274890.0313331.7072230.28413311.5756659.1660920.6936890.2100120.500082
min-16.0000000.0000000.68400042.7500000.866000-10.4320000.0000000.04100042.7780003.5330000.7850000.000000
25%0.0000002.5160000.89500068.2940000.974000-3.6060000.0000005.58750067.5560005.4592501.0820000.000000
50%2.0000007.1430000.96300074.0595000.994000-2.2965000.00000014.98850073.6970005.9255001.1840000.500000
75%4.00000013.1580001.04100079.3437501.011000-1.2832500.00000026.80775079.7780006.3820001.3510001.000000
max30.00000046.6670001.451000101.6820001.1960003.5760001.00000051.280000103.1670008.6620002.1920001.000000
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" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n", + "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", + "mean 2.060237 8.521520 0.971410 73.668760 \n", + "std 3.819929 7.586652 0.107413 8.527489 \n", + "min -16.000000 0.000000 0.684000 42.750000 \n", + "25% 0.000000 2.516000 0.895000 68.294000 \n", + "50% 2.000000 7.143000 0.963000 74.059500 \n", + "75% 4.000000 13.158000 1.041000 79.343750 \n", + "max 30.000000 46.667000 1.451000 101.682000 \n", + "\n", + " FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n", + "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", + "mean 0.994007 -2.432927 0.088545 15.683233 \n", + "std 0.031333 1.707223 0.284133 11.575665 \n", + "min 0.866000 -10.432000 0.000000 0.041000 \n", + "25% 0.974000 -3.606000 0.000000 5.587500 \n", + "50% 0.994000 -2.296500 0.000000 14.988500 \n", + "75% 1.011000 -1.283250 0.000000 26.807750 \n", + "max 1.196000 3.576000 1.000000 51.280000 \n", + "\n", + " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 CLASS \n", + "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", + "mean 73.650828 5.911361 1.235255 0.500000 \n", + "std 9.166092 0.693689 0.210012 0.500082 \n", + "min 42.778000 3.533000 0.785000 0.000000 \n", + "25% 67.556000 5.459250 1.082000 0.000000 \n", + "50% 73.697000 5.925500 1.184000 0.500000 \n", + "75% 79.778000 6.382000 1.351000 1.000000 \n", + "max 103.167000 8.662000 2.192000 1.000000 " + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Descriptive statistics \n", + "stats=amp_train.describe()\n", + "#print(stats)\n", + "\n", + "stats\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Class distributions\n", + "\n", + "Sometimes, observations from the different classes may not be equal, these may need special handling, so its important to note the class distributions, as if they are uneven, they may bias our model" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CLASS\n", + "0 1519\n", + "1 1519\n", + "dtype: int64\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# CLass distibutions \n", + "cdists= amp_train.groupby('CLASS').size() # groups the observation by the column of class, and counts all the observations including null values\n", + "print(cdists)\n", + "\n", + "#plots to visualize the class distribution\n", + "amp_train.groupby('CLASS').size().plot(kind=\"pie\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The observations from each class seem to be equal" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Correlation between the different attributes\n", + "Basically, we need to examine our attributes for correlation as highly correlated attributes present the same data to the algorithm. Removing one may speed learning of the algorithm (less dimensions more speed)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201FULL_GEOR030101FULL_OOBM850104NT_EFC195AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CT_RACS820104CLASS
FULL_Charge1.000000-0.612996-0.490977-0.434603-0.058725-0.2837580.0880680.355477-0.365374-0.0905700.2329290.534602
FULL_AcidicMolPerc-0.6129961.0000000.7947960.5414810.1152010.513344-0.143168-0.4315900.4496210.002334-0.213543-0.598816
FULL_AURR980107-0.4909770.7947961.0000000.5482530.3461390.462712-0.169540-0.4260970.4562600.032958-0.403599-0.584111
FULL_DAYM780201-0.4346030.5414810.5482531.0000000.0101180.334778-0.090058-0.4087930.8941910.055915-0.326792-0.554838
FULL_GEOR030101-0.0587250.1152010.3461390.0101181.0000000.319157-0.230417-0.160269-0.0290850.040480-0.151935-0.260470
FULL_OOBM850104-0.2837580.5133440.4627120.3347780.3191571.000000-0.230561-0.3362970.275640-0.4527690.155304-0.453287
NT_EFC1950.088068-0.143168-0.169540-0.090058-0.230417-0.2305611.0000000.178683-0.0368440.1459240.0808980.260702
AS_MeanAmphiMoment0.355477-0.431590-0.426097-0.408793-0.160269-0.3362970.1786831.000000-0.3223780.0255800.1715240.693552
AS_DAYM780201-0.3653740.4496210.4562600.894191-0.0290850.275640-0.036844-0.3223781.0000000.045562-0.256060-0.437168
AS_FUKS010112-0.0905700.0023340.0329580.0559150.040480-0.4527690.1459240.0255800.0455621.000000-0.4452840.033432
CT_RACS8201040.232929-0.213543-0.403599-0.326792-0.1519350.1553040.0808980.171524-0.256060-0.4452841.0000000.267652
CLASS0.534602-0.598816-0.584111-0.554838-0.260470-0.4532870.2607020.693552-0.4371680.0334320.2676521.000000
\n", + "
" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 \\\n", + "FULL_Charge 1.000000 -0.612996 -0.490977 \n", + "FULL_AcidicMolPerc -0.612996 1.000000 0.794796 \n", + "FULL_AURR980107 -0.490977 0.794796 1.000000 \n", + "FULL_DAYM780201 -0.434603 0.541481 0.548253 \n", + "FULL_GEOR030101 -0.058725 0.115201 0.346139 \n", + "FULL_OOBM850104 -0.283758 0.513344 0.462712 \n", + "NT_EFC195 0.088068 -0.143168 -0.169540 \n", + "AS_MeanAmphiMoment 0.355477 -0.431590 -0.426097 \n", + "AS_DAYM780201 -0.365374 0.449621 0.456260 \n", + "AS_FUKS010112 -0.090570 0.002334 0.032958 \n", + "CT_RACS820104 0.232929 -0.213543 -0.403599 \n", + "CLASS 0.534602 -0.598816 -0.584111 \n", + "\n", + " FULL_DAYM780201 FULL_GEOR030101 FULL_OOBM850104 \\\n", + "FULL_Charge -0.434603 -0.058725 -0.283758 \n", + "FULL_AcidicMolPerc 0.541481 0.115201 0.513344 \n", + "FULL_AURR980107 0.548253 0.346139 0.462712 \n", + "FULL_DAYM780201 1.000000 0.010118 0.334778 \n", + "FULL_GEOR030101 0.010118 1.000000 0.319157 \n", + "FULL_OOBM850104 0.334778 0.319157 1.000000 \n", + "NT_EFC195 -0.090058 -0.230417 -0.230561 \n", + "AS_MeanAmphiMoment -0.408793 -0.160269 -0.336297 \n", + "AS_DAYM780201 0.894191 -0.029085 0.275640 \n", + "AS_FUKS010112 0.055915 0.040480 -0.452769 \n", + "CT_RACS820104 -0.326792 -0.151935 0.155304 \n", + "CLASS -0.554838 -0.260470 -0.453287 \n", + "\n", + " NT_EFC195 AS_MeanAmphiMoment AS_DAYM780201 \\\n", + "FULL_Charge 0.088068 0.355477 -0.365374 \n", + "FULL_AcidicMolPerc -0.143168 -0.431590 0.449621 \n", + "FULL_AURR980107 -0.169540 -0.426097 0.456260 \n", + "FULL_DAYM780201 -0.090058 -0.408793 0.894191 \n", + "FULL_GEOR030101 -0.230417 -0.160269 -0.029085 \n", + "FULL_OOBM850104 -0.230561 -0.336297 0.275640 \n", + "NT_EFC195 1.000000 0.178683 -0.036844 \n", + "AS_MeanAmphiMoment 0.178683 1.000000 -0.322378 \n", + "AS_DAYM780201 -0.036844 -0.322378 1.000000 \n", + "AS_FUKS010112 0.145924 0.025580 0.045562 \n", + "CT_RACS820104 0.080898 0.171524 -0.256060 \n", + "CLASS 0.260702 0.693552 -0.437168 \n", + "\n", + " AS_FUKS010112 CT_RACS820104 CLASS \n", + "FULL_Charge -0.090570 0.232929 0.534602 \n", + "FULL_AcidicMolPerc 0.002334 -0.213543 -0.598816 \n", + "FULL_AURR980107 0.032958 -0.403599 -0.584111 \n", + "FULL_DAYM780201 0.055915 -0.326792 -0.554838 \n", + "FULL_GEOR030101 0.040480 -0.151935 -0.260470 \n", + "FULL_OOBM850104 -0.452769 0.155304 -0.453287 \n", + "NT_EFC195 0.145924 0.080898 0.260702 \n", + "AS_MeanAmphiMoment 0.025580 0.171524 0.693552 \n", + "AS_DAYM780201 0.045562 -0.256060 -0.437168 \n", + "AS_FUKS010112 1.000000 -0.445284 0.033432 \n", + "CT_RACS820104 -0.445284 1.000000 0.267652 \n", + "CLASS 0.033432 0.267652 1.000000 " + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Correlation between attributes \n", + "correlations = amp_train.corr(method=\"pearson\") # calculates pairwaise correlation for the attributes \n", + "\n", + "#print(correlations) #you don't always have to use print()\n", + "\n", + "correlations\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "FULL_AURR980107 and FULL_AcidicMolPerc have a correlation coefficent of 0.79, this might mean these two attributes may be some what correlated. Same goes for AS_DAYM780201 and FULL_DAYM780201 (correlation coefficient is 0.894191)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Plots to visualize the correlations\n", + "from matplotlib import rcParams\n", + "sns.heatmap(correlations, annot=True)\n", + "rcParams['figure.figsize'] = 11.7,8.27\n", + "\n", + "\n", + "## Note!!\n", + "# import matplotlib.pyplot as plt\n", + "# You can use the function: plt.figure(figsize=(x,x))\n", + "# import matplotlib.pyplot as plt --> to do your plotting it gives more choices.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Data skewness\n", + "\n", + "Most machine learning algorithms assume that data from the attributes is normally distributed, so identifying attributes with data that has a left or right skew, can be important as this can be easily corrected" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "FULL_Charge 0.601716\n", + "FULL_AcidicMolPerc 0.994487\n", + "FULL_AURR980107 0.490291\n", + "FULL_DAYM780201 -0.216841\n", + "FULL_GEOR030101 0.883022\n", + "FULL_OOBM850104 -0.207124\n", + "NT_EFC195 2.898124\n", + "AS_MeanAmphiMoment 0.383682\n", + "AS_DAYM780201 -0.070879\n", + "AS_FUKS010112 -0.112632\n", + "CT_RACS820104 0.999487\n", + "CLASS 0.000000\n", + "dtype: float64\n" + ] + } + ], + "source": [ + "sk = amp_train.skew() # calculates the skew for each attribute\n", + "print(sk)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Negative values like those of FULL_DAYM780201, FULL_OOBM850104,AS_DAYM780201, AS_FUKS010112, indicate that these attributes have values skewed more to the left\n", + "Values closer to zero are indicative of a less or no skew, while positive values would mean that that particular attribute is skewed more to the right" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " # Visualising data distributions with plots" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Plot one, histogram to show the distributions\n", + "import matplotlib as plot \n", + "from matplotlib import pyplot\n", + "amp_train.hist(layout=(4,3), figsize=(16,16))\n", + "plot.pyplot.subplots_adjust(wspace=0.4, hspace=0.5)\n", + "pyplot.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Plot two density plots can show the distributions better\n", + "amp_train.plot(kind=\"density\",subplots=True,layout=(4,3),sharex=False,sharey=False, figsize=(16,16))\n", + "#amp_train.plot(kind=\"density\",subplots=False,layout=(4,3),sharex=True,sharey=True)\n", + "pyplot.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Data transformations\n", + "Using square roots to transform the attributes with negative values into postives\n", + "\n", + "\n", + "# Note!\n", + "\n", + "Is there a way to render these side by side such that we will be able to see how the transformation affects the originals" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "```\n", + "neg1=amp_train.iloc[:,0]\n", + "print(neg1) #plot this so that we can see how it looks before\n", + "tneg1=neg1**2\n", + "tneg1.plot(kind=\"density\") #plot side by side to see what the transformation does.\n", + "amp_train.iloc[:,0]=tneg1\n", + "\n", + "```" + ] + }, + { + "cell_type": "raw", + "metadata": {}, + "source": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "neg2=amp_train.iloc[:,5]\n", + "print(neg2)\n", + "tneg2=neg2**2\n", + "tneg2.plot(kind=\"density\")\n", + "amp_train.iloc[:,5]=tneg2\n", + "\n", + "## test\n", + "neg3=test_data.iloc[:,0]\n", + "print(neg3)\n", + "tneg3=neg3**2\n", + "tneg3.plot(kind=\"density\")\n", + "test_data.iloc[:,0]=tneg3\n", + "\n", + "\n", + "\n", + "neg4=test_data.iloc[:,5]\n", + "print(neg4)\n", + "tneg4=neg4**2\n", + "tneg4.plot(kind=\"density\")\n", + "test_data.iloc[:,5]=tneg4" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "distributions for AS_MeanAmphiMoment,FULL_AcidicMolPerc and NT_EFC195 dont look so good" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Feature selection\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(3038, 8)\n" + ] + }, + { + "data": { + "text/html": [ + "
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FULL_ChargeFULL_AcidicMolPercFULL_DAYM780201FULL_OOBM850104AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CLASS
05.00.00074.842-3.6630.28273.4445.6611.0
14.05.40571.595-4.0110.60068.2226.5371.0
25.55.40573.595-2.5120.59369.4444.9341.0
35.04.16766.250-1.3620.61467.2224.3161.0
47.58.53764.720-2.0910.61672.9444.5401.0
\n", + "
" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_DAYM780201 FULL_OOBM850104 \\\n", + "0 5.0 0.000 74.842 -3.663 \n", + "1 4.0 5.405 71.595 -4.011 \n", + "2 5.5 5.405 73.595 -2.512 \n", + "3 5.0 4.167 66.250 -1.362 \n", + "4 7.5 8.537 64.720 -2.091 \n", + "\n", + " AS_MeanAmphiMoment AS_DAYM780201 AS_FUKS010112 CLASS \n", + "0 0.282 73.444 5.661 1.0 \n", + "1 0.600 68.222 6.537 1.0 \n", + "2 0.593 69.444 4.934 1.0 \n", + "3 0.614 67.222 4.316 1.0 \n", + "4 0.616 72.944 4.540 1.0 " + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + " #test one selecting out features with low variance\n", + "from sklearn.feature_selection import VarianceThreshold\n", + "sel = VarianceThreshold(threshold=(.8 * (1 - .8)))\n", + "k=sel.fit_transform(amp_train) #fit the algorithm\n", + "\n", + "names=amp_train.columns[sel.get_support(indices=True)] #mapping the names\n", + "print(k.shape) #dimensions of the new data\n", + "amp_train2=pd.DataFrame(k,columns=names)\n", + "\n", + "amp_train2.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "ename": "ValueError", + "evalue": "Input X must be non-negative.", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mtest\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mSelectKBest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscore_func\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mchi2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 12\u001b[0;31m \u001b[0mfit\u001b[0m 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\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mscore_func\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 350\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscore_func_ret\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mlist\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtuple\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 351\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mscores_\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpvalues_\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mscore_func_ret\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/sklearn/feature_selection/_univariate_selection.py\u001b[0m in \u001b[0;36mchi2\u001b[0;34m(X, y)\u001b[0m\n\u001b[1;32m 214\u001b[0m \u001b[0mX\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcheck_array\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maccept_sparse\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'csr'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 215\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0many\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0missparse\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 216\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Input X must be non-negative.\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 217\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 218\u001b[0m \u001b[0mY\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mLabelBinarizer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit_transform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mValueError\u001b[0m: Input X must be non-negative." + ] + } + ], + "source": [ + "#test two\n", + "from sklearn.feature_selection import SelectKBest\n", + "from sklearn.feature_selection import chi2\n", + "\n", + "test_array = amp_train2.values\n", + "\n", + "test_atr = test_array[:,0:7]\n", + "class_atr = test_array[:,7]\n", + "\n", + "\n", + "test = SelectKBest(score_func=chi2, k=5)\n", + "fit = test.fit(test_atr, class_atr)\n", + "\n", + "\n", + "print(fit.scores_)\n", + "features = fit.transform(test_atr)\n", + "names2=amp_train2.columns[fit.get_support(indices=True)]\n", + "amp_train3=pd.DataFrame(features,columns=names2)\n", + "print(amp_train3[5:])\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Index(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'AS_MeanAmphiMoment',\n", + " 'AS_FUKS010112'],\n", + " dtype='object')\n", + "Index(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_OOBM850104',\n", + " 'AS_MeanAmphiMoment'],\n", + " dtype='object')\n", + "Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201',\n", + " 'FULL_OOBM850104', 'AS_MeanAmphiMoment'],\n", + " dtype='object')\n", + "Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", + " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", + " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", + " 'CLASS'],\n", + " dtype='object')\n", + " FULL_Charge FULL_AcidicMolPerc FULL_DAYM780201 FULL_OOBM850104 \\\n", + "0 25.00 0.000 74.842 13.417569 \n", + "1 16.00 5.405 71.595 16.088121 \n", + "2 30.25 5.405 73.595 6.310144 \n", + "3 25.00 4.167 66.250 1.855044 \n", + "4 56.25 8.537 64.720 4.372281 \n", + "5 25.00 7.692 78.949 9.554281 \n", + "6 9.00 6.897 78.586 12.559936 \n", + "7 4.00 5.882 76.588 34.012224 \n", + "8 49.00 2.632 60.447 0.085264 \n", + "9 81.00 0.000 65.808 15.116544 \n", + "10 4.00 3.448 71.172 13.778944 \n", + "11 6.25 0.000 60.579 1.852321 \n", + "12 9.00 0.000 70.875 12.981609 \n", + "13 9.00 7.143 71.357 18.748900 \n", + "14 6.25 7.692 60.769 13.256881 \n", + "15 36.00 4.348 67.870 2.050624 \n", + "16 4.00 0.000 73.842 24.285184 \n", + "17 16.00 0.000 64.083 24.770529 \n", + "18 20.25 11.111 77.185 0.481636 \n", + "19 4.00 4.167 68.667 9.778129 \n", + "20 4.00 6.667 68.233 11.068929 \n", + "21 9.00 10.345 72.000 22.127616 \n", + "22 12.25 2.703 72.919 13.162384 \n", + "23 1.00 0.000 52.769 21.696964 \n", + "24 1.00 0.000 63.231 16.483600 \n", + "25 30.25 4.348 58.913 22.619536 \n", + "26 42.25 0.000 63.917 11.703241 \n", + "27 1.00 5.556 74.833 15.038884 \n", + "28 42.25 0.000 66.500 17.926756 \n", + "29 56.25 8.333 69.375 3.115225 \n", + "... ... ... ... ... \n", + "3008 36.00 20.000 83.686 2.033476 \n", + "3009 1.00 22.500 77.700 0.045796 \n", + "3010 1.00 12.500 79.708 1.575025 \n", + "3011 0.00 5.263 73.079 2.334784 \n", + "3012 9.00 19.608 83.412 1.058841 \n", + "3013 1.00 12.245 76.122 2.849344 \n", + "3014 1.00 16.667 80.250 0.122500 \n", + "3015 4.00 10.811 67.514 5.017600 \n", + "3016 1.00 8.333 71.000 2.214144 \n", + "3017 0.00 10.256 80.077 1.153476 \n", + "3018 0.00 18.750 88.250 1.726596 \n", + "3019 0.25 16.667 77.729 1.334025 \n", + "3020 0.25 11.429 77.657 0.819025 \n", + "3021 1.00 11.538 78.038 0.040000 \n", + "3022 9.00 0.000 66.769 0.029929 \n", + "3023 4.00 12.000 75.867 2.005056 \n", + "3024 12.25 20.000 73.050 7.823209 \n", + "3025 6.25 10.714 78.071 8.334769 \n", + "3026 0.25 0.000 81.545 0.381924 \n", + "3027 81.00 7.547 77.283 11.682724 \n", + "3028 4.00 18.750 79.938 1.196836 \n", + "3029 20.25 14.286 69.143 1.177225 \n", + "3030 4.00 12.963 72.815 11.874916 \n", + "3031 0.00 17.021 76.234 5.143824 \n", + "3032 0.00 16.667 82.917 4.297329 \n", + "3033 1.00 5.263 67.947 4.626801 \n", + "3034 42.25 21.667 75.433 2.805625 \n", + "3035 2.25 12.500 76.542 0.842724 \n", + "3036 4.00 5.000 73.750 7.409284 \n", + "3037 1.00 15.789 66.158 4.326400 \n", + "\n", + " AS_MeanAmphiMoment AS_DAYM780201 AS_FUKS010112 CLASS \n", + "0 0.282 73.444 5.661 1.0 \n", + "1 0.600 68.222 6.537 1.0 \n", + "2 0.593 69.444 4.934 1.0 \n", + "3 0.614 67.222 4.316 1.0 \n", + "4 0.616 72.944 4.540 1.0 \n", + "5 0.511 78.778 5.992 1.0 \n", + "6 0.385 78.222 6.284 1.0 \n", + "7 0.154 76.588 6.479 1.0 \n", + "8 0.188 64.333 3.849 1.0 \n", + "9 0.361 63.222 6.327 1.0 \n", + "10 0.510 76.389 5.402 1.0 \n", + "11 0.163 61.667 5.627 1.0 \n", + "12 0.263 71.611 6.804 1.0 \n", + "13 0.232 72.778 6.726 1.0 \n", + "14 0.402 60.769 7.112 1.0 \n", + "15 0.187 65.167 5.238 1.0 \n", + "16 0.536 75.667 6.996 1.0 \n", + "17 0.826 65.944 6.038 1.0 \n", + "18 1.100 78.444 6.141 1.0 \n", + "19 1.210 66.944 6.149 1.0 \n", + "20 1.304 73.500 6.604 1.0 \n", + "21 1.726 61.056 5.722 1.0 \n", + "22 1.717 70.833 6.669 1.0 \n", + "23 2.834 52.769 7.426 1.0 \n", + "24 2.980 63.231 6.942 1.0 \n", + "25 2.138 63.444 7.546 1.0 \n", + "26 2.435 62.056 6.801 1.0 \n", + "27 2.044 74.833 6.644 1.0 \n", + "28 2.704 69.444 5.673 1.0 \n", + "29 2.743 65.889 5.242 1.0 \n", + "... ... ... ... ... \n", + "3008 15.452 81.722 6.566 0.0 \n", + "3009 15.625 78.333 5.747 0.0 \n", + "3010 15.502 75.556 5.558 0.0 \n", + "3011 15.676 70.556 5.723 0.0 \n", + "3012 15.813 75.111 6.378 0.0 \n", + "3013 15.774 78.278 6.374 0.0 \n", + "3014 23.502 80.250 5.325 0.0 \n", + "3015 15.974 65.944 5.169 0.0 \n", + "3016 23.550 71.000 5.017 0.0 \n", + "3017 15.781 80.167 6.149 0.0 \n", + "3018 17.666 88.250 6.383 0.0 \n", + "3019 15.838 80.111 6.138 0.0 \n", + "3020 15.867 74.167 5.523 0.0 \n", + "3021 16.209 79.944 5.267 0.0 \n", + "3022 22.477 66.769 6.068 0.0 \n", + "3023 16.444 74.111 5.611 0.0 \n", + "3024 16.495 74.944 6.606 0.0 \n", + "3025 16.513 82.056 5.732 0.0 \n", + "3026 26.931 81.545 5.120 0.0 \n", + "3027 16.517 78.111 5.451 0.0 \n", + "3028 18.119 79.938 6.241 0.0 \n", + "3029 20.625 69.143 5.769 0.0 \n", + "3030 16.256 65.722 6.378 0.0 \n", + "3031 16.365 77.278 5.821 0.0 \n", + "3032 24.497 82.917 5.640 0.0 \n", + "3033 16.706 68.611 5.598 0.0 \n", + "3034 16.897 73.278 6.194 0.0 \n", + "3035 16.918 82.111 5.889 0.0 \n", + "3036 17.131 74.722 6.055 0.0 \n", + "3037 17.151 67.111 5.853 0.0 \n", + "\n", + "[3038 rows x 8 columns]\n" + ] + } + ], + "source": [ + "# Test three Recursive feature elimination\n", + "\n", + "from sklearn.feature_selection import RFE\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.ensemble import RandomForestClassifier\n", + "\n", + "model1 = LogisticRegression()\n", + "model2=RandomForestClassifier()\n", + "\n", + "rfe = RFE(model1, 4)\n", + "fit2 = rfe.fit(test_atr, class_atr)\n", + "\n", + "rfe2= RFE(model2, 4)\n", + "fit3 = rfe2.fit(test_atr, class_atr)\n", + "\n", + "\n", + "\n", + "\n", + "names3=amp_train2.columns[fit2.get_support(indices=True)]\n", + "\n", + "names4=amp_train2.columns[fit3.get_support(indices=True)]\n", + "\n", + "#print(names3)\n", + "#print(names4)\n", + "#print(names2)\n", + "#print(amp_train.columns)\n", + "#print(amp_train2)\n", + "\n", + "#transformer functions\n", + "# When we use a fit function we normally folow with a transformation function.\n", + "# That way we can change our data the same way for the test and train dataset.\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Note\n", + "\n", + "Why not use the transform method to change " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "test_amp =amp_train.loc[:,['FULL_Charge', 'FULL_AcidicMolPerc',\"FULL_OOBM850104\",'FULL_DAYM780201', 'AS_MeanAmphiMoment','CLASS']]\n", + "print(test_amp)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.metrics import confusion_matrix\n", + "\n", + "\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", + "from sklearn.naive_bayes import GaussianNB\n", + "from sklearn.svm import SVC\n", + "from sklearn.neighbors import KNeighborsClassifier\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Logistic regression using cross validation" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "X=test_amp.iloc[:,0:5]\n", + "Y=test_amp.iloc[:,5]\n", + "folds=10\n", + "kfold = KFold(n_splits=folds, random_state=7, shuffle=True,)\n", + "model = LogisticRegression()\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "\n", + "print((\"Accuracy: %.3f%% (%.3f%%)\") % (results.mean()*100.0, results.std()*100.0))\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "test_data = pd.read_csv(\"/kaggle/input/ace-class-assignment/Test.csv\", header=0, sep=\",\")\n", + "amp_train = pd.read_csv(\"/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\", header=0, sep=\",\")\n", + "test_amp =amp_train.loc[:,['FULL_Charge', 'FULL_AcidicMolPerc',\"FULL_OOBM850104\",'FULL_DAYM780201', 'AS_MeanAmphiMoment','CLASS']]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Logistic regression with a test train split" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.metrics import matthews_corrcoef\n", + "test_amp=test_amp.values\n", + "#X=test_amp.iloc[:,0:5]\n", + "X=test_amp[:,0:5]\n", + "Y=test_amp[:,5]\n", + "\n", + "#Y=test_amp.iloc[:,5]\n", + "#print(Y)\n", + "test_size = 0.4\n", + "seed = 25\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\n", + "model = LogisticRegression()\n", + "model.fit(X_train, Y_train)\n", + "predicted = model.predict(X_test)\n", + "matrix = confusion_matrix(Y_test, predicted)\n", + "result = model.score(X_test, Y_test)\n", + "print(\"Accuracy: \", (result*100.0))\n", + "print(matrix)\n", + "print('MCC: ', matthews_corrcoef(model.predict(X_test),Y_test))\n", + "#print(test_data)\n", + "\n", + "test_data2=test_data.loc[:,['FULL_Charge', 'FULL_AcidicMolPerc','FULL_DAYM780201', 'FULL_OOBM850104', 'AS_MeanAmphiMoment']]\n", + "test_data2=test_data2.values \n", + "#model1 = LogisticRegression() \n", + "#model1.fit(X,Y)\n", + "kj_results=model.predict(test_data2)\n", + "\n", + "#print(test_data2)\n", + "kj_results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.DataFrame(kj_results)\n", + "df.columns = ['CLASS']\n", + "df.index.name = 'Index'\n", + "df['CLASS']=df['CLASS'].map({0.0:False,1.0:True})\n", + "print(df)\n", + "#X=test_amp.iloc[:,0:5]\n", + "#=test_amp.iloc[:,5]\n", + "df.to_csv(\"kj.csv\")\n", + "df[\"CLASS\"].unique()\n", + "#print(df.groupby(\"CLASS\").size()[0].sum())\n", + "#print(df.groupby(\"CLASS\").size()[1].sum())\n", + "df['CLASS'].value_counts()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Gausian/Naive Bayes" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "model=GaussianNB()\n", + "from sklearn.metrics import matthews_corrcoef\n", + "test_size = 0.4\n", + "seed = 25\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", + "random_state=seed)\n", + "model.fit(X_train, Y_train)\n", + "predicted = model.predict(X_test)\n", + "matrix = confusion_matrix(Y_test, predicted)\n", + "result = model.score(X_test, Y_test)\n", + "print(\"Accuracy: \", (result*100.0))\n", + "print(matrix)\n", + "print('MCC: ', matthews_corrcoef(model.predict(X_test),Y_test))\n", + "#print(test_data)\n", + "\n", + "X=test_amp.iloc[:,0:5]\n", + "Y=test_amp.iloc[:,5]\n", + "model=GaussianNB() \n", + "model.fit(X,Y)\n", + "kj_results=model.predict(test_data2)\n", + "\n", + "#print(test_data2)\n", + "kj_results" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Linear Discriminant Analysis" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "model=LinearDiscriminantAnalysis()\n", + "folds=10\n", + "kfold = KFold(n_splits=folds, random_state=7, shuffle=True,)\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print((\"Accuracy: %.3f%% (%.3f%%)\") % (results.mean()*100.0, results.std()*100.0))\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Support Vector Machines" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "model=SVC()\n", + "folds=10\n", + "kfold = KFold(n_splits=folds, random_state=7, shuffle=True,)\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print((\"Accuracy: %.3f%% (%.3f%%)\") % (results.mean()*100.0, results.std()*100.0))" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.4" + }, + "varInspector": { + "cols": { + "lenName": 16, + "lenType": 16, + "lenVar": 40 + }, + "kernels_config": { + "python": { + "delete_cmd_postfix": "", + "delete_cmd_prefix": "del ", + "library": "var_list.py", + "varRefreshCmd": "print(var_dic_list())" + }, + "r": { + "delete_cmd_postfix": ") ", + "delete_cmd_prefix": "rm(", + "library": "var_list.r", + "varRefreshCmd": "cat(var_dic_list()) " + } + }, + "types_to_exclude": [ + "module", + "function", + "builtin_function_or_method", + "instance", + "_Feature" + ], + "window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} From 706918b22ea8270aeaca25994adad08e9acac8c4 Mon Sep 17 00:00:00 2001 From: LevisK Date: Thu, 5 Mar 2020 19:26:13 +0300 Subject: [PATCH 04/29] Agasi's Work --- Assignment Colab/agasi-herbert.ipynb | 2204 ++++++++++++++++++++++++++ 1 file changed, 2204 insertions(+) create mode 100644 Assignment Colab/agasi-herbert.ipynb diff --git a/Assignment Colab/agasi-herbert.ipynb b/Assignment Colab/agasi-herbert.ipynb new file mode 100644 index 0000000..7c3752e --- /dev/null +++ b/Assignment Colab/agasi-herbert.ipynb @@ -0,0 +1,2204 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", + "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Using TensorFlow backend.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/kaggle/input/ace-class-assignment/Test.csv\n", + "/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\n" + ] + } + ], + "source": [ + "# This Python 3 environment comes with many helpful analytics libraries installed\n", + "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", + "# For example, here's several helpful packages to load in \n", + "\n", + "import numpy as np # linear algebra\n", + "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", + "import matplotlib.pyplot as plt #Data visualization\n", + "import seaborn as sns #Data Visualization\n", + "import math\n", + "\n", + "\n", + "###Feature Selection\n", + "from sklearn.feature_selection import SelectKBest\n", + "from sklearn.feature_selection import chi2\n", + "from sklearn.feature_selection import f_classif\n", + "from sklearn.feature_selection import mutual_info_classif\n", + "from sklearn.feature_selection import SelectFromModel\n", + "from sklearn.feature_selection import RFE\n", + "from sklearn.feature_selection import SelectFromModel\n", + "from sklearn.ensemble import RandomForestClassifier\n", + "from sklearn.ensemble import VotingClassifier\n", + "\n", + "###Modeling\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.model_selection import train_test_split\n", + "\n", + "from sklearn.metrics import accuracy_score, confusion_matrix, recall_score\n", + "from imblearn.over_sampling import SMOTE\n", + "from imblearn.under_sampling import NearMiss\n", + "\n", + "from sklearn.naive_bayes import GaussianNB\n", + "from sklearn.neural_network import MLPClassifier\n", + "from sklearn.linear_model import SGDClassifier\n", + "from sklearn import svm\n", + "from sklearn import tree\n", + "\n", + "from sklearn.model_selection import cross_val_score\n", + "\n", + "from numpy import savetxt\n", + "# Input data files are available in the \"../input/\" directory.\n", + "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", + "\n", + "import os\n", + "for dirname, _, filenames in os.walk('/kaggle/input'):\n", + " for filename in filenames:\n", + " print(os.path.join(dirname, filename))\n", + "\n", + "# Any results you write to the current directory are saved as output." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Importing Datasets" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0", + "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a" + }, + "outputs": [], + "source": [ + "#This segment imports the two datasets the test and train\n", + "Test = pd.read_csv(\"../input/ace-class-assignment/Test.csv\")\n", + "Train = pd.read_csv(\"../input/ace-class-assignment/AMP_TrainSet.csv\")\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Taking a preview of the data." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "#This is a for data with absolute values\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Train shape (3038, 12) \n", + " Test shape (758, 11) \n" + ] + } + ], + "source": [ + "print(\"Train shape {} \\n Test shape {} \".format(Train.shape,Test.shape))" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", + " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", + " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", + " 'CLASS'],\n", + " dtype='object')" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Train.columns" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "#Train['FULL_Charge'] = Train['FULL_Charge'] **2\n", + "#Train['CT_RACS820104'] = Train['CT_RACS820104'] **2" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "FULL_Charge float64\n", + "FULL_AcidicMolPerc float64\n", + "FULL_AURR980107 float64\n", + "FULL_DAYM780201 float64\n", + "FULL_GEOR030101 float64\n", + "FULL_OOBM850104 float64\n", + "NT_EFC195 int64\n", + "AS_MeanAmphiMoment float64\n", + "AS_DAYM780201 float64\n", + "AS_FUKS010112 float64\n", + "CT_RACS820104 float64\n", + "CLASS int64\n", + "dtype: object" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Train.dtypes" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + 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" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n", + "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", + "mean 2.060237 8.521520 0.971410 73.668760 \n", + "std 3.819929 7.586652 0.107413 8.527489 \n", + "min -16.000000 0.000000 0.684000 42.750000 \n", + "25% 0.000000 2.516000 0.895000 68.294000 \n", + "50% 2.000000 7.143000 0.963000 74.059500 \n", + "75% 4.000000 13.158000 1.041000 79.343750 \n", + "max 30.000000 46.667000 1.451000 101.682000 \n", + "\n", + " FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n", + "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", + "mean 0.994007 -2.432927 0.088545 15.683233 \n", + "std 0.031333 1.707223 0.284133 11.575665 \n", + "min 0.866000 -10.432000 0.000000 0.041000 \n", + "25% 0.974000 -3.606000 0.000000 5.587500 \n", + "50% 0.994000 -2.296500 0.000000 14.988500 \n", + "75% 1.011000 -1.283250 0.000000 26.807750 \n", + "max 1.196000 3.576000 1.000000 51.280000 \n", + "\n", + " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 CLASS \n", + "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", + "mean 73.650828 5.911361 1.235255 0.500000 \n", + "std 9.166092 0.693689 0.210012 0.500082 \n", + "min 42.778000 3.533000 0.785000 0.000000 \n", + "25% 67.556000 5.459250 1.082000 0.000000 \n", + "50% 73.697000 5.925500 1.184000 0.500000 \n", + "75% 79.778000 6.382000 1.351000 1.000000 \n", + "max 103.167000 8.662000 2.192000 1.000000 " + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Train.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.boxplot(Train[['FULL_OOBM850104']])" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "##Outlier detection\n", + "#O_FULL_Charge = [x for x in Train['FULL_Charge'] if x > 10]\n", + "#print(len(O_FULL_Charge))\n", + "#print(len(Train['FULL_Charge']))\n", + "\n", + "##Outlier detection for FULL_AcidicMolPerc\n", + "\n", + "#O_FULL_AcidicMolPerc = [x for x in Train['FULL_AcidicMolPerc'] if x > 20]\n", + "#print(len(O_FULL_AcidicMolPerc))\n", + "#O_FULL_AcidicMolPerc\n", + "\n", + "\n", + "## Testing to remove the outliers\n", + "\n", + "#Train[['FULL_Charge']] =[Train['FULL_Charge'].mean(axis = 0) for x in range(Train['FULL_Charge']) if x > 10]\n", + "#def out(xx):\n", + " # mm =Train['FULL_Charge'].mean() \n", + " # for x in range(len(Train['FULL_Charge'])):\n", + " # if x > 20:\n", + " # Train['FULL_Charge'].iloc[x] = mm \n", + " \n", + " \n", + "#out(Train)\n", + "#Train['FULL_Charge'].mean() \n", + "#Train[['FULL_Charge' ]> 20] =Train['FULL_Charge'].mean()\n", + "\n", + "##AS_MeanAmphiMoment\n", + "#This feature has no outliers\n", + "\n", + "###\n", + "#'FULL_AURR980107'\n", + "##This attribute has outliers greater than 13 \n", + "#Train['FULL_AURR980107']\n", + "#FAURR = np.array(Train['FULL_AURR980107'])\n", + "#FAURR[FAURR >= 13]= FAURR.mean()\n", + "#Train['FULL_AURR980107'] = pd.DataFrame(FAURR)\n", + "\n", + "\n", + "##Removing the outliers and replacing them with the mean\n", + "##Values greater than 10 and values less than -6\n", + "#FCharge = np.array(Train['FULL_Charge'])\n", + "#FCharge[ FCharge >= 10 ]= FCharge.mean()\n", + "#FCharge[ FCharge <= -6 ]= FCharge.mean()\n", + "#Train['FULL_Charge'] = pd.DataFrame(FCharge)\n", + "\n", + "##Removing outliers for values\n", + "#Train['FULL_DAYM780201']\n", + "#FDAY = np.array(Train['FULL_DAYM780201'])\n", + "#FDAY[FDAY >= 95]= FDAY.mean()\n", + "#FDAY[FDAY <= 52]= FDAY.mean()\n", + "#Train['FULL_DAYM780201'] = pd.DataFrame(FDAY)\n", + "### \n", + "#Removing outliers greater\n", + "#Train[['FULL_AcidicMolPerc']] \n", + "#FAcidic = np.array(Train['FULL_AcidicMolPerc'])\n", + "#FAcidic[ FAcidic >= 27 ]= FCharge.mean()\n", + "#Train['FULL_AcidicMolPerc'] = pd.DataFrame(FAcidic)\n", + "\n", + "\n", + "##Train[['FULL_OOBM850104']]\n", + "#FOOB = np.array(Train['FULL_OOBM850104'])\n", + "#FOOB[FOOB >= 2 ]= FOOB.mean()\n", + "#FOOB[FOOB <= -7 ]= FOOB.mean()\n", + "#Train['FULL_OOBM850104'] = pd.DataFrame(FOOB)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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c0n9LOqXSb9E0ZZz8RR8AOMJf9AGAI0QZABwhygDgCFEGAEeIMgA4QpQBwBGiDACOEGUAcOT/AQdi0NNOKculAAAAAElFTkSuQmCC\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "##The density plot is used to determint the distribution of the data.\n", + "##Sometimes the two peaks illustrate a binary categorical feature i.e.\n", + "##Most of the data appers to be normally distributed.\n", + "Train.plot(kind='density', subplots=True, layout=(4,4), sharex=False)\n", + "plt.show" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Looking at the categorical variable closesly to understand the short and long peak.\n", + "A count of the categorical values and a bar plot will give more description." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0 2769\n", + "1 269\n", + "Name: NT_EFC195, dtype: int64" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Train.NT_EFC195.value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Train.NT_EFC195.value_counts().plot(kind=\"bar\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Looking at the above graph. It shows that data is very unbalanced. In this case if we are to use this feature in our machine Learning alogorithm we would require to use either SMOTE or Near Miss to balance the dataset." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "##\n", + "#This is to determine the skewness of the data.\n", + "## For each feature the skewness can be determined.\n", + "\n", + "Train.skew().plot(kind='bar')" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import seaborn as sns\n", + "sns.pairplot(Train)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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QJDHhU0BV9WySdwF3AycAO6vq4UnOoXOeWtPzma/PCUtVrdwlSXrR8ZPAktQpA0CSOmUASFKnJv05AEkiyesYfAvAOgafBdoP7K6qR6Y6sc54BCBpopJcy+BrYAJ8kcHbwwPc6hdETpbvAupQkquq6uPTnof6lORbwOur6sdL6icCD1fVpunMrD8eAfTpz6c9AXXtp8Crl6mf2cY0IV4DeJFK8uCRhoAzJjkXaYn3APck2cuhL4c8C3gN8K6pzapDngJ6kUryBHAh8NTSIeDfqmq5/8CkiUjyEgZfD7+OwWtyAbi/qn4y1Yl1xiOAF6/PAK+oqq8sHUjy+clPRzqkqn4K3DvtefTOIwBJ6pQXgSWpUwaAJHXKAJCkThkAktSp/wPs1chqmw6rowAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Train.CLASS.value_counts().plot(kind='bar')" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "FULL_Charge 0.088068\n", + "FULL_AcidicMolPerc -0.143168\n", + "FULL_AURR980107 -0.169540\n", + "FULL_DAYM780201 -0.090058\n", + "FULL_GEOR030101 -0.230417\n", + "FULL_OOBM850104 -0.230561\n", + "NT_EFC195 1.000000\n", + "AS_MeanAmphiMoment 0.178683\n", + "AS_DAYM780201 -0.036844\n", + "AS_FUKS010112 0.145924\n", + "CT_RACS820104 0.080898\n", + "CLASS 0.260702\n", + "Name: NT_EFC195, dtype: float64" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Train.corr(method='pearson')['NT_EFC195']" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Missing data variables" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "FULL_Charge 0\n", + "FULL_AcidicMolPerc 0\n", + "FULL_AURR980107 0\n", + "FULL_DAYM780201 0\n", + "FULL_GEOR030101 0\n", + "FULL_OOBM850104 0\n", + "NT_EFC195 0\n", + "AS_MeanAmphiMoment 0\n", + "AS_DAYM780201 0\n", + "AS_FUKS010112 0\n", + "CT_RACS820104 0\n", + "CLASS 0\n", + "dtype: int64\n", + "FULL_Charge 0\n", + "FULL_AcidicMolPerc 0\n", + "FULL_AURR980107 0\n", + "FULL_DAYM780201 0\n", + "FULL_GEOR030101 0\n", + "FULL_OOBM850104 0\n", + "NT_EFC195 0\n", + "AS_MeanAmphiMoment 0\n", + "AS_DAYM780201 0\n", + "AS_FUKS010112 0\n", + "CT_RACS820104 0\n", + "CLASS 0\n", + "dtype: int64\n" + ] + } + ], + "source": [ + "print(Train.isna().sum())\n", + "print(Train.isnull().sum())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Feature Selection\n", + "### Chi Square test" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The chi square test didn't yield any results as a result of and error caused by having negative values. The code is in the section below." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "```\n", + "sel_chi2 = SelectKBest(chi2, k=4) # select 4 features\n", + "X_train_chi2 = sel_chi2.fit_transform(X_train, y_train)\n", + "print(sel_chi2.get_support())\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "#array = Train.values\n", + "X = Train.drop(\"CLASS\", axis = 1)\n", + "y = Train.CLASS\n", + "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42, stratify=y)\n", + "#array.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# F test" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[False True True True False False False True False False False]\n" + ] + } + ], + "source": [ + "sel_f = SelectKBest(f_classif, k=4)\n", + "X_train_f = sel_f.fit_transform(X_train, y_train)\n", + "print(sel_f.get_support())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Mutual_info_classif test" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ True True True False False False False True False False False]\n" + ] + } + ], + "source": [ + "sel_mutual = SelectKBest(mutual_info_classif, k=4)\n", + "X_train_mutual = sel_mutual.fit_transform(X_train, y_train)\n", + "print(sel_mutual.get_support())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Recursive Feature Elimination" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[False False True False False True True False False False True]\n", + "Index(['FULL_AURR980107', 'FULL_OOBM850104', 'NT_EFC195', 'CT_RACS820104'], dtype='object')\n" + ] + } + ], + "source": [ + "model_logistic = LogisticRegression(solver='lbfgs', multi_class='multinomial', max_iter=1000)\n", + "sel_rfe_logistic = RFE(estimator=model_logistic, n_features_to_select=4, step=1)\n", + "X_train_rfe_logistic = sel_rfe_logistic.fit_transform(X_train, y_train)\n", + "print(sel_rfe_logistic.get_support())\n", + "#####\n", + "print(Train.columns[sel_rfe_logistic.get_support(indices=True)])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Random forest as the model" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[False True True True False False False True False False False]\n" + ] + } + ], + "source": [ + "model_tree = RandomForestClassifier(random_state=100, n_estimators=50)\n", + "sel_rfe_tree = RFE(estimator=model_tree, n_features_to_select=4, step=1)\n", + "X_train_rfe_tree = sel_rfe_tree.fit_transform(X_train, y_train)\n", + "print(sel_rfe_tree.get_support())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " # Feature selection using SelectFromModel" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# L1-based feature selection" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ True True False True False True True True True True True]\n" + ] + } + ], + "source": [ + "model_logistic = LogisticRegression(solver='saga', multi_class='multinomial', max_iter=10000, penalty='l1')\n", + "sel_model_logistic = SelectFromModel(estimator=model_logistic)\n", + "X_train_sfm_l1 = sel_model_logistic.fit_transform(X_train, y_train)\n", + "print(sel_model_logistic.get_support())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Tree-based feature selection" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0.11807409 0.16028202 0.07342594 0.10156481 0.0515547 0.08030908\n", + " 0.00589794 0.3148824 0.03561078 0.02422801 0.03417023]\n", + "[ True True False True False False False True False False False]\n" + ] + } + ], + "source": [ + "model_tree = RandomForestClassifier(random_state=100, n_estimators=50)\n", + "model_tree.fit(X_train, y_train)\n", + "print(model_tree.feature_importances_)\n", + "sel_model_tree = SelectFromModel(estimator=model_tree, prefit=True, threshold='mean') \n", + " # since we already fit the data, we specify prefit option here\n", + " # Features whose importance is greater or equal to the threshold are kept while the others are discarded.\n", + "X_train_sfm_tree = sel_model_tree.transform(X_train)\n", + "print(sel_model_tree.get_support())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For the different feature selection model the " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Conclusion on Best Features" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " sel_model_tree sel_rfe_tree sel_rfe_logistic sel_mutual sel_f\n", + "0 1 0 0 1 0\n", + "1 1 1 0 1 1\n", + "2 0 1 1 1 1\n", + "3 1 1 0 0 1\n", + "4 0 0 0 0 0\n", + "5 0 0 1 0 0\n", + "6 0 0 1 0 0\n", + "7 1 1 0 1 1\n", + "8 0 0 0 0 0\n", + "9 0 0 0 0 0\n", + "10 0 0 1 0 0\n", + " 0 1 2 3 4 5 6 7 8 9 10\n", + "sel_model_tree 1 1 0 1 0 0 0 1 0 0 0\n", + "sel_rfe_tree 0 1 1 1 0 0 0 1 0 0 0\n", + "sel_rfe_logistic 0 0 1 0 0 1 1 0 0 0 1\n", + "sel_mutual 1 1 1 0 0 0 0 1 0 0 0\n", + "sel_f 0 1 1 1 0 0 0 1 0 0 0\n" + ] + }, + { + "data": { + "text/plain": [ + "[2, 4, 4, 3, 0, 1, 1, 4, 0, 0, 1]" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "F1 = pd.DataFrame(sel_model_tree.get_support(), columns=['sel_model_tree'])\n", + "F2 = pd.DataFrame(sel_rfe_tree.get_support(),columns=['sel_rfe_tree'])\n", + "F3 = pd.DataFrame(sel_rfe_logistic.get_support(),columns=['sel_rfe_logistic'])\n", + "F4 = pd.DataFrame(sel_mutual.get_support(),columns=['sel_mutual'])\n", + "F5 = pd.DataFrame(sel_f.get_support(),columns=['sel_f'])\n", + "df = pd.concat([F1,F2,F3,F4,F5], axis=1)\n", + "\n", + "df = df.replace({True:1,False:0})\n", + "print(df)\n", + "dff =df.T\n", + "print(dff)\n", + "#dff[1].sum()\n", + "dfff =[]\n", + "for x in dff:\n", + " dfff.append(dff[x].sum())\n", + " \n", + "dfff\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201AS_MeanAmphiMoment
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..................
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3038 rows × 5 columns

\n", + "
" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n", + "0 5.0 0.000 0.951 74.842 \n", + "1 4.0 5.405 0.931 71.595 \n", + "2 5.5 5.405 0.873 73.595 \n", + "3 5.0 4.167 0.895 66.250 \n", + "4 7.5 8.537 0.932 64.720 \n", + "... ... ... ... ... \n", + "3033 1.0 5.263 0.945 67.947 \n", + "3034 -6.5 21.667 1.133 75.433 \n", + "3035 -1.5 12.500 1.091 76.542 \n", + "3036 2.0 5.000 0.849 73.750 \n", + "3037 -1.0 15.789 1.066 66.158 \n", + "\n", + " AS_MeanAmphiMoment \n", + "0 0.282 \n", + "1 0.600 \n", + "2 0.593 \n", + "3 0.614 \n", + "4 0.616 \n", + "... ... \n", + "3033 16.706 \n", + "3034 16.897 \n", + "3035 16.918 \n", + "3036 17.131 \n", + "3037 17.151 \n", + "\n", + "[3038 rows x 5 columns]" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "##Adding the fifth feature to check the performance of the model.\n", + "#Train[['FULL_Charge','FULL_AcidicMolPerc','FULL_AURR980107','FULL_DAYM780201','AS_MeanAmphiMoment']]\n", + "##Checking the different features forthe different algorithms\n", + "\n", + "#['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", + " # 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", + " # 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", + " # 'CLASS'\n", + " \n", + "##Absolute value of features.\n", + "##[0, 4, 4, 4, 1, 1, 1, 4, 0, 0, 1]\n", + " \n", + "Train[['FULL_Charge','FULL_AcidicMolPerc','FULL_AURR980107','FULL_DAYM780201','AS_MeanAmphiMoment']]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Machine Learning\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Test " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Different algorithms are ran agasi the different features and the accuracy values of the different models is recorded. Ind addition a confusion matrix is uesd to add weight to accuray of the model. i.e. \n", + "True Positve and a False Negative.\n", + "* Logistic Regression \n", + "* Smote\n", + "* Near Miss \n", + "* Gaussian " + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.9171052631578948" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#X = Train[['FULL_AcidicMolPerc','FULL_AURR980107','FULL_DAYM780201','AS_MeanAmphiMoment']]\n", + "#X = Train[['FULL_Charge','FULL_AcidicMolPerc','FULL_AURR980107','FULL_DAYM780201','AS_MeanAmphiMoment']]\n", + "\n", + "## 'FULL_AURR980107'\n", + "\n", + "#X=Train[['FULL_AcidicMolPerc','FULL_AURR980107','FULL_DAYM780201','FULL_OOBM850104','AS_MeanAmphiMoment']]\n", + "\n", + "#'FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", + "# 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", + "# 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", + "# 'CLASS'\n", + "#\n", + "##Original data\n", + "\n", + "#First Test\n", + "### Train[['FULL_Charge','FULL_AcidicMolPerc','FULL_AURR980107','FULL_DAYM780201','FULL_OOBM850104','AS_MeanAmphiMoment']]\n", + "# Logistic 0.9013157894736842\n", + "# Smote 0.9263157894736842\n", + "# Near Miss 0.9263157894736842\n", + "# Gaussian 0.9394736842105263\n", + "\n", + "#Second Test\n", + "## Eliminating 'FULL_OOBM850104'\n", + "##X=Train[['FULL_Charge','FULL_AcidicMolPerc','FULL_AURR980107','FULL_DAYM780201','AS_MeanAmphiMoment']]\n", + "# Logistic Regression 0.8947368421052632\n", + "# Smote 0.9078947368421053\n", + "# Near Miss 0.9078947368421053\n", + "# Gaussian 0.9289473684210526\n", + "\n", + "\n", + "#There was a drop hence 'FULL_OOBM850104' is a good feature\n", + "\n", + "#Third Test\n", + "#,'FULL_AURR980107' eliminated \n", + "### Train[['FULL_Charge','FULL_AcidicMolPerc','FULL_DAYM780201','FULL_OOBM850104','AS_MeanAmphiMoment']]\n", + "#Logistic0.8986842105263158\n", + "# Smote 0.9210526315789473\n", + "#Near Miss 0.9210526315789473\n", + "#Gausian 0.9394736842105263\n", + "\n", + "# There was no big difference hence we can eliminate it.\n", + "\n", + "#Fourth Test\n", + "## Train[['FULL_AcidicMolPerc','FULL_DAYM780201','FULL_OOBM850104','AS_MeanAmphiMoment']]\n", + "#Logistic 0.8973684210526316\n", + "#Gausian 0.8973684210526316\n", + "\n", + "#The Sixth Feature\n", + "#Eliminating ,'FULL_AcidicMolPerc'\n", + "#Train[['FULL_Charge','FULL_DAYM780201','FULL_OOBM850104','AS_MeanAmphiMoment']]\n", + "#Logistic Regresssion 0.8828947368421053\n", + "#Smote 0.8921052631578947\n", + "#Near Miss 0.8921052631578947\n", + "#Gaussian 0.9105263157894737\n", + "#7th Feature\n", + "# Eliminating 'AS_MeanAmphiMoment'\n", + "#Train[['FULL_Charge','FULL_DAYM780201','FULL_AcidicMolPerc','FULL_OOBM850104',]]\n", + "#Logistic Regression 0.8473684210526315\n", + "#Smote 0.881578947368421\n", + "#Near Miss 0.881578947368421\n", + "#Gaussian 0.9\n", + "\n", + "#8th Test\n", + "#inluding Feature NT_EFC195\n", + "\n", + "#Trail\n", + "#Train[['FULL_Charge']] = Train[['FULL_Charge']] ** 2\n", + "#Train[['FULL_DAYM780201']] = Train[['FULL_DAYM780201']] ** 2\n", + "#Train[['FULL_OOBM850104']] = Train[['FULL_OOBM850104']] ** 2\n", + "X =Train[['FULL_Charge','FULL_AcidicMolPerc','FULL_DAYM780201','FULL_OOBM850104','AS_MeanAmphiMoment']]\n", + "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state = 25, stratify=y)\n", + "y_train.value_counts()\n", + "lr = LogisticRegression()\n", + "lr.fit(X_train, y_train)\n", + "\n", + "y_pred = lr.predict(X_test)\n", + "\n", + "confusion_matrix(y_test, y_pred)\n", + "\n", + "accuracy_score(y_test, y_pred)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Second Test" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "I try to tranform my data to cater for the negative values in my column and well as keeping track of the confusion matrix as well as the accuracy." + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [], + "source": [ + "##Train[['FULL_Charge']] = Train[['FULL_Charge']] ** 2\n", + "#X =Train[['FULL_Charge','FULL_AcidicMolPerc','FULL_DAYM780201','FULL_OOBM850104','AS_MeanAmphiMoment']]\n", + "#X_train, X_test, y_train, y_test = train_test_split(X, y, random_state = 1, stratify=y)\n", + "#y_train.value_counts()\n", + "#lr = LogisticRegression()\n", + "#lr.fit(X_train, y_train)\n", + "\n", + "#y_pred = lr.predict(X_test)\n", + "\n", + "#confusion_matrix(y_test, y_pred)\n", + "\n", + "#accuracy_score(y_test, y_pred)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# SMOTE" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.9210526315789473" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "smt = SMOTE()\n", + "X_train, y_train = smt.fit_sample(X_train, y_train)\n", + "np.bincount(y_train)\n", + "\n", + "lr = LogisticRegression()\n", + "lr.fit(X_train, y_train)\n", + "\n", + "y_pred = lr.predict(X_test)\n", + "\n", + "confusion_matrix(y_test, y_pred)\n", + "\n", + "accuracy_score(y_test, y_pred)\n", + "\n", + "recall_score(y_test, y_pred)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Nearmiss" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[347 33]\n", + " [ 30 350]]\n", + "0.9210526315789473\n" + ] + } + ], + "source": [ + "nr = NearMiss()\n", + "X_train, y_train = nr.fit_sample(X_train, y_train)\n", + "np.bincount(y_train)\n", + "\n", + "lr = LogisticRegression()\n", + "lr.fit(X_train, y_train)\n", + "\n", + "y_pred = lr.predict(X_test)\n", + "\n", + "print(confusion_matrix(y_test, y_pred))\n", + "\n", + "accuracy_score(y_test, y_pred)\n", + "\n", + "print(recall_score(y_test, y_pred))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Gaussian" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[344 36]\n", + " [ 20 360]]\n", + "0.9263157894736842\n", + "0.9473684210526315\n", + "[[344 36]\n", + " [ 20 360]]\n", + "0.9473684210526315\n" + ] + } + ], + "source": [ + "gnb = GaussianNB()\n", + "y_pred = gnb.fit(X_train, y_train).predict(X_test)\n", + "print(confusion_matrix(y_test,y_pred))\n", + "print(accuracy_score(y_test,y_pred))\n", + "\n", + "smt = SMOTE()\n", + "X_train, y_train = smt.fit_sample(X_train, y_train)\n", + "np.bincount(y_train)\n", + "\n", + "gnb = GaussianNB()\n", + "gnb.fit(X_train, y_train)\n", + "\n", + "y_pred = gnb.predict(X_test)\n", + "confusion_matrix(y_test, y_pred)\n", + "accuracy_score(y_test, y_pred)\n", + "print(recall_score(y_test, y_pred))\n", + "\n", + "\n", + "nr = NearMiss()\n", + "X_train, y_train = nr.fit_sample(X_train, y_train)\n", + "np.bincount(y_train)\n", + "\n", + "gnb = GaussianNB()\n", + "gnb.fit(X_train, y_train)\n", + "\n", + "y_pred = gnb.predict(X_test)\n", + "print(confusion_matrix(y_test, y_pred))\n", + "accuracy_score(y_test, y_pred)\n", + "print(recall_score(y_test, y_pred))\n", + "\n", + "\n", + "### Test for 94% accuracy\n", + "\n", + "X_trained = Test[['FULL_Charge','FULL_AcidicMolPerc','FULL_DAYM780201','FULL_OOBM850104','AS_MeanAmphiMoment']]\n", + "#X_trained = Test[['FULL_Charge','FULL_AcidicMolPerc','FULL_DAYM780201','FULL_OOBM850104','AS_MeanAmphiMoment']]\n", + "y_pred = gnb.predict(X_trained).astype(int)\n", + "#y_pred\n", + "#savetxt('data.csv', y_pred, delimiter=',',fmt=\"%d\",header=\"CLASS\")\n", + "test = pd.DataFrame(y_pred,columns=['CLASS'])\n", + "test.to_csv(\"Test_data.csv\",sep=\",\",index=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Nueral Networks" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[ 74 306]\n", + " [353 27]]\n", + "0.13289473684210526\n", + "0.07105263157894737\n", + "[[344 36]\n", + " [ 20 360]]\n", + "0.9473684210526315\n" + ] + } + ], + "source": [ + "clf = MLPClassifier(solver='lbfgs', alpha=1e-5,hidden_layer_sizes=(5, 2), random_state=1)\n", + "y_pred = clf.fit(X, y).predict(X_test)\n", + "print(confusion_matrix(y_test, y_pred))\n", + "print(accuracy_score(y_test,y_pred))\n", + "\n", + "##Balancing the data set using smote\n", + "smt = SMOTE()\n", + "X_train, y_train = smt.fit_sample(X_train, y_train)\n", + "np.bincount(y_train)\n", + "##Re runnings the algorithm.\n", + "clf = MLPClassifier(solver='lbfgs', alpha=1e-5,hidden_layer_sizes=(5, 2), random_state=1)\n", + "clf.fit(X_train, y_train)\n", + "y_pred = clf.predict(X_test)\n", + "confusion_matrix(y_test, y_pred)\n", + "accuracy_score(y_test, y_pred)\n", + "print(recall_score(y_test, y_pred))\n", + "\n", + "##Near Miss\n", + "\n", + "nr = NearMiss()\n", + "X_train, y_train = nr.fit_sample(X_train, y_train)\n", + "np.bincount(y_train)\n", + "\n", + "#clf = MLPClassifier(solver='lbfgs', alpha=1e-5,hidden_layer_sizes=(5, 2), random_state=1)\n", + "clf = MLPClassifier(solver='lbfgs', alpha=1e-5,hidden_layer_sizes=(5, 2), random_state=1)\n", + "clf.fit(X_train, y_train)\n", + "y_pred = gnb.predict(X_test)\n", + "print(confusion_matrix(y_test, y_pred))\n", + "accuracy_score(y_test, y_pred)\n", + "print(recall_score(y_test, y_pred))\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Stockastic Gradient" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The model doesn't work well after balancing the data for the class model with SMOTE and Near Miss but the " + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[380 0]\n", + " [157 223]]\n", + "0.7934210526315789\n", + "0.07105263157894737\n", + "[[ 74 306]\n", + " [353 27]]\n", + "0.07105263157894737\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/conda/lib/python3.6/site-packages/sklearn/linear_model/_stochastic_gradient.py:557: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n", + " ConvergenceWarning)\n" + ] + } + ], + "source": [ + "SGDC = SGDClassifier(loss=\"hinge\", penalty=\"l2\", max_iter=30)\n", + "y_pred = SGDC.fit(X, y).predict(X_test)\n", + "print(confusion_matrix(y_test, y_pred))\n", + "print(accuracy_score(y_test,y_pred))\n", + "\n", + "##Balancing the data set using smote\n", + "smt = SMOTE()\n", + "X_train, y_train = smt.fit_sample(X_train, y_train)\n", + "np.bincount(y_train)\n", + "##Re runnings the algorithm.\n", + "SGDC = MLPClassifier(solver='lbfgs', alpha=1e-5,hidden_layer_sizes=(5, 2), random_state=1)\n", + "SGDC.fit(X_train, y_train)\n", + "y_pred = SGDC.predict(X_test)\n", + "confusion_matrix(y_test, y_pred)\n", + "accuracy_score(y_test, y_pred)\n", + "print(recall_score(y_test, y_pred))\n", + "\n", + "##Near Miss\n", + "\n", + "nr = NearMiss()\n", + "X_train, y_train = nr.fit_sample(X_train, y_train)\n", + "np.bincount(y_train)\n", + "\n", + "SGDC = MLPClassifier(solver='lbfgs', alpha=1e-5,hidden_layer_sizes=(5, 2), random_state=1)\n", + "SGDC.fit(X_train, y_train)\n", + "y_pred = SGDC.predict(X_test)\n", + "print(confusion_matrix(y_test, y_pred))\n", + "accuracy_score(y_test, y_pred)\n", + "print(recall_score(y_test, y_pred))\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Support vector machines" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[358 22]\n", + " [ 29 351]]\n", + "0.9328947368421052\n" + ] + } + ], + "source": [ + "SVM = svm.SVC()\n", + "y_pred = SVM.fit(X_train,y_train).predict(X_test)\n", + "print(confusion_matrix(y_test, y_pred))\n", + "print(accuracy_score(y_test,y_pred))\n", + "\n", + "##Balancing the data set using smote\n", + "#smt = SMOTE()\n", + "#X_train, y_train = smt.fit_sample(X_train, y_train)\n", + "#np.bincount(y_train)\n", + "##Re runnings the algorithm.\n", + "#SVM = svm.SVC()\n", + "#SVM .fit(X_train, y_train)\n", + "#y_pred = SGDC.predict(X_test)\n", + "#confusion_matrix(y_test, y_pred)\n", + "#accuracy_score(y_test, y_pred)\n", + "#print(recall_score(y_test, y_pred))\n", + "\n", + "##Near Miss\n", + "\n", + "#nr = NearMiss()\n", + "#X_train, y_train = nr.fit_sample(X_train, y_train)\n", + "#np.bincount(y_train)\n", + "# Testing\n", + "#SVM = svm.SVC()\n", + "#SVM.fit(X_train, y_train)\n", + "#y_pred = SGDC.predict(X_test)\n", + "#print(confusion_matrix(y_test, y_pred))\n", + "#accuracy_score(y_test, y_pred)\n", + "#print(recall_score(y_test, y_pred))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For the different model checked.These two below perfomed the best most times.\n", + "* Logistic Regression\n", + "* Gaussian\n", + "* Neural Networks" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Submission" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201FULL_GEOR030101FULL_OOBM850104NT_EFC195AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CT_RACS820104
count758.000000758.000000758.000000758.000000758.000000758.000000758.000000758.000000758.000000758.000000758.000000
mean2.0738798.9450910.97304673.8218910.994212-2.3979220.08443315.57006773.8442045.9044921.250189
std4.2306157.8144490.1106768.0295240.0323701.5971380.27821911.3625898.9151930.6569110.218102
min-13.0000000.0000000.69900047.0000000.889000-7.8440000.0000000.06000047.0000003.8430000.841000
25%-0.5000002.7217500.89400068.7402500.973000-3.4572500.0000005.70900068.3460005.4712501.096000
50%2.0000007.5000000.96500074.0695000.994000-2.2380000.00000015.05700073.6460005.9355001.188000
75%4.00000014.2302501.05350079.2847501.013000-1.3062500.00000025.29025080.0692506.3752501.378500
max30.00000044.1180001.431000102.9290001.1820002.0170001.00000050.098000102.9290007.5880002.283000
\n", + "
" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n", + "count 758.000000 758.000000 758.000000 758.000000 \n", + "mean 2.073879 8.945091 0.973046 73.821891 \n", + "std 4.230615 7.814449 0.110676 8.029524 \n", + "min -13.000000 0.000000 0.699000 47.000000 \n", + "25% -0.500000 2.721750 0.894000 68.740250 \n", + "50% 2.000000 7.500000 0.965000 74.069500 \n", + "75% 4.000000 14.230250 1.053500 79.284750 \n", + "max 30.000000 44.118000 1.431000 102.929000 \n", + "\n", + " FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n", + "count 758.000000 758.000000 758.000000 758.000000 \n", + "mean 0.994212 -2.397922 0.084433 15.570067 \n", + "std 0.032370 1.597138 0.278219 11.362589 \n", + "min 0.889000 -7.844000 0.000000 0.060000 \n", + "25% 0.973000 -3.457250 0.000000 5.709000 \n", + "50% 0.994000 -2.238000 0.000000 15.057000 \n", + "75% 1.013000 -1.306250 0.000000 25.290250 \n", + "max 1.182000 2.017000 1.000000 50.098000 \n", + "\n", + " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 \n", + "count 758.000000 758.000000 758.000000 \n", + "mean 73.844204 5.904492 1.250189 \n", + "std 8.915193 0.656911 0.218102 \n", + "min 47.000000 3.843000 0.841000 \n", + "25% 68.346000 5.471250 1.096000 \n", + "50% 73.646000 5.935500 1.188000 \n", + "75% 80.069250 6.375250 1.378500 \n", + "max 102.929000 7.588000 2.283000 " + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Test.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "FULL_Charge 0\n", + "FULL_AcidicMolPerc 0\n", + "FULL_AURR980107 0\n", + "FULL_DAYM780201 0\n", + "FULL_GEOR030101 0\n", + "FULL_OOBM850104 0\n", + "NT_EFC195 0\n", + "AS_MeanAmphiMoment 0\n", + "AS_DAYM780201 0\n", + "AS_FUKS010112 0\n", + "CT_RACS820104 0\n", + "CLASS 0\n", + "dtype: int64\n", + "FULL_Charge 0\n", + "FULL_AcidicMolPerc 0\n", + "FULL_AURR980107 0\n", + "FULL_DAYM780201 0\n", + "FULL_GEOR030101 0\n", + "FULL_OOBM850104 0\n", + "NT_EFC195 0\n", + "AS_MeanAmphiMoment 0\n", + "AS_DAYM780201 0\n", + "AS_FUKS010112 0\n", + "CT_RACS820104 0\n", + "CLASS 0\n", + "dtype: int64\n" + ] + } + ], + "source": [ + "print(Train.isna().sum())\n", + "print(Train.isnull().sum())" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [], + "source": [ + "###\n", + "#'FULL_AURR980107'\n", + "##This attribute has outliers greater than 13 \n", + "#Test['FULL_AURR980107']\n", + "#FAURR = np.array(Test['FULL_AURR980107'])\n", + "#FAURR[FAURR >= 13]= FAURR.mean()\n", + "#Test['FULL_AURR980107'] = pd.DataFrame(FAURR)\n", + "\n", + "\n", + "##Removing the outliers and replacing them with the mean\n", + "##Values greater than 10 and values less than -6\n", + "#FCharge = np.array(Test['FULL_Charge'])\n", + "#FCharge[ FCharge >= 10 ]= FCharge.mean()\n", + "#FCharge[ FCharge <= -6 ]= FCharge.mean()\n", + "#Test['FULL_Charge'] = pd.DataFrame(FCharge)\n", + "\n", + "##Removing outliers for values\n", + "#Test['FULL_DAYM780201']\n", + "#FDAY = np.array(Train['FULL_DAYM780201'])\n", + "#FDAY[FDAY >= 95]= FDAY.mean()\n", + "#FDAY[FDAY <= 52]= FDAY.mean()\n", + "#Test['FULL_DAYM780201'] = pd.DataFrame(FDAY)\n", + "### \n", + "#Removing outliers greater\n", + "#Test[['FULL_AcidicMolPerc']] \n", + "#FAcidic = np.array(Train['FULL_AcidicMolPerc'])\n", + "#FAcidic[ FAcidic >= 27 ]= FCharge.mean()\n", + "#Test['FULL_AcidicMolPerc'] = pd.DataFrame(FAcidic)" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [], + "source": [ + "smt = SMOTE()\n", + "X_train, y_train = smt.fit_sample(X, y)\n", + "np.bincount(y_train)\n", + "\n", + "gnb = GaussianNB()\n", + "gnb.fit(X, y)\n", + "X_trained = Test[['FULL_Charge','FULL_AcidicMolPerc','FULL_DAYM780201','FULL_OOBM850104','AS_MeanAmphiMoment']]\n", + "#X_trained = Test[['FULL_Charge','FULL_AcidicMolPerc','FULL_DAYM780201','FULL_OOBM850104','AS_MeanAmphiMoment']]\n", + "y_pred = gnb.predict(X_trained).astype(int)\n", + "#y_pred\n", + "#savetxt('data.csv', y_pred, delimiter=',',fmt=\"%d\",header=\"CLASS\")\n", + "test = pd.DataFrame(y_pred,columns=['CLASS'])\n", + "test.to_csv(\"outliers_avail.csv\",sep=\",\",index=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Voting Classfier" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[358 22]\n", + " [ 22 358]]\n", + "0.9421052631578948\n" + ] + } + ], + "source": [ + "nr = NearMiss()\n", + "X_train, y_train = nr.fit_sample(X_train, y_train)\n", + "np.bincount(y_train)\n", + "ensemble=VotingClassifier(estimators=[('gnb', gnb),('clf',clf),('SVM',SVM)], voting='hard')\n", + "y_pred =ensemble.fit(X_train,y_train).predict(X_test)\n", + "print(confusion_matrix(y_test, y_pred))\n", + "accuracy_score(y_test, y_pred)\n", + "print(recall_score(y_test, y_pred))\n", + "X_trained = Test[['FULL_Charge','FULL_AcidicMolPerc','FULL_DAYM780201','FULL_OOBM850104','AS_MeanAmphiMoment']]\n", + "y_pred = ensemble.predict(X_trained).astype(int)\n", + "test = pd.DataFrame(y_pred,columns=['CLASS'])\n", + "test.to_csv(\"New.csv\",sep=\",\",index=True)\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.6" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} From 74881c0303436bfa83a7232ecf1bd82de23bb1b2 Mon Sep 17 00:00:00 2001 From: Atwine Date: Fri, 6 Mar 2020 08:32:12 +0300 Subject: [PATCH 05/29] latest update --- .../Jupiter Marina-checkpoint.ipynb | 1029 ++++++++++++++--- Assignment Colab/Jupiter Marina.ipynb | 1029 ++++++++++++++--- 2 files changed, 1706 insertions(+), 352 deletions(-) diff --git a/Assignment Colab/.ipynb_checkpoints/Jupiter Marina-checkpoint.ipynb b/Assignment Colab/.ipynb_checkpoints/Jupiter Marina-checkpoint.ipynb index 16c3b99..fec2998 100644 --- a/Assignment Colab/.ipynb_checkpoints/Jupiter Marina-checkpoint.ipynb +++ b/Assignment Colab/.ipynb_checkpoints/Jupiter Marina-checkpoint.ipynb @@ -50,7 +50,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 2, "metadata": { "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0", "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a" @@ -194,7 +194,7 @@ "4 72.944 4.540 1.539 1 " ] }, - "execution_count": 21, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" } @@ -211,7 +211,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -224,7 +224,7 @@ " dtype='object')" ] }, - "execution_count": 4, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -235,7 +235,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -337,7 +337,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -532,7 +532,7 @@ "max 103.167000 8.662000 2.192000 1.000000 " ] }, - "execution_count": 22, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -556,7 +556,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -572,10 +572,10 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 7, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" }, @@ -1092,12 +1092,285 @@ ] }, { - "cell_type": "raw", + "cell_type": "code", + "execution_count": 14, "metadata": {}, + "outputs": [ + { 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "\n", "\n", - "\n", + "neg1=amp_train.iloc[:,0]\n", + "print(neg1) #plot this so that we can see how it looks before\n", + "tneg1=neg1**2\n", + "tneg1.plot(kind=\"density\") #plot side by side to see what the transformation does.\n", + "amp_train.iloc[:,0]=tneg1\n", "\n", "\n", "neg2=amp_train.iloc[:,5]\n", @@ -1140,7 +1413,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -1184,10 +1457,10 @@ " \n", " \n", " 0\n", - " 5.0\n", + " 25.00\n", " 0.000\n", " 74.842\n", - " -3.663\n", + " 13.417569\n", " 0.282\n", " 73.444\n", " 5.661\n", @@ -1195,10 +1468,10 @@ " \n", " \n", " 1\n", - " 4.0\n", + " 16.00\n", " 5.405\n", " 71.595\n", - " -4.011\n", + " 16.088121\n", " 0.600\n", " 68.222\n", " 6.537\n", @@ -1206,10 +1479,10 @@ " \n", " \n", " 2\n", - " 5.5\n", + " 30.25\n", " 5.405\n", " 73.595\n", - " -2.512\n", + " 6.310144\n", " 0.593\n", " 69.444\n", " 4.934\n", @@ -1217,10 +1490,10 @@ " \n", " \n", " 3\n", - " 5.0\n", + " 25.00\n", " 4.167\n", " 66.250\n", - " -1.362\n", + " 1.855044\n", " 0.614\n", " 67.222\n", " 4.316\n", @@ -1228,10 +1501,10 @@ " \n", " \n", " 4\n", - " 7.5\n", + " 56.25\n", " 8.537\n", " 64.720\n", - " -2.091\n", + " 4.372281\n", " 0.616\n", " 72.944\n", " 4.540\n", @@ -1243,11 +1516,11 @@ ], "text/plain": [ " FULL_Charge FULL_AcidicMolPerc FULL_DAYM780201 FULL_OOBM850104 \\\n", - "0 5.0 0.000 74.842 -3.663 \n", - "1 4.0 5.405 71.595 -4.011 \n", - "2 5.5 5.405 73.595 -2.512 \n", - "3 5.0 4.167 66.250 -1.362 \n", - "4 7.5 8.537 64.720 -2.091 \n", + "0 25.00 0.000 74.842 13.417569 \n", + "1 16.00 5.405 71.595 16.088121 \n", + "2 30.25 5.405 73.595 6.310144 \n", + "3 25.00 4.167 66.250 1.855044 \n", + "4 56.25 8.537 64.720 4.372281 \n", "\n", " AS_MeanAmphiMoment AS_DAYM780201 AS_FUKS010112 CLASS \n", "0 0.282 73.444 5.661 1.0 \n", @@ -1257,7 +1530,7 @@ "4 0.616 72.944 4.540 1.0 " ] }, - "execution_count": 23, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -1277,77 +1550,16 @@ }, { "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "ename": "ValueError", - "evalue": "Input X must be non-negative.", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mtest\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mSelectKBest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscore_func\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mchi2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 12\u001b[0;31m \u001b[0mfit\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtest\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtest_atr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mclass_atr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 13\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 14\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/sklearn/feature_selection/_univariate_selection.py\u001b[0m in \u001b[0;36mfit\u001b[0;34m(self, X, y)\u001b[0m\n\u001b[1;32m 347\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 348\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_check_params\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m 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\u001b[0mscore_func_ret\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/sklearn/feature_selection/_univariate_selection.py\u001b[0m in \u001b[0;36mchi2\u001b[0;34m(X, y)\u001b[0m\n\u001b[1;32m 214\u001b[0m \u001b[0mX\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcheck_array\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maccept_sparse\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'csr'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 215\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0many\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0missparse\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 216\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Input X must be non-negative.\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 217\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 218\u001b[0m \u001b[0mY\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mLabelBinarizer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit_transform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mValueError\u001b[0m: Input X must be non-negative." - ] - } - ], - "source": [ - "#test two\n", - "from sklearn.feature_selection import SelectKBest\n", - "from sklearn.feature_selection import chi2\n", - "\n", - "test_array = amp_train2.values\n", - "\n", - "test_atr = test_array[:,0:7]\n", - "class_atr = test_array[:,7]\n", - "\n", - "\n", - "test = SelectKBest(score_func=chi2, k=5)\n", - "fit = test.fit(test_atr, class_atr)\n", - "\n", - "\n", - "print(fit.scores_)\n", - "features = fit.transform(test_atr)\n", - "names2=amp_train2.columns[fit.get_support(indices=True)]\n", - "amp_train3=pd.DataFrame(features,columns=names2)\n", - "print(amp_train3[5:])\n", - "\n", - "\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 17, + "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Index(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'AS_MeanAmphiMoment',\n", - " 'AS_FUKS010112'],\n", - " dtype='object')\n", - "Index(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_OOBM850104',\n", - " 'AS_MeanAmphiMoment'],\n", - " dtype='object')\n", - "Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201',\n", - " 'FULL_OOBM850104', 'AS_MeanAmphiMoment'],\n", - " dtype='object')\n", - "Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", - " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", - " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", - " 'CLASS'],\n", - " dtype='object')\n", + "[1.53389981e+04 7.35553647e+03 9.22860060e+02 7.06525505e+03\n", + " 1.24812698e+04 6.62112299e+02 2.76320294e-01]\n", " FULL_Charge FULL_AcidicMolPerc FULL_DAYM780201 FULL_OOBM850104 \\\n", - "0 25.00 0.000 74.842 13.417569 \n", - "1 16.00 5.405 71.595 16.088121 \n", - "2 30.25 5.405 73.595 6.310144 \n", - "3 25.00 4.167 66.250 1.855044 \n", - "4 56.25 8.537 64.720 4.372281 \n", "5 25.00 7.692 78.949 9.554281 \n", "6 9.00 6.897 78.586 12.559936 \n", "7 4.00 5.882 76.588 34.012224 \n", @@ -1373,6 +1585,11 @@ "27 1.00 5.556 74.833 15.038884 \n", "28 42.25 0.000 66.500 17.926756 \n", "29 56.25 8.333 69.375 3.115225 \n", + "30 0.25 11.765 79.882 9.084196 \n", + "31 2.25 0.000 73.313 21.196816 \n", + "32 49.00 8.108 74.838 19.140625 \n", + "33 4.00 0.000 71.300 29.408929 \n", + "34 81.00 0.000 63.625 13.616100 \n", "... ... ... ... ... \n", "3008 36.00 20.000 83.686 2.033476 \n", "3009 1.00 22.500 77.700 0.045796 \n", @@ -1405,73 +1622,103 @@ "3036 4.00 5.000 73.750 7.409284 \n", "3037 1.00 15.789 66.158 4.326400 \n", "\n", - " AS_MeanAmphiMoment AS_DAYM780201 AS_FUKS010112 CLASS \n", - "0 0.282 73.444 5.661 1.0 \n", - "1 0.600 68.222 6.537 1.0 \n", - "2 0.593 69.444 4.934 1.0 \n", - "3 0.614 67.222 4.316 1.0 \n", - "4 0.616 72.944 4.540 1.0 \n", - "5 0.511 78.778 5.992 1.0 \n", - "6 0.385 78.222 6.284 1.0 \n", - "7 0.154 76.588 6.479 1.0 \n", - "8 0.188 64.333 3.849 1.0 \n", - "9 0.361 63.222 6.327 1.0 \n", - "10 0.510 76.389 5.402 1.0 \n", - "11 0.163 61.667 5.627 1.0 \n", - "12 0.263 71.611 6.804 1.0 \n", - "13 0.232 72.778 6.726 1.0 \n", - "14 0.402 60.769 7.112 1.0 \n", - "15 0.187 65.167 5.238 1.0 \n", - "16 0.536 75.667 6.996 1.0 \n", - "17 0.826 65.944 6.038 1.0 \n", - "18 1.100 78.444 6.141 1.0 \n", - "19 1.210 66.944 6.149 1.0 \n", - "20 1.304 73.500 6.604 1.0 \n", - "21 1.726 61.056 5.722 1.0 \n", - "22 1.717 70.833 6.669 1.0 \n", - "23 2.834 52.769 7.426 1.0 \n", - "24 2.980 63.231 6.942 1.0 \n", - "25 2.138 63.444 7.546 1.0 \n", - "26 2.435 62.056 6.801 1.0 \n", - "27 2.044 74.833 6.644 1.0 \n", - "28 2.704 69.444 5.673 1.0 \n", - "29 2.743 65.889 5.242 1.0 \n", - "... ... ... ... ... \n", - "3008 15.452 81.722 6.566 0.0 \n", - "3009 15.625 78.333 5.747 0.0 \n", - "3010 15.502 75.556 5.558 0.0 \n", - "3011 15.676 70.556 5.723 0.0 \n", - "3012 15.813 75.111 6.378 0.0 \n", - "3013 15.774 78.278 6.374 0.0 \n", - "3014 23.502 80.250 5.325 0.0 \n", - "3015 15.974 65.944 5.169 0.0 \n", - "3016 23.550 71.000 5.017 0.0 \n", - "3017 15.781 80.167 6.149 0.0 \n", - "3018 17.666 88.250 6.383 0.0 \n", - "3019 15.838 80.111 6.138 0.0 \n", - "3020 15.867 74.167 5.523 0.0 \n", - "3021 16.209 79.944 5.267 0.0 \n", - "3022 22.477 66.769 6.068 0.0 \n", - "3023 16.444 74.111 5.611 0.0 \n", - "3024 16.495 74.944 6.606 0.0 \n", - "3025 16.513 82.056 5.732 0.0 \n", - "3026 26.931 81.545 5.120 0.0 \n", - "3027 16.517 78.111 5.451 0.0 \n", - "3028 18.119 79.938 6.241 0.0 \n", - "3029 20.625 69.143 5.769 0.0 \n", - "3030 16.256 65.722 6.378 0.0 \n", - "3031 16.365 77.278 5.821 0.0 \n", - "3032 24.497 82.917 5.640 0.0 \n", - "3033 16.706 68.611 5.598 0.0 \n", - "3034 16.897 73.278 6.194 0.0 \n", - "3035 16.918 82.111 5.889 0.0 \n", - "3036 17.131 74.722 6.055 0.0 \n", - "3037 17.151 67.111 5.853 0.0 \n", + " AS_MeanAmphiMoment \n", + "5 0.511 \n", + "6 0.385 \n", + "7 0.154 \n", + "8 0.188 \n", + "9 0.361 \n", + "10 0.510 \n", + "11 0.163 \n", + "12 0.263 \n", + "13 0.232 \n", + "14 0.402 \n", + "15 0.187 \n", + "16 0.536 \n", + "17 0.826 \n", + "18 1.100 \n", + "19 1.210 \n", + "20 1.304 \n", + "21 1.726 \n", + "22 1.717 \n", + "23 2.834 \n", + "24 2.980 \n", + "25 2.138 \n", + "26 2.435 \n", + "27 2.044 \n", + "28 2.704 \n", + "29 2.743 \n", + "30 2.898 \n", + "31 3.394 \n", + "32 3.282 \n", + "33 3.214 \n", + "34 3.020 \n", + "... ... \n", + "3008 15.452 \n", + "3009 15.625 \n", + "3010 15.502 \n", + "3011 15.676 \n", + "3012 15.813 \n", + "3013 15.774 \n", + "3014 23.502 \n", + "3015 15.974 \n", + "3016 23.550 \n", + "3017 15.781 \n", + "3018 17.666 \n", + "3019 15.838 \n", + "3020 15.867 \n", + "3021 16.209 \n", + "3022 22.477 \n", + "3023 16.444 \n", + "3024 16.495 \n", + "3025 16.513 \n", + "3026 26.931 \n", + "3027 16.517 \n", + "3028 18.119 \n", + "3029 20.625 \n", + "3030 16.256 \n", + "3031 16.365 \n", + "3032 24.497 \n", + "3033 16.706 \n", + "3034 16.897 \n", + "3035 16.918 \n", + "3036 17.131 \n", + "3037 17.151 \n", "\n", - "[3038 rows x 8 columns]\n" + "[3033 rows x 5 columns]\n" ] } ], + "source": [ + "#test two\n", + "from sklearn.feature_selection import SelectKBest\n", + "from sklearn.feature_selection import chi2\n", + "\n", + "test_array = amp_train2.values\n", + "\n", + "test_atr = test_array[:,0:7]\n", + "class_atr = test_array[:,7]\n", + "\n", + "\n", + "test = SelectKBest(score_func=chi2, k=5)\n", + "fit = test.fit(test_atr, class_atr)\n", + "\n", + "\n", + "print(fit.scores_)\n", + "features = fit.transform(test_atr)\n", + "names2=amp_train2.columns[fit.get_support(indices=True)]\n", + "amp_train3=pd.DataFrame(features,columns=names2)\n", + "print(amp_train3[5:])\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], "source": [ "# Test three Recursive feature elimination\n", "\n", @@ -1518,9 +1765,143 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " FULL_Charge FULL_AcidicMolPerc FULL_OOBM850104 FULL_DAYM780201 \\\n", + "0 25.00 0.000 13.417569 74.842 \n", + "1 16.00 5.405 16.088121 71.595 \n", + "2 30.25 5.405 6.310144 73.595 \n", + "3 25.00 4.167 1.855044 66.250 \n", + "4 56.25 8.537 4.372281 64.720 \n", + "5 25.00 7.692 9.554281 78.949 \n", + "6 9.00 6.897 12.559936 78.586 \n", + "7 4.00 5.882 34.012224 76.588 \n", + "8 49.00 2.632 0.085264 60.447 \n", + "9 81.00 0.000 15.116544 65.808 \n", + "10 4.00 3.448 13.778944 71.172 \n", + "11 6.25 0.000 1.852321 60.579 \n", + "12 9.00 0.000 12.981609 70.875 \n", + "13 9.00 7.143 18.748900 71.357 \n", + "14 6.25 7.692 13.256881 60.769 \n", + "15 36.00 4.348 2.050624 67.870 \n", + "16 4.00 0.000 24.285184 73.842 \n", + "17 16.00 0.000 24.770529 64.083 \n", + "18 20.25 11.111 0.481636 77.185 \n", + "19 4.00 4.167 9.778129 68.667 \n", + "20 4.00 6.667 11.068929 68.233 \n", + "21 9.00 10.345 22.127616 72.000 \n", + "22 12.25 2.703 13.162384 72.919 \n", + "23 1.00 0.000 21.696964 52.769 \n", + "24 1.00 0.000 16.483600 63.231 \n", + "25 30.25 4.348 22.619536 58.913 \n", + "26 42.25 0.000 11.703241 63.917 \n", + "27 1.00 5.556 15.038884 74.833 \n", + "28 42.25 0.000 17.926756 66.500 \n", + "29 56.25 8.333 3.115225 69.375 \n", + "... ... ... ... ... \n", + "3008 36.00 20.000 2.033476 83.686 \n", + "3009 1.00 22.500 0.045796 77.700 \n", + "3010 1.00 12.500 1.575025 79.708 \n", + "3011 0.00 5.263 2.334784 73.079 \n", + "3012 9.00 19.608 1.058841 83.412 \n", + "3013 1.00 12.245 2.849344 76.122 \n", + "3014 1.00 16.667 0.122500 80.250 \n", + "3015 4.00 10.811 5.017600 67.514 \n", + "3016 1.00 8.333 2.214144 71.000 \n", + "3017 0.00 10.256 1.153476 80.077 \n", + "3018 0.00 18.750 1.726596 88.250 \n", + "3019 0.25 16.667 1.334025 77.729 \n", + "3020 0.25 11.429 0.819025 77.657 \n", + "3021 1.00 11.538 0.040000 78.038 \n", + "3022 9.00 0.000 0.029929 66.769 \n", + "3023 4.00 12.000 2.005056 75.867 \n", + "3024 12.25 20.000 7.823209 73.050 \n", + "3025 6.25 10.714 8.334769 78.071 \n", + "3026 0.25 0.000 0.381924 81.545 \n", + "3027 81.00 7.547 11.682724 77.283 \n", + "3028 4.00 18.750 1.196836 79.938 \n", + "3029 20.25 14.286 1.177225 69.143 \n", + "3030 4.00 12.963 11.874916 72.815 \n", + "3031 0.00 17.021 5.143824 76.234 \n", + "3032 0.00 16.667 4.297329 82.917 \n", + "3033 1.00 5.263 4.626801 67.947 \n", + "3034 42.25 21.667 2.805625 75.433 \n", + "3035 2.25 12.500 0.842724 76.542 \n", + "3036 4.00 5.000 7.409284 73.750 \n", + "3037 1.00 15.789 4.326400 66.158 \n", + "\n", + " AS_MeanAmphiMoment CLASS \n", + "0 0.282 1 \n", + "1 0.600 1 \n", + "2 0.593 1 \n", + "3 0.614 1 \n", + "4 0.616 1 \n", + "5 0.511 1 \n", + "6 0.385 1 \n", + "7 0.154 1 \n", + "8 0.188 1 \n", + "9 0.361 1 \n", + "10 0.510 1 \n", + "11 0.163 1 \n", + "12 0.263 1 \n", + "13 0.232 1 \n", + "14 0.402 1 \n", + "15 0.187 1 \n", + "16 0.536 1 \n", + "17 0.826 1 \n", + "18 1.100 1 \n", + "19 1.210 1 \n", + "20 1.304 1 \n", + "21 1.726 1 \n", + "22 1.717 1 \n", + "23 2.834 1 \n", + "24 2.980 1 \n", + "25 2.138 1 \n", + "26 2.435 1 \n", + "27 2.044 1 \n", + "28 2.704 1 \n", + "29 2.743 1 \n", + "... ... ... \n", + "3008 15.452 0 \n", + "3009 15.625 0 \n", + "3010 15.502 0 \n", + "3011 15.676 0 \n", + "3012 15.813 0 \n", + "3013 15.774 0 \n", + "3014 23.502 0 \n", + "3015 15.974 0 \n", + "3016 23.550 0 \n", + "3017 15.781 0 \n", + "3018 17.666 0 \n", + "3019 15.838 0 \n", + "3020 15.867 0 \n", + "3021 16.209 0 \n", + "3022 22.477 0 \n", + "3023 16.444 0 \n", + "3024 16.495 0 \n", + "3025 16.513 0 \n", + "3026 26.931 0 \n", + "3027 16.517 0 \n", + "3028 18.119 0 \n", + "3029 20.625 0 \n", + "3030 16.256 0 \n", + "3031 16.365 0 \n", + "3032 24.497 0 \n", + "3033 16.706 0 \n", + "3034 16.897 0 \n", + "3035 16.918 0 \n", + "3036 17.131 0 \n", + "3037 17.151 0 \n", + "\n", + "[3038 rows x 6 columns]\n" + ] + } + ], "source": [ "test_amp =amp_train.loc[:,['FULL_Charge', 'FULL_AcidicMolPerc',\"FULL_OOBM850104\",'FULL_DAYM780201', 'AS_MeanAmphiMoment','CLASS']]\n", "print(test_amp)\n" @@ -1535,7 +1916,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ @@ -1561,9 +1942,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 91.442% (1.795%)\n" + ] + } + ], "source": [ "\n", "X=test_amp.iloc[:,0:5]\n", @@ -1599,25 +1988,117 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 29, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "pandas.core.frame.DataFrame" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(test_data.loc[:,['FULL_Charge', 'FULL_AcidicMolPerc','FULL_DAYM780201', 'FULL_OOBM850104', 'AS_MeanAmphiMoment']])" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 91.44736842105263\n", + "[[273 31]\n", + " [ 21 283]]\n", + "MCC: 0.8293962196513646\n" + ] + }, + { + "data": { + "text/plain": [ + "array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 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LogisticRegression()\n", + "\n", "model.fit(X_train, Y_train)\n", + "\n", "predicted = model.predict(X_test)\n", + "\n", "matrix = confusion_matrix(Y_test, predicted)\n", + "\n", "result = model.score(X_test, Y_test)\n", "print(\"Accuracy: \", (result*100.0))\n", "print(matrix)\n", @@ -1625,7 +2106,7 @@ "#print(test_data)\n", "\n", "test_data2=test_data.loc[:,['FULL_Charge', 'FULL_AcidicMolPerc','FULL_DAYM780201', 'FULL_OOBM850104', 'AS_MeanAmphiMoment']]\n", - "test_data2=test_data2.values \n", + "#test_data2=test_data2.values \n", "#model1 = LogisticRegression() \n", "#model1.fit(X,Y)\n", "kj_results=model.predict(test_data2)\n", @@ -1663,9 +2144,74 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 26, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 91.69407894736842\n", + "[[586 29]\n", + " [ 72 529]]\n", + "MCC: 0.8358210636901913\n" + ] + }, + { + "data": { + "text/plain": [ + 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- "Y=test_amp.iloc[:,5]\n", + "X=test_amp[:,0:5]\n", + "Y=test_amp[:,5]\n", "model=GaussianNB() \n", "model.fit(X,Y)\n", "kj_results=model.predict(test_data2)\n", @@ -1701,9 +2248,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 31, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 90.948% (1.647%)\n" + ] + } + ], "source": [ "model=LinearDiscriminantAnalysis()\n", "folds=10\n", @@ -1721,16 +2276,138 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 33, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 91.804% (1.970%)\n" + ] + } + ], "source": [ - "model=SVC()\n", + "model_sv=SVC()\n", "folds=10\n", "kfold = KFold(n_splits=folds, random_state=7, shuffle=True,)\n", "results = cross_val_score(model, X, Y, cv=kfold)\n", "print((\"Accuracy: %.3f%% (%.3f%%)\") % (results.mean()*100.0, results.std()*100.0))" ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "SVC(C=1.0, break_ties=False, cache_size=200, class_weight=None, coef0=0.0,\n", + " decision_function_shape='ovr', degree=3, gamma='scale', kernel='rbf',\n", + " max_iter=-1, probability=False, random_state=None, shrinking=True,\n", + " tol=0.001, verbose=False)" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model_sv.fit(X_train, Y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "((758, 5), (2430, 5))" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "test_data2.shape, X_train.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1., 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "\n", "\n", - "\n", + "neg1=amp_train.iloc[:,0]\n", + "print(neg1) #plot this so that we can see how it looks before\n", + "tneg1=neg1**2\n", + "tneg1.plot(kind=\"density\") #plot side by side to see what the transformation does.\n", + "amp_train.iloc[:,0]=tneg1\n", "\n", "\n", "neg2=amp_train.iloc[:,5]\n", @@ -1140,7 +1413,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -1184,10 +1457,10 @@ " \n", " \n", " 0\n", - " 5.0\n", + " 25.00\n", " 0.000\n", " 74.842\n", - " -3.663\n", + " 13.417569\n", " 0.282\n", " 73.444\n", " 5.661\n", @@ -1195,10 +1468,10 @@ " \n", " \n", " 1\n", - " 4.0\n", + " 16.00\n", " 5.405\n", " 71.595\n", - " -4.011\n", + " 16.088121\n", " 0.600\n", " 68.222\n", " 6.537\n", @@ -1206,10 +1479,10 @@ " \n", " \n", " 2\n", - " 5.5\n", + " 30.25\n", " 5.405\n", " 73.595\n", - " -2.512\n", + " 6.310144\n", " 0.593\n", " 69.444\n", " 4.934\n", @@ -1217,10 +1490,10 @@ " \n", " \n", " 3\n", - " 5.0\n", + " 25.00\n", " 4.167\n", " 66.250\n", - " -1.362\n", + " 1.855044\n", " 0.614\n", " 67.222\n", " 4.316\n", @@ -1228,10 +1501,10 @@ " \n", " \n", " 4\n", - " 7.5\n", + " 56.25\n", " 8.537\n", " 64.720\n", - " -2.091\n", + " 4.372281\n", " 0.616\n", " 72.944\n", " 4.540\n", @@ -1243,11 +1516,11 @@ ], "text/plain": [ " FULL_Charge FULL_AcidicMolPerc FULL_DAYM780201 FULL_OOBM850104 \\\n", - "0 5.0 0.000 74.842 -3.663 \n", - "1 4.0 5.405 71.595 -4.011 \n", - "2 5.5 5.405 73.595 -2.512 \n", - "3 5.0 4.167 66.250 -1.362 \n", - "4 7.5 8.537 64.720 -2.091 \n", + "0 25.00 0.000 74.842 13.417569 \n", + "1 16.00 5.405 71.595 16.088121 \n", + "2 30.25 5.405 73.595 6.310144 \n", + "3 25.00 4.167 66.250 1.855044 \n", + "4 56.25 8.537 64.720 4.372281 \n", "\n", " AS_MeanAmphiMoment AS_DAYM780201 AS_FUKS010112 CLASS \n", "0 0.282 73.444 5.661 1.0 \n", @@ -1257,7 +1530,7 @@ "4 0.616 72.944 4.540 1.0 " ] }, - "execution_count": 23, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -1277,77 +1550,16 @@ }, { "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "ename": "ValueError", - "evalue": "Input X must be non-negative.", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mtest\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mSelectKBest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscore_func\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mchi2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 12\u001b[0;31m \u001b[0mfit\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtest\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtest_atr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mclass_atr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 13\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 14\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/sklearn/feature_selection/_univariate_selection.py\u001b[0m in \u001b[0;36mfit\u001b[0;34m(self, X, y)\u001b[0m\n\u001b[1;32m 347\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 348\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_check_params\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m 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\u001b[0mscore_func_ret\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/opt/anaconda3/lib/python3.7/site-packages/sklearn/feature_selection/_univariate_selection.py\u001b[0m in \u001b[0;36mchi2\u001b[0;34m(X, y)\u001b[0m\n\u001b[1;32m 214\u001b[0m \u001b[0mX\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcheck_array\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maccept_sparse\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'csr'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 215\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0many\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0missparse\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 216\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Input X must be non-negative.\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 217\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 218\u001b[0m \u001b[0mY\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mLabelBinarizer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit_transform\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mValueError\u001b[0m: Input X must be non-negative." - ] - } - ], - "source": [ - "#test two\n", - "from sklearn.feature_selection import SelectKBest\n", - "from sklearn.feature_selection import chi2\n", - "\n", - "test_array = amp_train2.values\n", - "\n", - "test_atr = test_array[:,0:7]\n", - "class_atr = test_array[:,7]\n", - "\n", - "\n", - "test = SelectKBest(score_func=chi2, k=5)\n", - "fit = test.fit(test_atr, class_atr)\n", - "\n", - "\n", - "print(fit.scores_)\n", - "features = fit.transform(test_atr)\n", - "names2=amp_train2.columns[fit.get_support(indices=True)]\n", - "amp_train3=pd.DataFrame(features,columns=names2)\n", - "print(amp_train3[5:])\n", - "\n", - "\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 17, + "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Index(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'AS_MeanAmphiMoment',\n", - " 'AS_FUKS010112'],\n", - " dtype='object')\n", - "Index(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_OOBM850104',\n", - " 'AS_MeanAmphiMoment'],\n", - " dtype='object')\n", - "Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201',\n", - " 'FULL_OOBM850104', 'AS_MeanAmphiMoment'],\n", - " dtype='object')\n", - "Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", - " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", - " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", - " 'CLASS'],\n", - " dtype='object')\n", + "[1.53389981e+04 7.35553647e+03 9.22860060e+02 7.06525505e+03\n", + " 1.24812698e+04 6.62112299e+02 2.76320294e-01]\n", " FULL_Charge FULL_AcidicMolPerc FULL_DAYM780201 FULL_OOBM850104 \\\n", - "0 25.00 0.000 74.842 13.417569 \n", - "1 16.00 5.405 71.595 16.088121 \n", - "2 30.25 5.405 73.595 6.310144 \n", - "3 25.00 4.167 66.250 1.855044 \n", - "4 56.25 8.537 64.720 4.372281 \n", "5 25.00 7.692 78.949 9.554281 \n", "6 9.00 6.897 78.586 12.559936 \n", "7 4.00 5.882 76.588 34.012224 \n", @@ -1373,6 +1585,11 @@ "27 1.00 5.556 74.833 15.038884 \n", "28 42.25 0.000 66.500 17.926756 \n", "29 56.25 8.333 69.375 3.115225 \n", + "30 0.25 11.765 79.882 9.084196 \n", + "31 2.25 0.000 73.313 21.196816 \n", + "32 49.00 8.108 74.838 19.140625 \n", + "33 4.00 0.000 71.300 29.408929 \n", + "34 81.00 0.000 63.625 13.616100 \n", "... ... ... ... ... \n", "3008 36.00 20.000 83.686 2.033476 \n", "3009 1.00 22.500 77.700 0.045796 \n", @@ -1405,73 +1622,103 @@ "3036 4.00 5.000 73.750 7.409284 \n", "3037 1.00 15.789 66.158 4.326400 \n", "\n", - " AS_MeanAmphiMoment AS_DAYM780201 AS_FUKS010112 CLASS \n", - "0 0.282 73.444 5.661 1.0 \n", - "1 0.600 68.222 6.537 1.0 \n", - "2 0.593 69.444 4.934 1.0 \n", - "3 0.614 67.222 4.316 1.0 \n", - "4 0.616 72.944 4.540 1.0 \n", - "5 0.511 78.778 5.992 1.0 \n", - "6 0.385 78.222 6.284 1.0 \n", - "7 0.154 76.588 6.479 1.0 \n", - "8 0.188 64.333 3.849 1.0 \n", - "9 0.361 63.222 6.327 1.0 \n", - "10 0.510 76.389 5.402 1.0 \n", - "11 0.163 61.667 5.627 1.0 \n", - "12 0.263 71.611 6.804 1.0 \n", - "13 0.232 72.778 6.726 1.0 \n", - "14 0.402 60.769 7.112 1.0 \n", - "15 0.187 65.167 5.238 1.0 \n", - "16 0.536 75.667 6.996 1.0 \n", - "17 0.826 65.944 6.038 1.0 \n", - "18 1.100 78.444 6.141 1.0 \n", - "19 1.210 66.944 6.149 1.0 \n", - "20 1.304 73.500 6.604 1.0 \n", - "21 1.726 61.056 5.722 1.0 \n", - "22 1.717 70.833 6.669 1.0 \n", - "23 2.834 52.769 7.426 1.0 \n", - "24 2.980 63.231 6.942 1.0 \n", - "25 2.138 63.444 7.546 1.0 \n", - "26 2.435 62.056 6.801 1.0 \n", - "27 2.044 74.833 6.644 1.0 \n", - "28 2.704 69.444 5.673 1.0 \n", - "29 2.743 65.889 5.242 1.0 \n", - "... ... ... ... ... \n", - "3008 15.452 81.722 6.566 0.0 \n", - "3009 15.625 78.333 5.747 0.0 \n", - "3010 15.502 75.556 5.558 0.0 \n", - "3011 15.676 70.556 5.723 0.0 \n", - "3012 15.813 75.111 6.378 0.0 \n", - "3013 15.774 78.278 6.374 0.0 \n", - "3014 23.502 80.250 5.325 0.0 \n", - "3015 15.974 65.944 5.169 0.0 \n", - "3016 23.550 71.000 5.017 0.0 \n", - "3017 15.781 80.167 6.149 0.0 \n", - "3018 17.666 88.250 6.383 0.0 \n", - "3019 15.838 80.111 6.138 0.0 \n", - "3020 15.867 74.167 5.523 0.0 \n", - "3021 16.209 79.944 5.267 0.0 \n", - "3022 22.477 66.769 6.068 0.0 \n", - "3023 16.444 74.111 5.611 0.0 \n", - "3024 16.495 74.944 6.606 0.0 \n", - "3025 16.513 82.056 5.732 0.0 \n", - "3026 26.931 81.545 5.120 0.0 \n", - "3027 16.517 78.111 5.451 0.0 \n", - "3028 18.119 79.938 6.241 0.0 \n", - "3029 20.625 69.143 5.769 0.0 \n", - "3030 16.256 65.722 6.378 0.0 \n", - "3031 16.365 77.278 5.821 0.0 \n", - "3032 24.497 82.917 5.640 0.0 \n", - "3033 16.706 68.611 5.598 0.0 \n", - "3034 16.897 73.278 6.194 0.0 \n", - "3035 16.918 82.111 5.889 0.0 \n", - "3036 17.131 74.722 6.055 0.0 \n", - "3037 17.151 67.111 5.853 0.0 \n", + " AS_MeanAmphiMoment \n", + "5 0.511 \n", + "6 0.385 \n", + "7 0.154 \n", + "8 0.188 \n", + "9 0.361 \n", + "10 0.510 \n", + "11 0.163 \n", + "12 0.263 \n", + "13 0.232 \n", + "14 0.402 \n", + "15 0.187 \n", + "16 0.536 \n", + "17 0.826 \n", + "18 1.100 \n", + "19 1.210 \n", + "20 1.304 \n", + "21 1.726 \n", + "22 1.717 \n", + "23 2.834 \n", + "24 2.980 \n", + "25 2.138 \n", + "26 2.435 \n", + "27 2.044 \n", + "28 2.704 \n", + "29 2.743 \n", + "30 2.898 \n", + "31 3.394 \n", + "32 3.282 \n", + "33 3.214 \n", + "34 3.020 \n", + "... ... \n", + "3008 15.452 \n", + "3009 15.625 \n", + "3010 15.502 \n", + "3011 15.676 \n", + "3012 15.813 \n", + "3013 15.774 \n", + "3014 23.502 \n", + "3015 15.974 \n", + "3016 23.550 \n", + "3017 15.781 \n", + "3018 17.666 \n", + "3019 15.838 \n", + "3020 15.867 \n", + "3021 16.209 \n", + "3022 22.477 \n", + "3023 16.444 \n", + "3024 16.495 \n", + "3025 16.513 \n", + "3026 26.931 \n", + "3027 16.517 \n", + "3028 18.119 \n", + "3029 20.625 \n", + "3030 16.256 \n", + "3031 16.365 \n", + "3032 24.497 \n", + "3033 16.706 \n", + "3034 16.897 \n", + "3035 16.918 \n", + "3036 17.131 \n", + "3037 17.151 \n", "\n", - "[3038 rows x 8 columns]\n" + "[3033 rows x 5 columns]\n" ] } ], + "source": [ + "#test two\n", + "from sklearn.feature_selection import SelectKBest\n", + "from sklearn.feature_selection import chi2\n", + "\n", + "test_array = amp_train2.values\n", + "\n", + "test_atr = test_array[:,0:7]\n", + "class_atr = test_array[:,7]\n", + "\n", + "\n", + "test = SelectKBest(score_func=chi2, k=5)\n", + "fit = test.fit(test_atr, class_atr)\n", + "\n", + "\n", + "print(fit.scores_)\n", + "features = fit.transform(test_atr)\n", + "names2=amp_train2.columns[fit.get_support(indices=True)]\n", + "amp_train3=pd.DataFrame(features,columns=names2)\n", + "print(amp_train3[5:])\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], "source": [ "# Test three Recursive feature elimination\n", "\n", @@ -1518,9 +1765,143 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " FULL_Charge FULL_AcidicMolPerc FULL_OOBM850104 FULL_DAYM780201 \\\n", + "0 25.00 0.000 13.417569 74.842 \n", + "1 16.00 5.405 16.088121 71.595 \n", + "2 30.25 5.405 6.310144 73.595 \n", + "3 25.00 4.167 1.855044 66.250 \n", + "4 56.25 8.537 4.372281 64.720 \n", + "5 25.00 7.692 9.554281 78.949 \n", + "6 9.00 6.897 12.559936 78.586 \n", + "7 4.00 5.882 34.012224 76.588 \n", + "8 49.00 2.632 0.085264 60.447 \n", + "9 81.00 0.000 15.116544 65.808 \n", + "10 4.00 3.448 13.778944 71.172 \n", + "11 6.25 0.000 1.852321 60.579 \n", + "12 9.00 0.000 12.981609 70.875 \n", + "13 9.00 7.143 18.748900 71.357 \n", + "14 6.25 7.692 13.256881 60.769 \n", + "15 36.00 4.348 2.050624 67.870 \n", + "16 4.00 0.000 24.285184 73.842 \n", + "17 16.00 0.000 24.770529 64.083 \n", + "18 20.25 11.111 0.481636 77.185 \n", + "19 4.00 4.167 9.778129 68.667 \n", + "20 4.00 6.667 11.068929 68.233 \n", + "21 9.00 10.345 22.127616 72.000 \n", + "22 12.25 2.703 13.162384 72.919 \n", + "23 1.00 0.000 21.696964 52.769 \n", + "24 1.00 0.000 16.483600 63.231 \n", + "25 30.25 4.348 22.619536 58.913 \n", + "26 42.25 0.000 11.703241 63.917 \n", + "27 1.00 5.556 15.038884 74.833 \n", + "28 42.25 0.000 17.926756 66.500 \n", + "29 56.25 8.333 3.115225 69.375 \n", + "... ... ... ... ... \n", + "3008 36.00 20.000 2.033476 83.686 \n", + "3009 1.00 22.500 0.045796 77.700 \n", + "3010 1.00 12.500 1.575025 79.708 \n", + "3011 0.00 5.263 2.334784 73.079 \n", + "3012 9.00 19.608 1.058841 83.412 \n", + "3013 1.00 12.245 2.849344 76.122 \n", + "3014 1.00 16.667 0.122500 80.250 \n", + "3015 4.00 10.811 5.017600 67.514 \n", + "3016 1.00 8.333 2.214144 71.000 \n", + "3017 0.00 10.256 1.153476 80.077 \n", + "3018 0.00 18.750 1.726596 88.250 \n", + "3019 0.25 16.667 1.334025 77.729 \n", + "3020 0.25 11.429 0.819025 77.657 \n", + "3021 1.00 11.538 0.040000 78.038 \n", + "3022 9.00 0.000 0.029929 66.769 \n", + "3023 4.00 12.000 2.005056 75.867 \n", + "3024 12.25 20.000 7.823209 73.050 \n", + "3025 6.25 10.714 8.334769 78.071 \n", + "3026 0.25 0.000 0.381924 81.545 \n", + "3027 81.00 7.547 11.682724 77.283 \n", + "3028 4.00 18.750 1.196836 79.938 \n", + "3029 20.25 14.286 1.177225 69.143 \n", + "3030 4.00 12.963 11.874916 72.815 \n", + "3031 0.00 17.021 5.143824 76.234 \n", + "3032 0.00 16.667 4.297329 82.917 \n", + "3033 1.00 5.263 4.626801 67.947 \n", + "3034 42.25 21.667 2.805625 75.433 \n", + "3035 2.25 12.500 0.842724 76.542 \n", + "3036 4.00 5.000 7.409284 73.750 \n", + "3037 1.00 15.789 4.326400 66.158 \n", + "\n", + " AS_MeanAmphiMoment CLASS \n", + "0 0.282 1 \n", + "1 0.600 1 \n", + "2 0.593 1 \n", + "3 0.614 1 \n", + "4 0.616 1 \n", + "5 0.511 1 \n", + "6 0.385 1 \n", + "7 0.154 1 \n", + "8 0.188 1 \n", + "9 0.361 1 \n", + "10 0.510 1 \n", + "11 0.163 1 \n", + "12 0.263 1 \n", + "13 0.232 1 \n", + "14 0.402 1 \n", + "15 0.187 1 \n", + "16 0.536 1 \n", + "17 0.826 1 \n", + "18 1.100 1 \n", + "19 1.210 1 \n", + "20 1.304 1 \n", + "21 1.726 1 \n", + "22 1.717 1 \n", + "23 2.834 1 \n", + "24 2.980 1 \n", + "25 2.138 1 \n", + "26 2.435 1 \n", + "27 2.044 1 \n", + "28 2.704 1 \n", + "29 2.743 1 \n", + "... ... ... \n", + "3008 15.452 0 \n", + "3009 15.625 0 \n", + "3010 15.502 0 \n", + "3011 15.676 0 \n", + "3012 15.813 0 \n", + "3013 15.774 0 \n", + "3014 23.502 0 \n", + "3015 15.974 0 \n", + "3016 23.550 0 \n", + "3017 15.781 0 \n", + "3018 17.666 0 \n", + "3019 15.838 0 \n", + "3020 15.867 0 \n", + "3021 16.209 0 \n", + "3022 22.477 0 \n", + "3023 16.444 0 \n", + "3024 16.495 0 \n", + "3025 16.513 0 \n", + "3026 26.931 0 \n", + "3027 16.517 0 \n", + "3028 18.119 0 \n", + "3029 20.625 0 \n", + "3030 16.256 0 \n", + "3031 16.365 0 \n", + "3032 24.497 0 \n", + "3033 16.706 0 \n", + "3034 16.897 0 \n", + "3035 16.918 0 \n", + "3036 17.131 0 \n", + "3037 17.151 0 \n", + "\n", + "[3038 rows x 6 columns]\n" + ] + } + ], "source": [ "test_amp =amp_train.loc[:,['FULL_Charge', 'FULL_AcidicMolPerc',\"FULL_OOBM850104\",'FULL_DAYM780201', 'AS_MeanAmphiMoment','CLASS']]\n", "print(test_amp)\n" @@ -1535,7 +1916,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ @@ -1561,9 +1942,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 91.442% (1.795%)\n" + ] + } + ], "source": [ "\n", "X=test_amp.iloc[:,0:5]\n", @@ -1599,25 +1988,117 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 29, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "pandas.core.frame.DataFrame" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(test_data.loc[:,['FULL_Charge', 'FULL_AcidicMolPerc','FULL_DAYM780201', 'FULL_OOBM850104', 'AS_MeanAmphiMoment']])" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 91.44736842105263\n", + "[[273 31]\n", + " [ 21 283]]\n", + "MCC: 0.8293962196513646\n" + ] + }, + { + "data": { + "text/plain": [ + "array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 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LogisticRegression()\n", + "\n", "model.fit(X_train, Y_train)\n", + "\n", "predicted = model.predict(X_test)\n", + "\n", "matrix = confusion_matrix(Y_test, predicted)\n", + "\n", "result = model.score(X_test, Y_test)\n", "print(\"Accuracy: \", (result*100.0))\n", "print(matrix)\n", @@ -1625,7 +2106,7 @@ "#print(test_data)\n", "\n", "test_data2=test_data.loc[:,['FULL_Charge', 'FULL_AcidicMolPerc','FULL_DAYM780201', 'FULL_OOBM850104', 'AS_MeanAmphiMoment']]\n", - "test_data2=test_data2.values \n", + "#test_data2=test_data2.values \n", "#model1 = LogisticRegression() \n", "#model1.fit(X,Y)\n", "kj_results=model.predict(test_data2)\n", @@ -1663,9 +2144,74 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 26, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 91.69407894736842\n", + "[[586 29]\n", + " [ 72 529]]\n", + "MCC: 0.8358210636901913\n" + ] + }, + { + "data": { + "text/plain": [ + 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- "Y=test_amp.iloc[:,5]\n", + "X=test_amp[:,0:5]\n", + "Y=test_amp[:,5]\n", "model=GaussianNB() \n", "model.fit(X,Y)\n", "kj_results=model.predict(test_data2)\n", @@ -1701,9 +2248,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 31, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 90.948% (1.647%)\n" + ] + } + ], "source": [ "model=LinearDiscriminantAnalysis()\n", "folds=10\n", @@ -1721,16 +2276,138 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 33, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 91.804% (1.970%)\n" + ] + } + ], "source": [ - "model=SVC()\n", + "model_sv=SVC()\n", "folds=10\n", "kfold = KFold(n_splits=folds, random_state=7, shuffle=True,)\n", "results = cross_val_score(model, X, Y, cv=kfold)\n", "print((\"Accuracy: %.3f%% (%.3f%%)\") % (results.mean()*100.0, results.std()*100.0))" ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "SVC(C=1.0, break_ties=False, cache_size=200, class_weight=None, coef0=0.0,\n", + " decision_function_shape='ovr', degree=3, gamma='scale', kernel='rbf',\n", + " max_iter=-1, probability=False, random_state=None, shrinking=True,\n", + " tol=0.001, verbose=False)" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model_sv.fit(X_train, Y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "((758, 5), (2430, 5))" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "test_data2.shape, X_train.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([1., 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1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.])" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model_sv.predict(test_data2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { From 28356e9079d58e96ca39c3bdaef3f45e8584031a Mon Sep 17 00:00:00 2001 From: Maria_Magdalene_Namaganda Date: Sat, 7 Mar 2020 19:49:00 +0300 Subject: [PATCH 06/29] Initial commit --- Current Platforms of AI and ML/.Rhistory | 0 ...rent AI Platforms and where to start.ipynb | 2 +- Thur 20 Feb/.ipynb_checkpoints/.Rhistory | 0 Thur 20 Feb/ACE_ClassML Pipeline.ipynb | 318 ++++++++++++++++-- Thur 20 Feb/untitled | 0 5 files changed, 298 insertions(+), 22 deletions(-) create mode 100644 Current Platforms of AI and ML/.Rhistory create mode 100644 Thur 20 Feb/.ipynb_checkpoints/.Rhistory create mode 100644 Thur 20 Feb/untitled diff --git a/Current Platforms of AI and ML/.Rhistory b/Current Platforms of AI and ML/.Rhistory new file mode 100644 index 0000000..e69de29 diff --git a/Current Platforms of AI and ML/Current AI Platforms and where to start.ipynb b/Current Platforms of AI and ML/Current AI Platforms and where to start.ipynb index a8ee5fe..9fab383 100644 --- a/Current Platforms of AI and ML/Current AI Platforms and where to start.ipynb +++ b/Current Platforms of AI and ML/Current AI Platforms and where to start.ipynb @@ -608,7 +608,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.7.3" }, "varInspector": { "cols": { diff --git a/Thur 20 Feb/.ipynb_checkpoints/.Rhistory b/Thur 20 Feb/.ipynb_checkpoints/.Rhistory new file mode 100644 index 0000000..e69de29 diff --git a/Thur 20 Feb/ACE_ClassML Pipeline.ipynb b/Thur 20 Feb/ACE_ClassML Pipeline.ipynb index 4103dff..a67d367 100644 --- a/Thur 20 Feb/ACE_ClassML Pipeline.ipynb +++ b/Thur 20 Feb/ACE_ClassML Pipeline.ipynb @@ -24,7 +24,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -40,26 +40,39 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Jason Brownlee Practice.ipynb \u001b[31mhousing.csv\u001b[m\u001b[m\r\n", - "\u001b[31mdiabetes.csv\u001b[m\u001b[m\r\n" + "'ACE_ClassML Pipeline.ipynb' diabetes.csv housing.csv untitled\n", + "total 1036\n", + "-rw-r--r-- 1 namaganda namaganda 984181 Feb 28 09:01 'ACE_ClassML Pipeline.ipynb'\n", + "-rwxr-xr-x 1 namaganda namaganda 23873 Feb 20 14:32 diabetes.csv\n", + "-rwxr-xr-x 1 namaganda namaganda 49082 Feb 20 14:32 housing.csv\n", + "-rw-r--r-- 1 namaganda namaganda 0 Feb 20 14:33 untitled\n", + "total 1040\n", + "-rw-r--r-- 1 namaganda namaganda 984181 Feb 28 09:01 'ACE_ClassML Pipeline.ipynb'\n", + "-rwxr-xr-x 1 namaganda namaganda 23873 Feb 20 14:32 diabetes.csv\n", + "-rwxr-xr-x 1 namaganda namaganda 49082 Feb 20 14:32 housing.csv\n", + "drwxr-xr-x 2 namaganda namaganda 4096 Mar 6 09:19 meeee\n", + "-rw-r--r-- 1 namaganda namaganda 0 Feb 20 14:33 untitled\n" ] } ], "source": [ "#lets' check which files we have in our folder\n", - "!ls" + "!ls\n", + "!ls -l\n", + "!mkdir meeee\n", + "!ls -l" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -175,7 +188,7 @@ "4 2.288 33 1 " ] }, - "execution_count": 3, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -186,6 +199,125 @@ "data.head(5)" ] }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]\n", + "[[0, 1, 4, 9, 16, 25, 36, 49, 64, 81], [0, 1, 8, 27, 64, 125, 216, 343, 512, 729]]\n", + "[[ 0 1 2]\n", + " [ 3 4 5]\n", + " [ 6 7 8]\n", + " [ 9 10 11]]\n", + " 0 1 2\n", + "0 0 1 2\n", + "1 3 4 5\n", + "2 6 7 8\n", + "3 9 10 11\n", + "[[ 0 1 2]\n", + " [ 3 4 5]\n", + " [ 6 7 8]\n", + " [ 9 10 11]]\n", + " 0 1 2\n", + "0 0 1 2\n", + "1 3 4 5\n", + "2 6 7 8\n", + "3 9 10 11\n", + "[[ 0 1 2]\n", + " [ 3 4 5]\n", + " [ 6 7 8]\n", + " [ 9 10 11]]\n", + " aria youu meh\n", + "0 0 1 2\n", + "1 3 4 5\n", + "2 6 7 8\n", + "3 9 10 11\n", + " 0 1 2\n", + "xx 0 1 2\n", + "yy 3 4 5\n", + "zz 6 7 8\n", + "3 9 10 11\n" + ] + } + ], + "source": [ + "arr = [x**2 for x in range(10)]\n", + "print(arr)\n", + "arr1 = [x**3 for x in range(10)]\n", + "\n", + "#print(arr, arr1)\n", + "\n", + "list = [arr, arr1]\n", + "\n", + "#print(arr1)\n", + "\n", + "print(list)\n", + "\n", + "arr3 = [x for x in range(12)]\n", + "\n", + "arr3 = np.array(arr3)\n", + "\n", + "arr3 = arr3.reshape(4,3)\n", + "print(arr3)\n", + "df = pd.DataFrame(arr3)\n", + "print(df)\n", + "\n", + "df.head()\n", + "\n", + "dff = arr3.reshape((4,3), order = 'C')\n", + "dfff = arr3.reshape((4,3), order = 'F')\n", + "# there are two types of reshaping, C is default and fills rows, F fills columns\n", + "print(dff)\n", + "print(df)\n", + "print(dff)\n", + "df\n", + "\n", + "dffff = df.rename(columns={0: \"aria\", 1: \"youu\", 2: \"meh\"})\n", + "print(dffff)\n", + "\n", + "\n", + "dffff.index\n", + "\n", + "type(dffff)\n", + "dffff.index\n", + "\n", + "dffff = df.rename(index={0: \"xx\", 1: \"yy\", 2: \"zz\"})\n", + "\n", + "print(dffff)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0\n", + "1\n", + "2\n", + "3\n", + "4\n", + "5\n", + "6\n", + "7\n", + "8\n", + "9\n" + ] + } + ], + "source": [ + "for x in range(10):\n", + " print(x)" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -201,7 +333,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -210,7 +342,7 @@ "(768, 9)" ] }, - "execution_count": 4, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -265,6 +397,35 @@ "data.dtypes" ] }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['Pregnancies', 'Glucose', 'BloodPressure', 'SkinThickness', 'Insulin',\n", + " 'BMI', 'DiabetesPedigreeFunction', 'Age', 'Outcome'],\n", + " dtype='object')" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data.columns" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, { "cell_type": "markdown", "metadata": {}, @@ -706,6 +867,16 @@ "data.corr(method='pearson')" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#if we have missing data, we can replace them with the median but not the average.\n", + "#because the median is one of those things that dont change." + ] + }, { "cell_type": "code", "execution_count": 9, @@ -993,6 +1164,88 @@ "plt.show()" ] }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0 4.997212\n", + "1 4.442651\n", + "2 5.209486\n", + "3 4.488636\n", + "4 4.919981\n", + "5 4.753590\n", + "6 4.356709\n", + "7 4.744932\n", + "8 5.283204\n", + "9 4.828314\n", + "10 4.700480\n", + "11 5.123964\n", + "12 4.934474\n", + "13 5.241747\n", + "14 5.111988\n", + "15 4.605170\n", + "16 4.770685\n", + "17 4.672829\n", + "18 4.634729\n", + "19 4.744932\n", + "20 4.836282\n", + "21 4.595120\n", + "22 5.278115\n", + "23 4.779123\n", + "24 4.962845\n", + "25 4.828314\n", + "26 4.990433\n", + "27 4.574711\n", + "28 4.976734\n", + "29 4.762174\n", + " ... \n", + "738 4.595120\n", + "739 4.624973\n", + "740 4.787492\n", + "741 4.624973\n", + "742 4.691348\n", + "743 4.941642\n", + "744 5.030438\n", + "745 4.605170\n", + "746 4.990433\n", + "747 4.394449\n", + "748 5.231109\n", + "749 5.087596\n", + "750 4.912655\n", + "751 4.795791\n", + "752 4.682131\n", + "753 5.198497\n", + "754 5.036953\n", + "755 4.852030\n", + "756 4.919981\n", + "757 4.812184\n", + "758 4.663439\n", + "759 5.247024\n", + "760 4.477337\n", + "761 5.135798\n", + "762 4.488636\n", + "763 4.615121\n", + "764 4.804021\n", + "765 4.795791\n", + "766 4.836282\n", + "767 4.532599\n", + "Name: Glucose, Length: 768, dtype: float64" + ] + }, + "execution_count": 55, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.log(data)\n", + "np.log((data['Glucose'])) #data['Glucose'] = np.log((data['Glucose'])) to correct the skewness of your data." + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -1013,6 +1266,13 @@ "in your data." ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, { "cell_type": "code", "execution_count": 16, @@ -1114,6 +1374,31 @@ "sns.pairplot(data)" ] }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "ename": "KeyError", + "evalue": "\"['Pregancies'] not in index\"", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Glucose'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'BMI'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'Pregancies'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhead\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 2932\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2933\u001b[0m indexer = self.loc._convert_to_indexer(key, axis=1,\n\u001b[0;32m-> 2934\u001b[0;31m raise_missing=True)\n\u001b[0m\u001b[1;32m 2935\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2936\u001b[0m \u001b[0;31m# take() does not accept boolean indexers\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_convert_to_indexer\u001b[0;34m(self, obj, axis, is_setter, raise_missing)\u001b[0m\n\u001b[1;32m 1352\u001b[0m kwargs = {'raise_missing': True if is_setter else\n\u001b[1;32m 1353\u001b[0m raise_missing}\n\u001b[0;32m-> 1354\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_listlike_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1355\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1356\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_get_listlike_indexer\u001b[0;34m(self, key, axis, raise_missing)\u001b[0m\n\u001b[1;32m 1159\u001b[0m self._validate_read_indexer(keyarr, indexer,\n\u001b[1;32m 1160\u001b[0m \u001b[0mo\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_axis_number\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1161\u001b[0;31m raise_missing=raise_missing)\n\u001b[0m\u001b[1;32m 1162\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1163\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_validate_read_indexer\u001b[0;34m(self, key, indexer, axis, raise_missing)\u001b[0m\n\u001b[1;32m 1250\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'loc'\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mraise_missing\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1251\u001b[0m \u001b[0mnot_found\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1252\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"{} not in index\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnot_found\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1253\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1254\u001b[0m \u001b[0;31m# we skip the warning on Categorical/Interval\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mKeyError\u001b[0m: \"['Pregancies'] not in index\"" + ] + } + ], + "source": [ + "data[['Glucose', 'BMI', 'Pregancies']].head(1)" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -2023,18 +2308,9 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[141 21]\n", - " [ 41 51]]\n" - ] - } - ], + "outputs": [], "source": [ "from sklearn.metrics import confusion_matrix\n", "\n", @@ -3812,7 +4088,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.7.3" }, "varInspector": { "cols": { diff --git a/Thur 20 Feb/untitled b/Thur 20 Feb/untitled new file mode 100644 index 0000000..e69de29 From e2b00632583acb25657bfe07f4e1623cac13a925 Mon Sep 17 00:00:00 2001 From: Maria_Magdalene_Namaganda Date: Sat, 7 Mar 2020 19:57:02 +0300 Subject: [PATCH 07/29] Added my first notebook --- Assignment Colab/MARIA MAGDALENE NAMAGANDA.ipynb | 1 + 1 file changed, 1 insertion(+) create mode 100644 Assignment Colab/MARIA MAGDALENE NAMAGANDA.ipynb diff --git a/Assignment Colab/MARIA MAGDALENE NAMAGANDA.ipynb b/Assignment Colab/MARIA MAGDALENE NAMAGANDA.ipynb new file mode 100644 index 0000000..2f53cab --- /dev/null +++ b/Assignment Colab/MARIA MAGDALENE NAMAGANDA.ipynb @@ -0,0 +1 @@ +{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n for filename in filenames:\n print(os.path.join(dirname, filename))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#import the necessary libraries you are going to use\nimport warnings\nwarnings.filterwarnings('ignore')\n\n# -----> Put your code here below:\n\n\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Working with AMP_Data_set\n## `Training and testing data in Machine Learning`\n"},{"metadata":{"_cell_guid":"","_uuid":"","trusted":true},"cell_type":"code","source":"#Load the datasets, there are two i.e the Train and Test datasets\n\nTrain = pd.read_csv(\"../input/amp-data-set/AMP_TrainSet.csv\")\nTest = pd.read_csv(\"../input/amp-data-set/Test.csv\")\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":">Getting to know more about the data"},{"metadata":{"trusted":true},"cell_type":"code","source":"#here, am trying to find the kind of data am dealing with.\nprint(type(Train))\nprint(type(Test))\nprint(Train.dtypes)\nprint(Test.dtypes)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# check the dimensions of your data\n# this retuns the number of rows and columns in the data\n\nTrain.shape, Test.shape\n\n#this helps to know how big the data is in terms of rows and columns.\n#it also informs one of which data is labeled","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> The data is pre-prepared so ill just continue to work with it, since the Train dataset is already labeled with a CLASS attribute."},{"metadata":{"trusted":true},"cell_type":"code","source":"#getting a description of the data\n#Train.describe, Test.describe\nTrain.describe()\nTest.describe()\n#description gives a summary of the data.","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#looking at the first 5 entries of my data\nTrain.head()\nTest.head()\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":">Looking at the skewness of the data"},{"metadata":{"trusted":true},"cell_type":"code","source":"#knowing data skewness allows one to perform data preparation and improve a model\nTrain.skew().plot(kind='bar')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> Data correlation."},{"metadata":{"trusted":true},"cell_type":"code","source":"#first ill review the pairwise correlation of the attributes.\nTrain.corr(method='pearson')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Reviewing inter-correlation of attributes using heatmap\n#graphical representation\nplt.figure(figsize=(6,6))\nsns.heatmap(Train.corr(method='pearson'))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Ill also check the correlation in regards to the 'CLASS' attribute\nTrain.corr(method='pearson')['CLASS']","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Train['CLASS'].value_counts","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#I need to know the distribution of the class attribute of my data.\nprint(Train.groupby('CLASS').size().plot(kind='bar'))\n#train.CLASS.value_counts().plot(kind='bar')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"\n### From the above bar graph, the Class distribution is even which means am dealing with balanced data."},{"metadata":{},"cell_type":"markdown","source":"# Feature selection \n## Using recursive feature elimination"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.feature_selection import RFE\nfrom sklearn.linear_model import LogisticRegression\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = LogisticRegression()\nrfe = RFE(model, 4)\nfit = rfe.fit(X, Y)\nprint(\"Num Features: \", fit.n_features_)\nprint(\"Selected Features:\", fit.support_)\nprint(\"Feature Ranking: \", fit.ranking_)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Calling out the column names so I can know which features am going to drop from RFE\nTrain.columns","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Using Feature importance"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.ensemble import ExtraTreesClassifier\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = ExtraTreesClassifier()\nmodel.fit(X, Y)\nprint(model.feature_importances_)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Am going to use 4 features and drop the rest"},{"metadata":{"trusted":true},"cell_type":"code","source":"# I will call the new Train data with selected features New_Train.\nTrain\nNew_Train = Train.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#dropping the same features in the test dataset\nNew_Test = Test.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#viewing tselected features\nNew_Train.columns","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Rescaling data"},{"metadata":{"trusted":true},"cell_type":"code","source":"from numpy import set_printoptions\nfrom sklearn.preprocessing import MinMaxScaler\narray = New_Train.values\n\n#seperating data into onput and output options\nX = array[:,0:4]\nY = array[:,4]\nscaler = MinMaxScaler(feature_range = (0,1))\nrescaledX = scaler.fit_transform(X)\n\n#summarising transformed data\nset_printoptions(precision = 3)\nprint(rescaledX[0:4,:])\n ","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Standardising data"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.preprocessing import StandardScaler\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Comparing models to use"},{"metadata":{"trusted":true},"cell_type":"code","source":"#comparing different models to from which ill choose.\nfrom matplotlib import pyplot\nfrom sklearn.model_selection import KFold\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.svm import SVC\n\n\n# load dataset\n\narray = New_Train.values\n\n#split the dataset \nX = array[:,0:4] #X = Train.drop(columns=['CLASS'])\nY = array[:,4] #Y = Train['CLASS']\n\n# prepare models and add them to a list\nmodels = []\nmodels.append(('LR', LogisticRegression()))\nmodels.append(('LDA', LinearDiscriminantAnalysis()))\nmodels.append(('KNN', KNeighborsClassifier()))\nmodels.append(('CART', DecisionTreeClassifier()))\nmodels.append(('NB', GaussianNB()))\nmodels.append(('SVM', SVC()))\n\n# evaluate each model in turn\nresults = []\nnames = []\n\nfor name, model in models:\n kfold = KFold(n_splits=40, random_state=10)\n cv_results = cross_val_score(model, X, Y, cv=kfold, scoring='accuracy')\n results.append(cv_results)\n names.append(name)\n msg = (name, cv_results.mean(), cv_results.std())\n print(msg)\n\n# boxplot algorithm comparison\nfig = pyplot.figure()\nfig.suptitle('Algorithm Comparison')\nax = fig.add_subplot(111)\npyplot.boxplot(results)\nax.set_xticklabels(names)\npyplot.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now slitting data\n#array = New_Train.values\nX = New_Train.values[:,0:4]\nY = New_Train.values[:,4]\nfrom sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size=0.2, random_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# also train and test the model on Matthews correlation coefficient.\nfrom sklearn.metrics import matthews_corrcoef\n\nGS = GaussianNB()\nGS.fit(X_Train,Y_Train)\npred = GS.predict(X_Test)\n\nprint(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now creating a model and training it\nmodel = LogisticRegression(solver='liblinear', C=0.05, multi_class='ovr', random_state=30)\nmodel.fit(X_Train, Y_Train)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2,\nrandom_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.metrics import matthews_corrcoef\n\nnv = GaussianNB()\nnv.fit(X_Train,Y_Train)\npred = nv.predict(X_Test)\n\nprint(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#model = DecisionTreeClassifier()\n\n#model.fit(X_train, y_train)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Test.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#we now need to predict on the test dataset\nmd = pd.DataFrame((New_Test.index,nv.predict(New_Test))).T\nmd = md.rename(columns={0:\"Index\",1:\"CLASS\"}).set_index('Index')\nmd.to_csv('maria.csv')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"import os\nos.listdir()\n!ls ../../kaggle/working/","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4} \ No newline at end of file From 9777ea06c3793d2f5c2ac4a79a5bde96b5cd9a44 Mon Sep 17 00:00:00 2001 From: Maria_Magdalene_Namaganda Date: Sat, 7 Mar 2020 19:58:17 +0300 Subject: [PATCH 08/29] Added my first notebook --- Assignment Colab/MARIA MAGDALENE NAMAGANDA.ipynb | 1 + 1 file changed, 1 insertion(+) create mode 100644 Assignment Colab/MARIA MAGDALENE NAMAGANDA.ipynb diff --git a/Assignment Colab/MARIA MAGDALENE NAMAGANDA.ipynb b/Assignment Colab/MARIA MAGDALENE NAMAGANDA.ipynb new file mode 100644 index 0000000..2f53cab --- /dev/null +++ b/Assignment Colab/MARIA MAGDALENE NAMAGANDA.ipynb @@ -0,0 +1 @@ +{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n for filename in filenames:\n print(os.path.join(dirname, filename))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#import the necessary libraries you are going to use\nimport warnings\nwarnings.filterwarnings('ignore')\n\n# -----> Put your code here below:\n\n\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Working with AMP_Data_set\n## `Training and testing data in Machine Learning`\n"},{"metadata":{"_cell_guid":"","_uuid":"","trusted":true},"cell_type":"code","source":"#Load the datasets, there are two i.e the Train and Test datasets\n\nTrain = pd.read_csv(\"../input/amp-data-set/AMP_TrainSet.csv\")\nTest = pd.read_csv(\"../input/amp-data-set/Test.csv\")\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":">Getting to know more about the data"},{"metadata":{"trusted":true},"cell_type":"code","source":"#here, am trying to find the kind of data am dealing with.\nprint(type(Train))\nprint(type(Test))\nprint(Train.dtypes)\nprint(Test.dtypes)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# check the dimensions of your data\n# this retuns the number of rows and columns in the data\n\nTrain.shape, Test.shape\n\n#this helps to know how big the data is in terms of rows and columns.\n#it also informs one of which data is labeled","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> The data is pre-prepared so ill just continue to work with it, since the Train dataset is already labeled with a CLASS attribute."},{"metadata":{"trusted":true},"cell_type":"code","source":"#getting a description of the data\n#Train.describe, Test.describe\nTrain.describe()\nTest.describe()\n#description gives a summary of the data.","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#looking at the first 5 entries of my data\nTrain.head()\nTest.head()\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":">Looking at the skewness of the data"},{"metadata":{"trusted":true},"cell_type":"code","source":"#knowing data skewness allows one to perform data preparation and improve a model\nTrain.skew().plot(kind='bar')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> Data correlation."},{"metadata":{"trusted":true},"cell_type":"code","source":"#first ill review the pairwise correlation of the attributes.\nTrain.corr(method='pearson')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Reviewing inter-correlation of attributes using heatmap\n#graphical representation\nplt.figure(figsize=(6,6))\nsns.heatmap(Train.corr(method='pearson'))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Ill also check the correlation in regards to the 'CLASS' attribute\nTrain.corr(method='pearson')['CLASS']","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Train['CLASS'].value_counts","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#I need to know the distribution of the class attribute of my data.\nprint(Train.groupby('CLASS').size().plot(kind='bar'))\n#train.CLASS.value_counts().plot(kind='bar')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"\n### From the above bar graph, the Class distribution is even which means am dealing with balanced data."},{"metadata":{},"cell_type":"markdown","source":"# Feature selection \n## Using recursive feature elimination"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.feature_selection import RFE\nfrom sklearn.linear_model import LogisticRegression\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = LogisticRegression()\nrfe = RFE(model, 4)\nfit = rfe.fit(X, Y)\nprint(\"Num Features: \", fit.n_features_)\nprint(\"Selected Features:\", fit.support_)\nprint(\"Feature Ranking: \", fit.ranking_)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Calling out the column names so I can know which features am going to drop from RFE\nTrain.columns","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Using Feature importance"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.ensemble import ExtraTreesClassifier\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = ExtraTreesClassifier()\nmodel.fit(X, Y)\nprint(model.feature_importances_)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Am going to use 4 features and drop the rest"},{"metadata":{"trusted":true},"cell_type":"code","source":"# I will call the new Train data with selected features New_Train.\nTrain\nNew_Train = Train.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#dropping the same features in the test dataset\nNew_Test = Test.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#viewing tselected features\nNew_Train.columns","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Rescaling data"},{"metadata":{"trusted":true},"cell_type":"code","source":"from numpy import set_printoptions\nfrom sklearn.preprocessing import MinMaxScaler\narray = New_Train.values\n\n#seperating data into onput and output options\nX = array[:,0:4]\nY = array[:,4]\nscaler = MinMaxScaler(feature_range = (0,1))\nrescaledX = scaler.fit_transform(X)\n\n#summarising transformed data\nset_printoptions(precision = 3)\nprint(rescaledX[0:4,:])\n ","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Standardising data"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.preprocessing import StandardScaler\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Comparing models to use"},{"metadata":{"trusted":true},"cell_type":"code","source":"#comparing different models to from which ill choose.\nfrom matplotlib import pyplot\nfrom sklearn.model_selection import KFold\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.svm import SVC\n\n\n# load dataset\n\narray = New_Train.values\n\n#split the dataset \nX = array[:,0:4] #X = Train.drop(columns=['CLASS'])\nY = array[:,4] #Y = Train['CLASS']\n\n# prepare models and add them to a list\nmodels = []\nmodels.append(('LR', LogisticRegression()))\nmodels.append(('LDA', LinearDiscriminantAnalysis()))\nmodels.append(('KNN', KNeighborsClassifier()))\nmodels.append(('CART', DecisionTreeClassifier()))\nmodels.append(('NB', GaussianNB()))\nmodels.append(('SVM', SVC()))\n\n# evaluate each model in turn\nresults = []\nnames = []\n\nfor name, model in models:\n kfold = KFold(n_splits=40, random_state=10)\n cv_results = cross_val_score(model, X, Y, cv=kfold, scoring='accuracy')\n results.append(cv_results)\n names.append(name)\n msg = (name, cv_results.mean(), cv_results.std())\n print(msg)\n\n# boxplot algorithm comparison\nfig = pyplot.figure()\nfig.suptitle('Algorithm Comparison')\nax = fig.add_subplot(111)\npyplot.boxplot(results)\nax.set_xticklabels(names)\npyplot.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now slitting data\n#array = New_Train.values\nX = New_Train.values[:,0:4]\nY = New_Train.values[:,4]\nfrom sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size=0.2, random_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# also train and test the model on Matthews correlation coefficient.\nfrom sklearn.metrics import matthews_corrcoef\n\nGS = GaussianNB()\nGS.fit(X_Train,Y_Train)\npred = GS.predict(X_Test)\n\nprint(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now creating a model and training it\nmodel = LogisticRegression(solver='liblinear', C=0.05, multi_class='ovr', random_state=30)\nmodel.fit(X_Train, Y_Train)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2,\nrandom_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.metrics import matthews_corrcoef\n\nnv = GaussianNB()\nnv.fit(X_Train,Y_Train)\npred = nv.predict(X_Test)\n\nprint(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#model = DecisionTreeClassifier()\n\n#model.fit(X_train, y_train)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Test.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#we now need to predict on the test dataset\nmd = pd.DataFrame((New_Test.index,nv.predict(New_Test))).T\nmd = md.rename(columns={0:\"Index\",1:\"CLASS\"}).set_index('Index')\nmd.to_csv('maria.csv')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"import os\nos.listdir()\n!ls ../../kaggle/working/","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4} \ No newline at end of file From 785f8e9f7199fa9b17d8843a98ae423df39b792b Mon Sep 17 00:00:00 2001 From: Agasi Herbert Date: Mon, 9 Mar 2020 11:09:37 -0400 Subject: [PATCH 09/29] Updated Notebook --- Assignment Colab/Agasi_Update.ipynb | 1 + 1 file changed, 1 insertion(+) create mode 100644 Assignment Colab/Agasi_Update.ipynb diff --git a/Assignment Colab/Agasi_Update.ipynb b/Assignment Colab/Agasi_Update.ipynb new file mode 100644 index 0000000..a0c7b44 --- /dev/null +++ b/Assignment Colab/Agasi_Update.ipynb @@ -0,0 +1 @@ +{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\n# DATA VISUALIZATION\nimport matplotlib.pyplot as plt\nimport matplotlib.gridspec as gridspec\nimport seaborn as sns\n\n#scikit learn libraries\n#Lineaer Models\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.neural_network import MLPClassifier\nfrom sklearn.linear_model import SGDClassifier\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n\n\nfrom sklearn.svm import SVC\nfrom sklearn.naive_bayes import GaussianNB\n# Tree\nfrom sklearn.tree import DecisionTreeClassifier\n\n# sklearn libraries\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn.model_selection import train_test_split,KFold,cross_val_score\nfrom sklearn.preprocessing import normalize\nfrom sklearn.metrics import confusion_matrix,accuracy_score,precision_score,recall_score,f1_score,matthews_corrcoef,classification_report,roc_curve\nfrom sklearn.externals import joblib\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.decomposition import PCA\n\n#let's remove the annoying warnings from our cells.\nimport warnings\nwarnings.filterwarnings('ignore')\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n for filename in filenames:\n print(os.path.join(dirname, filename))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"## Loading the datasets\n\nTrain = pd.read_csv(\"../input/ace-class-assignment/AMP_TrainSet.csv\")\nTest = pd.read_csv(\"../input/ace-class-assignment/Test.csv\")\n\n## Taking a preview of the data\nTrain.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"## Loking at the dimensions of the dataset\n\nTrain.shape,Test.shape","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"## Looking for misssing and null values\nTrain.isnull().any().sum()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"## Looking the data types of the data\nTrain.dtypes","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"## Looking at the description of the data \nTrain.describe()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Looking at the data:\n* There are two categorical features CLASS and NT_EFC195\n* There is a big difference between the 75th percentile and the maximum values for columns FULL_Charge and FULL_AcidicMolPerc\n* The columns FULL_AcidicMolPerc and FULL_OOBM850104 have both negative and positive values."},{"metadata":{"trusted":true},"cell_type":"code","source":"# Looking at the ratio of the binary data for the class\n\nAll = Train.shape[0]\nPositive = Train[Train['CLASS'] == 1]\nNegative = Train[Train['CLASS'] == 0]\n\nx = len(Positive)/All\ny = len(Negative)/All\n\nprint('Positives :',x*100,'%')\nprint('Negatives :',y*100,'%')\n\n## The sets are evenly balanced and hence there will be no need to use SMOTE OR NEAR MISS","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Visualizing the data class\nlabels = ['Negatives','Positives']\nclasses = pd.value_counts(Train['CLASS'], sort = True)\nclasses.plot(kind = 'bar', rot=0)\nplt.title(\"Visualizing the data class\")\nplt.xticks(range(2), labels)\nplt.xlabel(\"Class\")\nplt.ylabel(\"Frequency\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Plot the distribution of features"},{"metadata":{"trusted":true},"cell_type":"code","source":"# distribution of features\n# This feature works with numerical data not categorical data.\nfeatures =Train.drop([\"CLASS\",\"NT_EFC195\"],axis=1).columns\n\nplt.figure(figsize=(12,12*4))\ngs = gridspec.GridSpec(12, 1)\nfor i, cn in enumerate(Train[features]):\n ax = plt.subplot(gs[i])\n sns.distplot(Train[cn][Train.CLASS == 1], bins=50)\n sns.distplot(Train[cn][Train.CLASS == 0], bins=50)\n ax.set_xlabel('')\n ax.set_title('histogram of feature: ' + str(cn))\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# PCA (Principal Component Analysis) mainly using to reduce the size of the feature space while\n# retaining as much of the information as possible.\n# In here all the features transformed into 2 features using PCA.\n\nX = Train.drop(['CLASS'], axis = 1)\ny = Train['CLASS']\n\npca = PCA(n_components=2)\nprincipalComponents = pca.fit_transform(X.values)\nprincipalDf = pd.DataFrame(data = principalComponents\n , columns = ['principal component 1', 'principal component 2'])\nFTrain = pd.concat([principalDf, y], axis = 1)\nFTrain.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# 2D visualization\nfig = plt.figure(figsize = (8,8))\nax = fig.add_subplot(1,1,1) \nax.set_xlabel('Principal Component 1', fontsize = 15)\nax.set_ylabel('Principal Component 2', fontsize = 15)\nax.set_title('2 component PCA', fontsize = 20)\ntargets = [0, 1]\ncolors = ['r', 'g']\nfor target, color in zip(targets,colors):\n indicesToKeep = FTrain['CLASS'] == target\n ax.scatter(FTrain.loc[indicesToKeep, 'principal component 1']\n , FTrain.loc[indicesToKeep, 'principal component 2']\n , c = color\n , s = 50)\nax.legend(targets)\nax.grid()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"\n# Data splitting\n\n# splitting the faeture array and label array keeping 80% for the trainnig sets\nX_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.20)\n\n# normalize: Scale input vectors individually to unit norm (vector length).\nX_train = normalize(X_train)\nX_test=normalize(X_test)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Spot-Check Algorithms\n\nmodels = []\nmodels.append(('LR', LogisticRegression()))\nmodels.append(('LDA', LinearDiscriminantAnalysis()))\nmodels.append(('KNN', KNeighborsClassifier()))\nmodels.append(('CART', DecisionTreeClassifier()))\nmodels.append(('NB', GaussianNB()))\nmodels.append(('SVM', SVC()))\nmodels.append(('NN',MLPClassifier()))\nmodels.append(('SG',SGDClassifier()))\n\n# evaluate each model in turn\n\nresults = []\nnames = []\nseed =25\nfor name, model in models:\n kfold = KFold(n_splits=10, random_state=seed,shuffle=True)\n cv_results = cross_val_score(model, X_train, y_train, cv=kfold, \n scoring='accuracy')\n results.append(cv_results)\n names.append(name)\n print(\"%s: %f (%f)\" % (name, cv_results.mean(), cv_results.std()))\n#print(msg)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"\n# Model Evaluation\n"},{"metadata":{"trusted":true},"cell_type":"code","source":"\n#scoring knn\nknn_accuracy_score = accuracy_score(y_test,knn_predicted_test_labels)\nknn_precison_score = precision_score(y_test,knn_predicted_test_labels)\nknn_recall_score = recall_score(y_test,knn_predicted_test_labels)\nknn_f1_score = f1_score(y_test,knn_predicted_test_labels)\nknn_MCC = matthews_corrcoef(y_test,knn_predicted_test_labels)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"for n in results:\n print(n)\n#names['LR'].predict(X_test)","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4} \ No newline at end of file From b6ce652843c48a83439deb918f11f9071fd275f9 Mon Sep 17 00:00:00 2001 From: Maria_Magdalene_Namaganda Date: Tue, 10 Mar 2020 16:48:10 +0300 Subject: [PATCH 10/29] commit_message --- Assignment Colab/MARIA MAGDALENE NAMAGANDA (1).ipynb | 1 + 1 file changed, 1 insertion(+) create mode 100644 Assignment Colab/MARIA MAGDALENE NAMAGANDA (1).ipynb diff --git a/Assignment Colab/MARIA MAGDALENE NAMAGANDA (1).ipynb b/Assignment Colab/MARIA MAGDALENE NAMAGANDA (1).ipynb new file mode 100644 index 0000000..1a8c68c --- /dev/null +++ b/Assignment Colab/MARIA MAGDALENE NAMAGANDA (1).ipynb @@ -0,0 +1 @@ +{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n for filename in filenames:\n print(os.path.join(dirname, filename))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# MARIA MAGDALENE NAMAGANDA\n# 2019/HD07/24853U\n# Kaggle assignment"},{"metadata":{},"cell_type":"markdown","source":"## Importing some of the needed packages and libraries"},{"metadata":{"trusted":true},"cell_type":"code","source":"import pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib import pyplot\nimport seaborn as sns\nfrom sklearn.metrics import classification_report\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis\nfrom sklearn.svm import SVC\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis\nfrom sklearn.metrics import confusion_matrix\nfrom sklearn.model_selection import KFold\nfrom sklearn.model_selection import train_test_split\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> Now i need to get rid of some unecessary warnings "},{"metadata":{"trusted":true},"cell_type":"code","source":"#To avoid unnecessary warnings, I will ignore them in the code below\nimport warnings\nwarnings.filterwarnings('ignore')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Loading the datasets to be used\n> There are two datasets, the train and test datasets "},{"metadata":{"_cell_guid":"","_uuid":"","trusted":true},"cell_type":"code","source":"#Loading the datasets, \n\nTrain = pd.read_csv(\"../input/amp-data-set/AMP_TrainSet.csv\")\nTest = pd.read_csv(\"../input/amp-data-set/Test.csv\")\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Exploring my data\n## Trying to know more about the data am dealing with"},{"metadata":{"trusted":true},"cell_type":"code","source":"#here, am trying to find the type of data\ntype(Train)\ntype(Test)\nTrain.dtypes\n#Test.dtypes","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# checking the dimensions of the data\n# this retuns the number of rows and columns in the data\n\nTrain.shape, Test.shape\n\n#this helps to know how big the data is in terms of rows and columns.\n#it also informs one of which data is labeled","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Data description\n>for now, I will focus more on the train dataset because its what I will use to train the model "},{"metadata":{"trusted":true},"cell_type":"code","source":"#getting a description of the data\n\nTrain.describe()\n\n#description gives a summary of the data.","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#looking at the first 5 entries of my data\nTrain.head()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> *From the Train dataset, i see there is an extra class column which will be my validation set*"},{"metadata":{},"cell_type":"markdown","source":"## Class Distribution"},{"metadata":{"trusted":true},"cell_type":"code","source":"Train.groupby('CLASS').size().plot(kind='bar')\npyplot.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> From the above barplot, I can see that the classes are evenly distributed so no need to use smote"},{"metadata":{},"cell_type":"markdown","source":"> I would like to know how many instaces i have for each class"},{"metadata":{"trusted":true},"cell_type":"code","source":"#getting the number of instances in each class\nTrain.groupby('CLASS').size()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Data Visualisation"},{"metadata":{},"cell_type":"markdown","source":"## Looking at the correlation of the data"},{"metadata":{"trusted":true},"cell_type":"code","source":"#first ill checkfor the pairwise correlation of the attributes.\nTrain.corr(method='pearson')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Reviewing inter-correlation of attributes using heatmap\n#graphical representation\nplt.figure(figsize=(6,6))\nsns.heatmap(Train.corr(method='pearson'))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Ill also check the correlation in regards to the 'CLASS' attribute\nTrain.corr(method='pearson')['CLASS']","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Train['CLASS'].value_counts","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Skewnwess of the data\n> knowing data skewness allows one to perform data preparation and improve a model"},{"metadata":{"trusted":true},"cell_type":"code","source":"Train.skew().plot(kind='bar')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Comparing Models"},{"metadata":{"trusted":true},"cell_type":"code","source":"#comparing different models to from which ill choose.\n\n\n# load dataset\n\narray = Train.values\n\n#split the dataset \nX = array[:,0:11] #X = Train.drop(columns=['CLASS'])\nY = array[:,11] #Y = Train['CLASS']\n\n# prepare models and add them to a list\nmodels = []\nmodels.append(('LR', LogisticRegression()))\nmodels.append(('LDA', LinearDiscriminantAnalysis()))\nmodels.append(('KNN', KNeighborsClassifier()))\nmodels.append(('CART', DecisionTreeClassifier()))\nmodels.append(('NB', GaussianNB()))\nmodels.append(('SVM', SVC()))\n\n# evaluate each model in turn\nresults = []\nnames = []\n\nfor name, model in models:\n kfold = KFold(n_splits=40, random_state=10)\n cv_results = cross_val_score(model, X, Y, cv=kfold, scoring='accuracy')\n results.append(cv_results)\n names.append(name)\n msg = (name, cv_results.mean(), cv_results.std())\n print(msg)\n\n# boxplot algorithm comparison\nfig = pyplot.figure()\nfig.suptitle('Algorithm Comparison')\nax = fig.add_subplot(111)\npyplot.boxplot(results)\nax.set_xticklabels(names)\npyplot.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Feature selection \n## Using recursive feature elimination"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.feature_selection import RFE\nfrom sklearn.linear_model import LogisticRegression\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = LogisticRegression()\nrfe = RFE(model, 4)\nfit = rfe.fit(X, Y)\nprint(\"Num Features: \", fit.n_features_)\nprint(\"Selected Features:\", fit.support_)\nprint(\"Feature Ranking: \", fit.ranking_)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Calling out the column names so I can know which features am going to drop from RFE\nTrain.columns","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Using Feature importance"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.ensemble import ExtraTreesClassifier\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = ExtraTreesClassifier()\nmodel.fit(X, Y)\nprint(model.feature_importances_)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## If am to use 4 features and drop the rest"},{"metadata":{"trusted":true},"cell_type":"code","source":"# I will call the new Train data with selected features New_Train.\nTrain\nNew_Train4 = Train.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#dropping the same features in the test dataset\nNew_Test4 = Test.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#viewing tselected features\nNew_Train4.columns","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Rescaling data"},{"metadata":{"trusted":true},"cell_type":"code","source":"from numpy import set_printoptions\nfrom sklearn.preprocessing import MinMaxScaler\narray = New_Train4.values\n\n#seperating data into onput and output options\nX = array[:,0:4]\nY = array[:,4]\nscaler = MinMaxScaler(feature_range = (0,1))\nrescaledX = scaler.fit_transform(X)\n\n#summarising transformed data\nset_printoptions(precision = 3)\nprint(rescaledX[0:4,:])\n ","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Standardising data"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.preprocessing import StandardScaler\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now splitting data\n#array = New_Train.values\nX = New_Train4.values[:,0:4]\nY = New_Train4.values[:,4]\nfrom sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size=0.2, random_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# also train and test the model on Matthews correlation coefficient.\nfrom sklearn.metrics import matthews_corrcoef\n\nGS = GaussianNB()\nGS.fit(X_Train,Y_Train)\npred = GS.predict(X_Test)\n\nprint(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Using four features gives me a very low MCC and low overall score.\n## I'll therefore consider using 8 features and see what score get"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.feature_selection import RFE\nfrom sklearn.linear_model import LogisticRegression\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = LogisticRegression()\nrfe = RFE(model, 8)\nfit = rfe.fit(X, Y)\nprint(\"Num Features: \", fit.n_features_)\nprint(\"Selected Features:\", fit.support_)\nprint(\"Feature Ranking: \", fit.ranking_)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# I will call the new Train data with selected features New_Train.\nTrain\nNew_Train8 = Train.drop(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'AS_DAYM780201'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#dropping the same features in the test dataset\nNew_Test8 = Test.drop(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'AS_DAYM780201'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now splitting data\n#array = New_Train.values\n\n\nX = New_Train8.values[:,0:8]\nY = New_Train8.values[:,8]\nfrom sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size=0.2, random_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now creating a model and training it on 8 features\nmodel = LogisticRegression(solver='liblinear', C=0.05, multi_class='ovr', random_state=30)\nmodel.fit(X_Train, Y_Train)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2,\nrandom_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.metrics import matthews_corrcoef\n\nnv = GaussianNB()\nnv.fit(X_Train,Y_Train)\npred = nv.predict(X_Test)\n\nprint(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Logistic Regression using 8 features"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = New_Train8.values\nX = array[:,0:8]\nY = array[:,8]\ntest_size = 0.30\nseed = 7\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\nrandom_state=seed)\nmodel = LogisticRegression()\nmodel.fit(X_train, Y_train)\nresult = model.score(X_test, Y_test)\nprint(\"Accuracy: \", (result*100.0))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Test.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#we now need to predict on the test dataset\n#md = pd.DataFrame((New_Test.index,nv.predict(New_Test))).T\n#md = md.rename(columns={0:\"Index\",1:\"CLASS\"}).set_index('Index')\n#md.to_csv('maria.csv')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#we now need to predict on the test dataset\nmd = pd.DataFrame((New_Test8.index,nv.predict(New_Test8))).T\nmd = md.rename(columns={0:\"Index\",1:\"CLASS\"}).set_index('Index')\nmd.to_csv('maria1.csv')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"import os\nos.listdir()\n!ls ../../kaggle/working/","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Using Naive Bayes and all the features"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\ntest_size = 0.35\nseed = 3\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\nrandom_state=seed)\nmodel = GaussianNB()\nmodel.fit(X_train, Y_train)\nresult = model.score(X_test, Y_test)\nprediction=model.predict(X_test)\nmatrix=matthews_corrcoef(Y_test,prediction)\nprint(\"Accuracy: \", (result*100.0))\nprint(matrix)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\nkfold = KFold(n_splits=10, random_state=7)\nmodel = GaussianNB()\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())\n\n\nmodel.fit(X,Y)\noutput = model.predict(Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria2_bayes = pd.DataFrame(output)\nmaria2_bayes.columns = ['CLASS']\nmaria2_bayes.index.name = \"Index\"\nmaria2_bayes['CLASS']=maria2_bayes['CLASS'].map({0.0:False, 1.0:True})\nmaria2_bayes.to_csv(\"maria2_bayes.csv\")\n\n\nprint(maria2_bayes['CLASS'].unique())\nprint('False: ',maria2_bayes.groupby('CLASS').size()[0].sum())\nprint('True: ',maria2_bayes.groupby('CLASS').size()[1].sum())","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4} \ No newline at end of file From 325913a92223979986b9d8ccf0dd94709457e64a Mon Sep 17 00:00:00 2001 From: Atwine Date: Tue, 10 Mar 2020 17:08:00 +0300 Subject: [PATCH 11/29] Make corrections --- ...MARIA MAGDALENE NAMAGANDA-checkpoint.ipynb | 1769 ++++++++++++++++ .../MARIA MAGDALENE NAMAGANDA.ipynb | 1770 ++++++++++++++++- Assignment Colab/maria.csv | 759 +++++++ .../Pandas Cookbook/Pandas-Cookbook | 1 + Thur 20 Feb/ACE_ClassML Pipeline.ipynb | 36 +- 5 files changed, 4312 insertions(+), 23 deletions(-) create mode 100644 Assignment Colab/.ipynb_checkpoints/MARIA MAGDALENE NAMAGANDA-checkpoint.ipynb create mode 100644 Assignment Colab/maria.csv create mode 160000 Reading Material/Pandas Cookbook/Pandas-Cookbook diff --git a/Assignment Colab/.ipynb_checkpoints/MARIA MAGDALENE NAMAGANDA-checkpoint.ipynb b/Assignment Colab/.ipynb_checkpoints/MARIA MAGDALENE NAMAGANDA-checkpoint.ipynb new file mode 100644 index 0000000..8155bd1 --- /dev/null +++ b/Assignment Colab/.ipynb_checkpoints/MARIA MAGDALENE NAMAGANDA-checkpoint.ipynb @@ -0,0 +1,1769 @@ +{ + "cells": [ + { + "cell_type": "raw", + "metadata": { + "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", + "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" + }, + "source": [ + "# This Python 3 environment comes with many helpful analytics libraries installed\n", + "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", + "# For example, here's several helpful packages to load in \n", + "\n", + "import numpy as np # linear algebra\n", + "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", + "\n", + "# Input data files are available in the \"../input/\" directory.\n", + "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", + "\n", + "import os\n", + "for dirname, _, filenames in os.walk('/kaggle/input'):\n", + " for filename in filenames:\n", + " print(os.path.join(dirname, filename))\n", + "\n", + "# Any results you write to the current directory are saved as output." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "#import the necessary libraries you are going to use\n", + "import warnings\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "# -----> Put your code here below:\n", + "\n", + "\n", + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Working with AMP_Data_set\n", + "## `Training and testing data in Machine Learning`\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "_cell_guid": "", + "_uuid": "" + }, + "outputs": [], + "source": [ + "#Load the datasets, there are two i.e the Train and Test datasets\n", + "\n", + "Train = pd.read_csv(\"../AMP Data Sets/AMP_TrainSet.csv\")\n", + "Test = pd.read_csv(\"../AMP Data Sets/Test.csv\")\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + ">Getting to know more about the data\n", + "\n", + "
(Atwine)\n", + "\n", + "When you run the code below, what did you learn?\n", + "\n", + "Please document those findings.
" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n", + "FULL_Charge float64\n", + "FULL_AcidicMolPerc float64\n", + "FULL_AURR980107 float64\n", + "FULL_DAYM780201 float64\n", + "FULL_GEOR030101 float64\n", + "FULL_OOBM850104 float64\n", + "NT_EFC195 int64\n", + "AS_MeanAmphiMoment float64\n", + "AS_DAYM780201 float64\n", + "AS_FUKS010112 float64\n", + "CT_RACS820104 float64\n", + "CLASS int64\n", + "dtype: object\n", + "FULL_Charge float64\n", + "FULL_AcidicMolPerc float64\n", + "FULL_AURR980107 float64\n", + "FULL_DAYM780201 float64\n", + "FULL_GEOR030101 float64\n", + "FULL_OOBM850104 float64\n", + "NT_EFC195 int64\n", + "AS_MeanAmphiMoment float64\n", + "AS_DAYM780201 float64\n", + "AS_FUKS010112 float64\n", + "CT_RACS820104 float64\n", + "dtype: object\n" + ] + } + ], + "source": [ + "#here, am trying to find the kind of data am dealing with.\n", + "print(type(Train))\n", + "print(type(Test))\n", + "print(Train.dtypes)\n", + "print(Test.dtypes)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "((3038, 12), (758, 11))" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# check the dimensions of your data\n", + "# this retuns the number of rows and columns in the data\n", + "\n", + "Train.shape, Test.shape\n", + "\n", + "#this helps to know how big the data is in terms of rows and columns.\n", + "#it also informs one of which data is labeled" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> The data is pre-prepared so ill just continue to work with it, since the Train dataset is already labeled with a CLASS attribute.\n", + "\n", + "
\n", + " This is a good note\n", + "

Please highlight what you learnt from the describe function below, what does it tell you? \n", + " What did you notice from the data? Is it perfect?\n", + "

\n", + "

Or there are some things that bug you but you are deciding to leave them a lone for some reason?

\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n", + "0 4.0 3.704 0.873 73.519 \n", + "1 4.0 4.444 0.892 62.444 \n", + "2 2.0 0.000 0.901 47.000 \n", + "3 4.5 0.000 0.869 69.222 \n", + "4 -4.0 21.591 1.061 71.682 \n", + "\n", + " FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n", + "0 0.987 -4.833 0 0.382 \n", + "1 0.931 -0.584 0 0.320 \n", + "2 1.039 -5.664 0 0.164 \n", + "3 0.982 -5.423 0 2.010 \n", + "4 0.976 -2.002 0 2.758 \n", + "\n", + " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 \n", + "0 74.556 7.225 1.234 \n", + "1 56.056 4.942 1.853 \n", + "2 47.000 5.969 1.174 \n", + "3 69.222 5.462 1.138 \n", + "4 66.000 5.582 1.453 " + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#looking at the first 5 entries of my data\n", + "Train.head()\n", + "Test.head()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + ">Looking at the skewness of the data\n", + "\n", + "
\n", + " What did you learn?\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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FULL_OOBM850104-0.2837580.5133440.4627120.3347780.3191571.000000-0.230561-0.3362970.275640-0.4527690.155304-0.453287
NT_EFC1950.088068-0.143168-0.169540-0.090058-0.230417-0.2305611.0000000.178683-0.0368440.1459240.0808980.260702
AS_MeanAmphiMoment0.355477-0.431590-0.426097-0.408793-0.160269-0.3362970.1786831.000000-0.3223780.0255800.1715240.693552
AS_DAYM780201-0.3653740.4496210.4562600.894191-0.0290850.275640-0.036844-0.3223781.0000000.045562-0.256060-0.437168
AS_FUKS010112-0.0905700.0023340.0329580.0559150.040480-0.4527690.1459240.0255800.0455621.000000-0.4452840.033432
CT_RACS8201040.232929-0.213543-0.403599-0.326792-0.1519350.1553040.0808980.171524-0.256060-0.4452841.0000000.267652
CLASS0.534602-0.598816-0.584111-0.554838-0.260470-0.4532870.2607020.693552-0.4371680.0334320.2676521.000000
\n", + "
" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 \\\n", + "FULL_Charge 1.000000 -0.612996 -0.490977 \n", + "FULL_AcidicMolPerc -0.612996 1.000000 0.794796 \n", + "FULL_AURR980107 -0.490977 0.794796 1.000000 \n", + "FULL_DAYM780201 -0.434603 0.541481 0.548253 \n", + "FULL_GEOR030101 -0.058725 0.115201 0.346139 \n", + "FULL_OOBM850104 -0.283758 0.513344 0.462712 \n", + "NT_EFC195 0.088068 -0.143168 -0.169540 \n", + "AS_MeanAmphiMoment 0.355477 -0.431590 -0.426097 \n", + "AS_DAYM780201 -0.365374 0.449621 0.456260 \n", + "AS_FUKS010112 -0.090570 0.002334 0.032958 \n", + "CT_RACS820104 0.232929 -0.213543 -0.403599 \n", + "CLASS 0.534602 -0.598816 -0.584111 \n", + "\n", + " FULL_DAYM780201 FULL_GEOR030101 FULL_OOBM850104 \\\n", + "FULL_Charge -0.434603 -0.058725 -0.283758 \n", + "FULL_AcidicMolPerc 0.541481 0.115201 0.513344 \n", + "FULL_AURR980107 0.548253 0.346139 0.462712 \n", + "FULL_DAYM780201 1.000000 0.010118 0.334778 \n", + "FULL_GEOR030101 0.010118 1.000000 0.319157 \n", + "FULL_OOBM850104 0.334778 0.319157 1.000000 \n", + "NT_EFC195 -0.090058 -0.230417 -0.230561 \n", + "AS_MeanAmphiMoment -0.408793 -0.160269 -0.336297 \n", + "AS_DAYM780201 0.894191 -0.029085 0.275640 \n", + "AS_FUKS010112 0.055915 0.040480 -0.452769 \n", + "CT_RACS820104 -0.326792 -0.151935 0.155304 \n", + "CLASS -0.554838 -0.260470 -0.453287 \n", + "\n", + " NT_EFC195 AS_MeanAmphiMoment AS_DAYM780201 \\\n", + "FULL_Charge 0.088068 0.355477 -0.365374 \n", + "FULL_AcidicMolPerc -0.143168 -0.431590 0.449621 \n", + "FULL_AURR980107 -0.169540 -0.426097 0.456260 \n", + "FULL_DAYM780201 -0.090058 -0.408793 0.894191 \n", + "FULL_GEOR030101 -0.230417 -0.160269 -0.029085 \n", + "FULL_OOBM850104 -0.230561 -0.336297 0.275640 \n", + "NT_EFC195 1.000000 0.178683 -0.036844 \n", + "AS_MeanAmphiMoment 0.178683 1.000000 -0.322378 \n", + "AS_DAYM780201 -0.036844 -0.322378 1.000000 \n", + "AS_FUKS010112 0.145924 0.025580 0.045562 \n", + "CT_RACS820104 0.080898 0.171524 -0.256060 \n", + "CLASS 0.260702 0.693552 -0.437168 \n", + "\n", + " AS_FUKS010112 CT_RACS820104 CLASS \n", + "FULL_Charge -0.090570 0.232929 0.534602 \n", + "FULL_AcidicMolPerc 0.002334 -0.213543 -0.598816 \n", + "FULL_AURR980107 0.032958 -0.403599 -0.584111 \n", + "FULL_DAYM780201 0.055915 -0.326792 -0.554838 \n", + "FULL_GEOR030101 0.040480 -0.151935 -0.260470 \n", + "FULL_OOBM850104 -0.452769 0.155304 -0.453287 \n", + "NT_EFC195 0.145924 0.080898 0.260702 \n", + "AS_MeanAmphiMoment 0.025580 0.171524 0.693552 \n", + "AS_DAYM780201 0.045562 -0.256060 -0.437168 \n", + "AS_FUKS010112 1.000000 -0.445284 0.033432 \n", + "CT_RACS820104 -0.445284 1.000000 0.267652 \n", + "CLASS 0.033432 0.267652 1.000000 " + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#first ill review the pairwise correlation of the attributes.\n", + "Train.corr(method='pearson')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + " What did you learn from the correlation?\n", + " \n", + "

What does correlation server, in this instance? Why are we even doing it?\n", + " \n", + " Please write your report as if you are explaining to someone who has never done Machine learning\n", + "

\n", + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + " Please draw better visuals.\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#Reviewing inter-correlation of attributes using heatmap\n", + "#graphical representation\n", + "plt.figure(figsize=(6,6))\n", + "sns.heatmap(Train.corr(method='pearson'))" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "FULL_Charge 0.534602\n", + "FULL_AcidicMolPerc -0.598816\n", + "FULL_AURR980107 -0.584111\n", + "FULL_DAYM780201 -0.554838\n", + "FULL_GEOR030101 -0.260470\n", + "FULL_OOBM850104 -0.453287\n", + "NT_EFC195 0.260702\n", + "AS_MeanAmphiMoment 0.693552\n", + "AS_DAYM780201 -0.437168\n", + "AS_FUKS010112 0.033432\n", + "CT_RACS820104 0.267652\n", + "CLASS 1.000000\n", + "Name: CLASS, dtype: float64" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Ill also check the correlation in regards to the 'CLASS' attribute\n", + "Train.corr(method='pearson')['CLASS']" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Train['CLASS'].value_counts" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + " What did you learn?\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "AxesSubplot(0.125,0.125;0.775x0.755)\n" + ] + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#I need to know the distribution of the class attribute of my data.\n", + "print(Train.groupby('CLASS').size().plot(kind='bar'))\n", + "#train.CLASS.value_counts().plot(kind='bar')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### From the above bar graph, the Class distribution is even which means am dealing with balanced data." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Feature selection \n", + "## Using recursive feature elimination\n", + "\n", + "\n", + "
\n", + " What is Feature Selection?\n", + " \n", + " What are you trying to achieve here? Please write your thoughts.\n", + " \n", + " How did you arrive at 4 features?\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Num Features: 4\n", + "Selected Features: [False False True False False True True False False False True]\n", + "Feature Ranking: [3 7 1 6 2 1 1 4 8 5 1]\n" + ] + } + ], + "source": [ + "from sklearn.feature_selection import RFE\n", + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "# feature extraction\n", + "model = LogisticRegression()\n", + "rfe = RFE(model, 4)\n", + "fit = rfe.fit(X, Y)\n", + "print(\"Num Features: \", fit.n_features_)\n", + "print(\"Selected Features:\", fit.support_)\n", + "print(\"Feature Ranking: \", fit.ranking_)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", + " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", + " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", + " 'CLASS'],\n", + " dtype='object')" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Calling out the column names so I can know which features am going to drop from RFE\n", + "Train.columns" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Using Feature importance\n", + "\n", + "\n", + "
\n", + " When you see \"???\" just know you haven't sufficiently explained your thoughts.\n", + " \n", + " ## ??\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0.08652491 0.1297364 0.09323019 0.09956668 0.05401905 0.07223362\n", + " 0.03333241 0.30103142 0.05143828 0.03167747 0.04720957]\n" + ] + } + ], + "source": [ + "from sklearn.ensemble import ExtraTreesClassifier\n", + "\n", + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "# feature extraction\n", + "model = ExtraTreesClassifier()\n", + "model.fit(X, Y)\n", + "print(model.feature_importances_)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Am going to use 4 features and drop the rest\n", + "\n", + "
\n", + " ## ??\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "# I will call the new Train data with selected features New_Train.\n", + "Train\n", + "New_Train = Train.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "#dropping the same features in the test dataset\n", + "New_Test = Test.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['FULL_AURR980107', 'FULL_OOBM850104', 'NT_EFC195', 'CT_RACS820104',\n", + " 'CLASS'],\n", + " dtype='object')" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#viewing tselected features\n", + "New_Train.columns" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Rescaling data\n", + "\n", + "\n", + "
\n", + " ## ??\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[0.348 0.483 0. 0.182]\n", + " [0.322 0.458 1. 0.475]\n", + " [0.246 0.565 0. 0.666]\n", + " [0.275 0.647 0. 0.424]]\n" + ] + } + ], + "source": [ + "from numpy import set_printoptions\n", + "from sklearn.preprocessing import MinMaxScaler\n", + "array = New_Train.values\n", + "\n", + "#seperating data into onput and output options\n", + "X = array[:,0:4]\n", + "Y = array[:,4]\n", + "scaler = MinMaxScaler(feature_range = (0,1))\n", + "rescaledX = scaler.fit_transform(X)\n", + "\n", + "#summarising transformed data\n", + "set_printoptions(precision = 3)\n", + "print(rescaledX[0:4,:])\n", + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Standardising data\n", + "\n", + "\n", + "
\n", + " ## ??\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.preprocessing import StandardScaler\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Comparing models to use\n", + "\n", + "\n", + "
\n", + " ## ??\n", + " You have less than 10 algorithms, why?\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('LR', 0.798219298245614, 0.04658230982015574)\n", + "('LDA', 0.7955789473684212, 0.045052023551671226)\n", + "('KNN', 0.7985438596491228, 0.05940387146136468)\n", + "('CART', 0.7537807017543859, 0.04398756697084728)\n", + "('NB', 0.7996228070175438, 0.12333496511360942)\n", + "('SVM', 0.8071447368421053, 0.07573362330045245)\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#comparing different models to from which ill choose.\n", + "from matplotlib import pyplot\n", + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "from sklearn.neighbors import KNeighborsClassifier\n", + "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", + "from sklearn.naive_bayes import GaussianNB\n", + "from sklearn.svm import SVC\n", + "\n", + "\n", + "# load dataset\n", + "\n", + "array = New_Train.values\n", + "\n", + "#split the dataset \n", + "X = array[:,0:4] #X = Train.drop(columns=['CLASS'])\n", + "Y = array[:,4] #Y = Train['CLASS']\n", + "\n", + "# prepare models and add them to a list\n", + "models = []\n", + "models.append(('LR', LogisticRegression()))\n", + "models.append(('LDA', LinearDiscriminantAnalysis()))\n", + "models.append(('KNN', KNeighborsClassifier()))\n", + "models.append(('CART', DecisionTreeClassifier()))\n", + "models.append(('NB', GaussianNB()))\n", + "models.append(('SVM', SVC()))\n", + "\n", + "# evaluate each model in turn\n", + "results = []\n", + "names = []\n", + "\n", + "for name, model in models:\n", + " kfold = KFold(n_splits=40, random_state=10)\n", + " cv_results = cross_val_score(model, X, Y, cv=kfold, scoring='accuracy')\n", + " results.append(cv_results)\n", + " names.append(name)\n", + " msg = (name, cv_results.mean(), cv_results.std())\n", + " print(msg)\n", + "\n", + "# boxplot algorithm comparison\n", + "fig = pyplot.figure()\n", + "fig.suptitle('Algorithm Comparison')\n", + "ax = fig.add_subplot(111)\n", + "pyplot.boxplot(results)\n", + "ax.set_xticklabels(names)\n", + "pyplot.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "#now slitting data\n", + "#array = New_Train.values\n", + "X = New_Train.values[:,0:4]\n", + "Y = New_Train.values[:,4]\n", + "from sklearn.model_selection import train_test_split\n", + "X_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size=0.2, random_state=42)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The result is: 62.28 Mathew's Coef\n" + ] + } + ], + "source": [ + "# also train and test the model on Matthews correlation coefficient.\n", + "from sklearn.metrics import matthews_corrcoef\n", + "\n", + "GS = GaussianNB()\n", + "GS.fit(X_Train,Y_Train)\n", + "pred = GS.predict(X_Test)\n", + "\n", + "print(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "LogisticRegression(C=0.05, class_weight=None, dual=False, fit_intercept=True,\n", + " intercept_scaling=1, l1_ratio=None, max_iter=100,\n", + " multi_class='ovr', n_jobs=None, penalty='l2',\n", + " random_state=30, solver='liblinear', tol=0.0001, verbose=0,\n", + " warm_start=False)" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#now creating a model and training it\n", + "model = LogisticRegression(solver='liblinear', C=0.05, multi_class='ovr', random_state=30)\n", + "model.fit(X_Train, Y_Train)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "X_Train, X_Test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2,\n", + "random_state=42)" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The result is: 62.28 Mathew's Coef\n" + ] + } + ], + "source": [ + "from sklearn.metrics import matthews_corrcoef\n", + "\n", + "nv = GaussianNB()\n", + "nv.fit(X_Train,Y_Train)\n", + "pred = nv.predict(X_Test)\n", + "\n", + "print(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "#model = DecisionTreeClassifier()\n", + "\n", + "#model.fit(X_train, y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201FULL_GEOR030101FULL_OOBM850104NT_EFC195AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CT_RACS820104
04.03.7040.87373.5190.987-4.83300.38274.5567.2251.234
14.04.4440.89262.4440.931-0.58400.32056.0564.9421.853
22.00.0000.90147.0001.039-5.66400.16447.0005.9691.174
34.50.0000.86969.2220.982-5.42302.01069.2225.4621.138
4-4.021.5911.06171.6820.976-2.00202.75866.0005.5821.453
\n", + "
" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n", + "0 4.0 3.704 0.873 73.519 \n", + "1 4.0 4.444 0.892 62.444 \n", + "2 2.0 0.000 0.901 47.000 \n", + "3 4.5 0.000 0.869 69.222 \n", + "4 -4.0 21.591 1.061 71.682 \n", + "\n", + " FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n", + "0 0.987 -4.833 0 0.382 \n", + "1 0.931 -0.584 0 0.320 \n", + "2 1.039 -5.664 0 0.164 \n", + "3 0.982 -5.423 0 2.010 \n", + "4 0.976 -2.002 0 2.758 \n", + "\n", + " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 \n", + "0 74.556 7.225 1.234 \n", + "1 56.056 4.942 1.853 \n", + "2 47.000 5.969 1.174 \n", + "3 69.222 5.462 1.138 \n", + "4 66.000 5.582 1.453 " + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Test.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "#we now need to predict on the test dataset\n", + "md = pd.DataFrame((New_Test.index,nv.predict(New_Test))).T\n", + "md = md.rename(columns={0:\"Index\",1:\"CLASS\"}).set_index('Index')\n", + "md.to_csv('maria.csv')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "
\n", + " ## ??\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ls: ../../kaggle/working/: No such file or directory\r\n" + ] + } + ], + "source": [ + "import os\n", + "os.listdir()\n", + "!ls ../../kaggle/working/" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.4" + }, + "varInspector": { + "cols": { + "lenName": 16, + "lenType": 16, + "lenVar": 40 + }, + "kernels_config": { + "python": { + "delete_cmd_postfix": "", + "delete_cmd_prefix": "del ", + "library": "var_list.py", + "varRefreshCmd": "print(var_dic_list())" + }, + "r": { + "delete_cmd_postfix": ") ", + "delete_cmd_prefix": "rm(", + "library": "var_list.r", + "varRefreshCmd": "cat(var_dic_list()) " + } + }, + "types_to_exclude": [ + "module", + "function", + "builtin_function_or_method", + "instance", + "_Feature" + ], + "window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/Assignment Colab/MARIA MAGDALENE NAMAGANDA.ipynb b/Assignment Colab/MARIA MAGDALENE NAMAGANDA.ipynb index 2f53cab..8155bd1 100644 --- a/Assignment Colab/MARIA MAGDALENE NAMAGANDA.ipynb +++ b/Assignment Colab/MARIA MAGDALENE NAMAGANDA.ipynb @@ -1 +1,1769 @@ -{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n for filename in filenames:\n print(os.path.join(dirname, filename))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#import the necessary libraries you are going to use\nimport warnings\nwarnings.filterwarnings('ignore')\n\n# -----> Put your code here below:\n\n\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Working with AMP_Data_set\n## `Training and testing data in Machine Learning`\n"},{"metadata":{"_cell_guid":"","_uuid":"","trusted":true},"cell_type":"code","source":"#Load the datasets, there are two i.e the Train and Test datasets\n\nTrain = pd.read_csv(\"../input/amp-data-set/AMP_TrainSet.csv\")\nTest = pd.read_csv(\"../input/amp-data-set/Test.csv\")\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":">Getting to know more about the data"},{"metadata":{"trusted":true},"cell_type":"code","source":"#here, am trying to find the kind of data am dealing with.\nprint(type(Train))\nprint(type(Test))\nprint(Train.dtypes)\nprint(Test.dtypes)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# check the dimensions of your data\n# this retuns the number of rows and columns in the data\n\nTrain.shape, Test.shape\n\n#this helps to know how big the data is in terms of rows and columns.\n#it also informs one of which data is labeled","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> The data is pre-prepared so ill just continue to work with it, since the Train dataset is already labeled with a CLASS attribute."},{"metadata":{"trusted":true},"cell_type":"code","source":"#getting a description of the data\n#Train.describe, Test.describe\nTrain.describe()\nTest.describe()\n#description gives a summary of the data.","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#looking at the first 5 entries of my data\nTrain.head()\nTest.head()\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":">Looking at the skewness of the data"},{"metadata":{"trusted":true},"cell_type":"code","source":"#knowing data skewness allows one to perform data preparation and improve a model\nTrain.skew().plot(kind='bar')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> Data correlation."},{"metadata":{"trusted":true},"cell_type":"code","source":"#first ill review the pairwise correlation of the attributes.\nTrain.corr(method='pearson')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Reviewing inter-correlation of attributes using heatmap\n#graphical representation\nplt.figure(figsize=(6,6))\nsns.heatmap(Train.corr(method='pearson'))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Ill also check the correlation in regards to the 'CLASS' attribute\nTrain.corr(method='pearson')['CLASS']","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Train['CLASS'].value_counts","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#I need to know the distribution of the class attribute of my data.\nprint(Train.groupby('CLASS').size().plot(kind='bar'))\n#train.CLASS.value_counts().plot(kind='bar')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"\n### From the above bar graph, the Class distribution is even which means am dealing with balanced data."},{"metadata":{},"cell_type":"markdown","source":"# Feature selection \n## Using recursive feature elimination"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.feature_selection import RFE\nfrom sklearn.linear_model import LogisticRegression\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = LogisticRegression()\nrfe = RFE(model, 4)\nfit = rfe.fit(X, Y)\nprint(\"Num Features: \", fit.n_features_)\nprint(\"Selected Features:\", fit.support_)\nprint(\"Feature Ranking: \", fit.ranking_)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Calling out the column names so I can know which features am going to drop from RFE\nTrain.columns","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Using Feature importance"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.ensemble import ExtraTreesClassifier\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = ExtraTreesClassifier()\nmodel.fit(X, Y)\nprint(model.feature_importances_)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Am going to use 4 features and drop the rest"},{"metadata":{"trusted":true},"cell_type":"code","source":"# I will call the new Train data with selected features New_Train.\nTrain\nNew_Train = Train.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#dropping the same features in the test dataset\nNew_Test = Test.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#viewing tselected features\nNew_Train.columns","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Rescaling data"},{"metadata":{"trusted":true},"cell_type":"code","source":"from numpy import set_printoptions\nfrom sklearn.preprocessing import MinMaxScaler\narray = New_Train.values\n\n#seperating data into onput and output options\nX = array[:,0:4]\nY = array[:,4]\nscaler = MinMaxScaler(feature_range = (0,1))\nrescaledX = scaler.fit_transform(X)\n\n#summarising transformed data\nset_printoptions(precision = 3)\nprint(rescaledX[0:4,:])\n ","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Standardising data"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.preprocessing import StandardScaler\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Comparing models to use"},{"metadata":{"trusted":true},"cell_type":"code","source":"#comparing different models to from which ill choose.\nfrom matplotlib import pyplot\nfrom sklearn.model_selection import KFold\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.svm import SVC\n\n\n# load dataset\n\narray = New_Train.values\n\n#split the dataset \nX = array[:,0:4] #X = Train.drop(columns=['CLASS'])\nY = array[:,4] #Y = Train['CLASS']\n\n# prepare models and add them to a list\nmodels = []\nmodels.append(('LR', LogisticRegression()))\nmodels.append(('LDA', LinearDiscriminantAnalysis()))\nmodels.append(('KNN', KNeighborsClassifier()))\nmodels.append(('CART', DecisionTreeClassifier()))\nmodels.append(('NB', GaussianNB()))\nmodels.append(('SVM', SVC()))\n\n# evaluate each model in turn\nresults = []\nnames = []\n\nfor name, model in models:\n kfold = KFold(n_splits=40, random_state=10)\n cv_results = cross_val_score(model, X, Y, cv=kfold, scoring='accuracy')\n results.append(cv_results)\n names.append(name)\n msg = (name, cv_results.mean(), cv_results.std())\n print(msg)\n\n# boxplot algorithm comparison\nfig = pyplot.figure()\nfig.suptitle('Algorithm Comparison')\nax = fig.add_subplot(111)\npyplot.boxplot(results)\nax.set_xticklabels(names)\npyplot.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now slitting data\n#array = New_Train.values\nX = New_Train.values[:,0:4]\nY = New_Train.values[:,4]\nfrom sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size=0.2, random_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# also train and test the model on Matthews correlation coefficient.\nfrom sklearn.metrics import matthews_corrcoef\n\nGS = GaussianNB()\nGS.fit(X_Train,Y_Train)\npred = GS.predict(X_Test)\n\nprint(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now creating a model and training it\nmodel = LogisticRegression(solver='liblinear', C=0.05, multi_class='ovr', random_state=30)\nmodel.fit(X_Train, Y_Train)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2,\nrandom_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.metrics import matthews_corrcoef\n\nnv = GaussianNB()\nnv.fit(X_Train,Y_Train)\npred = nv.predict(X_Test)\n\nprint(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#model = DecisionTreeClassifier()\n\n#model.fit(X_train, y_train)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Test.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#we now need to predict on the test dataset\nmd = pd.DataFrame((New_Test.index,nv.predict(New_Test))).T\nmd = md.rename(columns={0:\"Index\",1:\"CLASS\"}).set_index('Index')\nmd.to_csv('maria.csv')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"import os\nos.listdir()\n!ls ../../kaggle/working/","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4} \ No newline at end of file +{ + "cells": [ + { + "cell_type": "raw", + "metadata": { + "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", + "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" + }, + "source": [ + "# This Python 3 environment comes with many helpful analytics libraries installed\n", + "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", + "# For example, here's several helpful packages to load in \n", + "\n", + "import numpy as np # linear algebra\n", + "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", + "\n", + "# Input data files are available in the \"../input/\" directory.\n", + "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", + "\n", + "import os\n", + "for dirname, _, filenames in os.walk('/kaggle/input'):\n", + " for filename in filenames:\n", + " print(os.path.join(dirname, filename))\n", + "\n", + "# Any results you write to the current directory are saved as output." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "#import the necessary libraries you are going to use\n", + "import warnings\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "# -----> Put your code here below:\n", + "\n", + "\n", + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Working with AMP_Data_set\n", + "## `Training and testing data in Machine Learning`\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "_cell_guid": "", + "_uuid": "" + }, + "outputs": [], + "source": [ + "#Load the datasets, there are two i.e the Train and Test datasets\n", + "\n", + "Train = pd.read_csv(\"../AMP Data Sets/AMP_TrainSet.csv\")\n", + "Test = pd.read_csv(\"../AMP Data Sets/Test.csv\")\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + ">Getting to know more about the data\n", + "\n", + "
(Atwine)\n", + "\n", + "When you run the code below, what did you learn?\n", + "\n", + "Please document those findings.
" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n", + "FULL_Charge float64\n", + "FULL_AcidicMolPerc float64\n", + "FULL_AURR980107 float64\n", + "FULL_DAYM780201 float64\n", + "FULL_GEOR030101 float64\n", + "FULL_OOBM850104 float64\n", + "NT_EFC195 int64\n", + "AS_MeanAmphiMoment float64\n", + "AS_DAYM780201 float64\n", + "AS_FUKS010112 float64\n", + "CT_RACS820104 float64\n", + "CLASS int64\n", + "dtype: object\n", + "FULL_Charge float64\n", + "FULL_AcidicMolPerc float64\n", + "FULL_AURR980107 float64\n", + "FULL_DAYM780201 float64\n", + "FULL_GEOR030101 float64\n", + "FULL_OOBM850104 float64\n", + "NT_EFC195 int64\n", + "AS_MeanAmphiMoment float64\n", + "AS_DAYM780201 float64\n", + "AS_FUKS010112 float64\n", + "CT_RACS820104 float64\n", + "dtype: object\n" + ] + } + ], + "source": [ + "#here, am trying to find the kind of data am dealing with.\n", + "print(type(Train))\n", + "print(type(Test))\n", + "print(Train.dtypes)\n", + "print(Test.dtypes)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "((3038, 12), (758, 11))" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# check the dimensions of your data\n", + "# this retuns the number of rows and columns in the data\n", + "\n", + "Train.shape, Test.shape\n", + "\n", + "#this helps to know how big the data is in terms of rows and columns.\n", + "#it also informs one of which data is labeled" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> The data is pre-prepared so ill just continue to work with it, since the Train dataset is already labeled with a CLASS attribute.\n", + "\n", + "
\n", + " This is a good note\n", + "

Please highlight what you learnt from the describe function below, what does it tell you? \n", + " What did you notice from the data? Is it perfect?\n", + "

\n", + "

Or there are some things that bug you but you are deciding to leave them a lone for some reason?

\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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\n", + " What did you learn?\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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cMrJcQPXmK0k3TbWKkphqewrwQeB0259q9uGZtl/bQixYmggAXgo83fYfJX0JOLNmINsfAD4g6QO1k/cUOj1WgPvZPqF5/GFJZwAnSHo1SxNvTZ8D1gPebvt3AJIut71FC7GgfPEOPAf4CoDt39a8mJukhP4x4OvARpL+jXLm9a4W430R+J6kzzXPXwscVjnGkv/J5oz8KOCo5pJs58qxoJz93Gr7+8vtiPTzFuLdADxp8IEZiXdl7WC2T2/ad/9R0inAO2gnGQysLWlrStPl6rb/2OzHHZLuaiOg7f0kbQI8hKHPr+0fVA7V9bGCpHVt3whg+5SmyeyrwAa1Y9l+k6RtgCMkHQMcRLvHyg2SXghcDTwV2AtA0hpUPLmZmCYXAEmPAnagJMLv2b6o5Xg7As9unp5k+8TK2/8n2x+uuc35pLnncKzt5dpAJR1g+x0txt4E+A9gke2HthTjlJFFr7D9G0kPAE5so9CTpA9SruIuBAZfGrY90Td/Jb0CuMz2qSPLFwL/Yvv1LcVdDXgjsCvwMNsPbinOIygnpQ8CPmr7883y5wHPtf22KnEmJaFLGvctfbPtO1qItTrwXdvPqr3t+UDSA4FNmqdXjzuDjpXXHD9r2b51xhev+LZ/Djxu0BTYtnvKsSJpY2Br28fN9b6siklqcjkT2Az4A+UMfT3gt5J+B7ze9hm1Atm+S9Ldw5eAbWiaVvajNK9sRLnkuwb4BvBB2zdUjrc18ClgXcqlH8Cmkm4A/sF21XbfJua6lBu+S5IC5ey16t82FKuz93Mo7iLKsXkX8AvbP2PpjcvaLgPWBFpN6HNxrEyzL4fY3ruF7T4K2ImhY7NpR69+5S/p9cD/2L646QF1KPAy4ApgT9tn1YgzSQn9JODoQbOHpOdS3pDPUbo0/mXleLcA50k6CfjjYKHtN1WMcRRwMuWO928BmrveezbrnlsxFpT36m9tnza8UNJ2zbqqPYYk/Q3wbuA7LE0KzwLeL+lfbX+hZjw6fj8lPQM4kHKvYBvgx8D6TW+bV9uufp+A8kVxtqTvMZTUKx+X0P2xMlU7uYAX1IzVxHsHpXfZkcCgSXBTSpv6kbY/WDnkm4HPN4/3AB4HbAFsTWmKeXqNIJPU5HKe7ceOLDvX9uMknW37CZXj7Tluue1qN0Yl/dz2I1d03SrEu9j2llOsu8T2wyvH+znwl6Nnxk0f49NsP6J2vI7fz7Mo7Z/XStoC+IjtlzQ3Zt9uu/YXcifHZROn62PlLsoMZsNdPtw838T2vSrH+wWw1WiTraR7ARdM9bevQrwlOarpBXWa7f9snlfrDj1JZ+i/ab5Vj2ye7wb8rmmvrN590fZhTVfChbZbuasP/FLS/wUOG+o69UDgNUAbZ3fHS/o2ZUDDYPubAX8DnDDlb608Mb7nwN0s+8Gtpev3c3Xb1zaPf0XpeYLtkyR9tIV4XR2X0P2xchmwg+1fja5oo0cU5Rh8MMtPg7kx7XSHvrtpp/8DpWPHvw2tq9bLZZIS+isol+/HUJLEj5tlqwMvrx1M0ouADwP3AraQ9ATgPZV7E+wG7At8X0uHAP8OOJYW/qamq9bzGWk3BD7R0s2gfwPOlPQdliaFhZR+uO9tIV6n7yewWNJnKc08Lwb+B0DSfSjHZXUdHZdzcax8FFif8sU46t9biLcPpVvyxSx7bD6c0uultv2BxZTj4ljbF8CSZrvLagWZiCaX5iz8ANv/1GHMM4DtKTcyBiNTz7f9F13tQx80zSvPY/mbon+Yu72qQ9KawOuBx1CGch/a3FBfG9jI9spMgj5TzByXlTRdFrdl2WPzdNutjCFo+pzfb/jYH3z52765RoyJOENvPiRP6zjsHbZv1LKjuNocmboMSa+1/bmZX7lC21ydMqx6U8pw458MrXuX7dq1amgO3iNnfGHL2ng/m/bXT45Z/ieWv5SvpZPjci6OlWn25Tm2T6q9Xdt3UwZQjca7r+3REbI14t1JaXKh6emyPaWV4YXAA2vEmKTiXGdJOlbSqzVUgKnFeBeoDHZYXdKWkj4O/GSmX6roX1vY5n8BzwB+D3xc0keG1rX5Xi5HpY5Nl9p4P6ck6fiWNt3VcTlvjhU6LhxHGbTVCknbSfoY5Qv/G8APgEdV2/4kNLkAaOkQ/GF25YJLQ/HuA/wzS7u6nQi8z/afK8Y4d6pVwCNsV60dM+gV1Dxeg3J2uSGlG9Wprl8AaaoPvoCDbS+oHK/r93OqngkCvmV745rxmpjDx6Uox+V7ax6XTZyuj5Wui4G9dZp4/2y7arkBSe+njEb9FaUA39eBxa5cO2ZiEnqXVAp/PQS4pK3BKE2c31Hal0fbkwX8pPYwZEk/s/2okWX7N/uwUQtdte6g1MQZd5DtYvt+leN1/X7eBXyf8T12trPdRgGyTszBsfIHpi4G9mXbVZokhuL9GfgQcOeY1W+xXbWctaRrgF9Qbv5+0/Ztki5z5bIUE9GGDiDp3pSCNlsB9x4sr32GLul1wPuBSym9CPa2PdXZw6r6FnBf22eP2Y//aSHeYkk7emlVO2y/R9KvKaMCazsX+LDt80dXSHr2mNevqq7fz4sog28uHhOvja52g1Gp7wQ2Z9niXI+rHKrrY6XrYmBnAsd4zAjzJgfUtjGld9cewEdV6gCtLWmNpm29iok5Q5f0FeBnlJsI7wFeCVxk+82V45wPPKsZLPJQ4Iu2n1wzxj2FpKcDv5yib/Ei24vnYLeqkbQLcN64/uCSdrZ9TAsxfw68HTiPoZuhbfSo6TNJjwSuHxpHMLzugW6xZo2ktSg3QvegjBD9niuVyp6khH6W7a21dHTomsAPbW9XOc4yo7ZGn9fW3O0e7Tr1U7f0H6Mx9Sso/WJbrVzZla7fz65J+pHtTnp8zcWxontIMbABSfcHdrJdZRrBSUroP7W9raQfAP8A/JbyQa3aBtW0dQ13s9t9+Lkr1sxQqUfzSeBihgogUQY3/IPt79SK1cQbrl9x1VC83YHq9Suam2l7AS+hjMqD8nd+A/js6LDrCvG6fj/fCtxo+7Mjy/ei9DeuPlpU0g6U/8PRWi5fqxyn62NlbDEwSp2c6sXANEeF3KbYl2qzd01SQn8dpdj94yjFge4L7G/74MpxxtbKGHDdWi4XAc+3fcXI8i2A42w/ulasZrtd1684gvKBPIxlk8KewAa2d6scr+v38wzKzc9x7+fiFtq1kfTflG5uF7C0yaV6b685OFbOZupiYP/lylNNSjqRMsL3MC9fyG0Ht1CHZ5p9udL2ZjW2NTE3RW1/pnn4faCVCQuaOLVnJZrOGixNdMOuppRIra3r+hXbePkCXFcBp6qdCXm7fj/XGHeVYfv2pumnDU9y5SJjU+j6WFlnNJkD2D5VUhtz3W5u+4CRWL8FDpDUSlfoaVQ7q56YhN7cSHgZy9/df0/lON9kmjfYdWtmHAqcLulIlq0nsRvtDKboun7F9ZJ2Bb7ajMobDLfeleW7FtYw7v3cjNJM0Mb7udq4G2hNO3BbfiLpMbZbG/zS6PpY6boY2C/VYSE3lYF04/KKqDRKFCaryeUE4EbgDJZOvYXtAyvHecZ068d1q1rFeI+hFHYavfHUygdWHdavkLQ5cABliPPwxCQnA/vavryFmI9m/I286u+nSr33NwFvY+mk0NtQ+jcf1MbVXtOs9DDgckobuihNLm0073Rd62RcMbBj3UIxMJUaQ/s28UYLuR1g+/rK8bakJO7RL4vNgN/avqRKnAlK6J0XIGraCwdNBj+vfRNvipgb2r6uxe0vBG6yfUOTcBdRun9e0FbMJu4DAGz/vs04XWuS0L7AX1DOwC6g3FRrZei/pIeMW95Gt8W5Olb6SNK3gP1snzey/LHA+22/qEacSarl8pPmj++EpGdSekt8gtJz4heS/qpyjOdLulzSjyRtLekC4DRJVzW9GaqStC/lHsSpzU3mE4DnA0dp6qHQqxpzW0lPahL5AyW9tUmCbcTacejxupI+I+lcSV9qqxnE9vG2n2H7AbY3bB63VcdlkLjXA17U/KzXUjLv/FiZZl8OaWm7j5K0w2gb/fBxVNEDR5M5QLNs82pRbM/rH8oAinMpBXPuAH7ePD8POLfFuGcAjxx6/gjgjMoxzgYeDTyZUgRpu2b5o4EzW/ibLqAU038AcDOwoFm+DnB+C/HeTRkBuBj4AKWp5V8oBYn+uYV4Zw49/gzwPkoJh7dQRgXWjvedocf7tXEcjon5ZuB8yuC69zSfg3/swbGywRQ/DwCuaiHem5pccgxlXs+dxh1HFeNdPM26S2rFmYSboi+co7hremgEoO1fNIOZarrbzSANSbfaPrWJdVHTflnbXbb/JOl24E+ULxFs/7GlThm7AE8A1qKMG9jU9k2SPgycxrKzttS2yEunJfyPmbqjrqTh4mK7Ur602rYXZVq/PwJIOgD4X+DjleN0faxcy9RT0G009jdWzespvbBuaZqTjpa0ucu0cG38gYslvd72p4cXNlc/1Sa4n4SEvhGwoUcuY5vL9mtor+70YkmfAf67ef5KyplmTTdI+lvg/sAfJL2FMpnxs1m+SFENZ6rMZ7gOZWDKYc3N5u1pp2TonS430G6VdKntm6DUC5fURte3jZrmAAH3lyQ3p0C007w4FzegxFCngOZxGwmo62Ol6ynoVnNT89z2FU0T69HNPYo23s99gK9LeiVLE/giysxTL6kVZBIS+gHAa8csv5AywGj7luL+PfAGyqUZwA8ZM5nBKtoTeBclMTyXMjLvRMqX1Osrx4IyYcGuTbyjKT0YXkG59PxEC/Ful3Qf27dSen8AS0bptZHQPw0MKjgeRin3em0zYGS5gl0VPFSl7KuGHi/hytPCNT5Huc/y9eb5zrTTJbPrY6XrKeh+J+kJbgq5NWfqL6R0fa1+r86la+RTJD2LcgMd4Nu2T64ZZ973cpF0uu0nTbFuSc3mmH8krWX7tjHLNwQ29pibRJOk6y6uQ3GfCAzqufzQ9lltxOkzSZtSriB/O2bdU23/eA52a5VNQkK/xPbDV3TdKsSbapIEoH6Z0uYb+2WU/qh3UWomf9r2pTXjNLHOBL4GHNHG9qeI2VmxLEkbUAa9/Jpy1vpOyg3niyhdw6oOZpJ0/0Ez0ph1C8c1H6xCrGknXHD9ftNzcax0Wgxsim6ZP/OYcs+TYhK6LX5X0r9p6E6MivdQek3UdjclsR5OmSn+RSM/1Uj6AGUk3KmUHjyXNj9Hq4ywrG19Spe3UyT9VNJbJFWd9GGYSrGsi4H/B7yg+flX4OJmXW3/TWnz3QY4BXgQpcnuT8DnW4j3P4MHkr43sq526dzrKM1Gi5ufM4Z+2ihD3PWx8g5KITABP21+BBzRdKGsHW+qbplf7rpbZlW1u+e00N1nHcqUTZdSinN9FbiE8p9/35ZiPoqSeM6kJIkXUOp21I5z3tDjNYAfN4/Xp52uYcPd+p5OuSfwW0ry27uFeBdRamaMLt+CMkCldryzm39FKb263LrK8c4a93jc8wqxPgqc0/yfPZ3m6rqtnzk4Vn5B6Vk2uvxeTNPlbxXiddots6ufeX+GbvuPtvegzPbx+ebnubZ399DM3JK2qhjzZ7bf7VIH/ZuU+hJvqbX9IXcPXUo/GFi9iT8YJt8a2z+0/Q+Uy9sDKE0TtXVdLGs1lSHdmwH3bS6jB6NU79VCPE/xeNzzVQtk70PpAvoV4NWUSdP/XaWSZKs6OlYGxcBGtVUM7C7bf6JUA12mW2YLsTozCb1cALB9GaVr01QOB6pMRCFpE0pBp5dQapC8hTKpa23vp3wwfwE8ktKzBpU5Tc9pId5yFQ5duhWeQDsFkLoulvUByqxWAP8H+IwkA4+hXHHVNtxNcqOhS3WxbB/1KlxOIU+RdBblPXwvpUnr09P+4srp+ljpuhjYVN0yd6CdbpmdmPc3RWdLzYxGFbbzfUrXt6MozTvL1B5x/ZtPG1DKAbc6IfVcUYfFspp4q1OO6ztVJth4AqX55TctxHr3dOttV/sSaYan70SpxLmAcsPyKFe88TrX1G3huDVYtlvmX1K6Df8K+MSknqn3KaFXmSpO0hUsvVwefnMGVe1aq8U+tA+PAN5uu2pf9Jlu9tj+SM14M+xL9a5hTXe+KbnyrKfvthYAABWtSURBVDezJWk/26s0ilTSHyln40c2/y7zwXX9GYs6PVYk3Qe4w00BPJU5P18AXGG7javj0fhrUvqHX237mrbjtSUJfQ5JehzwYUrb4TGUARsHUc4WDrT9H5Xj3U3pKXE8S0uvLlHzjLKJtzqlp9AmwAm2z28Gb7wTWLvGFdVIvLspdU4G1SqXGUZuu61BaNOqcWxK+jxTt8vb9Wcs6vpY+QGwl+2LJT2c0svli5Tmsp/a3q9yvIOBj9u+oBno9r+U3m0bAP9k+4ia8boy0Qld0oNt/7p5fKorThgt6SXAybZvbJ6vBzzTFWdyl3QaZR7F/wV2pCS6wyhT6/25VpyheI+nXFbuSOnudgRlxvG2JqT+PKXN/KeUL6lfU/r67lvzfRyKtw+lfsyNlDPZrw/fOJ8rtZoDuzQHx8p5th/bPH4vZYrCN6iUsD5jsK5ivAtsb9U83ofy2d65GVV8/KT9fw1MekKvNrnqmG2f7aXFnQbLqn4wR2NIuqyLJp0m1lMoH9hnA++wfewMv7IyMc4HHmf7bkn3pnR7e5hbroku6aGUm4Y7UcoovN/NEO+5UOkM/VW2/3uqppA2m8s6OlaWjPqW9GPgQ4MvfUnnuP6coks+yyozJX3F9udH102aienlMoU2u/aN69JZ+/26t8ps54O/47bh5221+Ta9aLam1Ky4ilLkrA23u5l6zvafmy+s1ie4sH2ZpG9Q+hm/mlL6eM4SOnWO00HN7vtN+6rKOjxWzlWpwnk1pWfLd5r467UU74am+e9q4KmUKpaDm6VrtxSzdTlDn3rbh1L6qA4KEb2Bchn4mooxTplmdfU2X5XJb18O3JtyZ/+oNm8ASbqVMggMSlJ7WPO8lWnTRs7Mr6Q0u3y76W9cnaQ32j5oFq97p+33t7EPbZmDY2VtSq33jYFDbZ/TLH8K5aru8MrxHgF8jDKa+KNDZ+fPo4xzeVvNeF2Z9wld0seZenLVPW3fv6W461AmY3h2s+gk4H2T2p0JlrlpOCg5PNpTomp1QE0xXdpQvKqlj5u/71zgG8BNLP/31e6Z0fmN+OaM+fUsP1l6GzdFuzxWnmP7pCnWHWD7HTXj9dUkNLlMV6eijRoWwJIRY9VrSMyGpOcA/9f2cypv+lmVtzetQcJuRjMORvJe2AwSa8N7WJp47ttSjLn2DUop5++ybF302jo9VoBPSHqL7W8PFjT90g+lnEVXJelDlLEf/zWy/G+BLWzPyWd/Vc37M/TpSPqw7X+qvM2P2t5H0jcZc2VQ88xE0vbAwSzttngApd61gH9roW/xO4APtzFQY4p496dMBbeIpW3YT6D0mtjLU1QqnBSS7gRuHbeK0qRU/epx3M36NszBsbIFpYvkfra/3txEP5pypbWnK0/QLukMyqxWHlm+GmVqy04npK9lEs7Qp/NyoGpCp5QQgNI/vG0HAntTui0+v/l339m0y66kzYAzJL2h9qCeKXyMMox698HNUUmiNGUdRKk0WU2TBHajlGv4JvB24K8ohd3ea/u6aX59ZZw3B70hviXpBbaPazlOp8eK7cslPRs4UWVC71dRRom2UUMJYK1xXTCbHlmt1lFq06SfoV9pe7O53o+VNdoGK+nnth/ZcswnUpLpRZQ+8EsKH9XuVSPpYttbrui6VYh3FKUM8To0FSspif1pwBNsV52ftsvubZJuZukcm+sAt1P+VmjvaqDLY2XwOXgwZSzGSQzNVNRCvNOBV9i+eGT5lpQa8ItqxuvKvD9D19SF/UUL3RYlncc0lfIq98xYT9JLh56vMfy8dpNLs80zJb2TUqfmYSxb5qDLkZRtnAU9xvZfNF3PrrI9mFHoBEltFDv7SgvbHMt2p90Vm5hdHisHDj0+F3jg0LI24u0PHC/pfSw7x+d+lEJhE2neJ3TKmz04Mxl1ewvxBmdxb2j+HTTBvIr6kwJ/n2UnzfjB0HNTCjBVI2kjyofkocD2g65hLfqJpP0pzR1L3jtJ/0JpXqrtdgCXwly/HlnXRlvwms3fN45tv7eFmDRf+k+jHCM/bGnUbafHiu2ub9gfL2lnSrPcPzaLLwBe5gmeGnGim1zaNO5yei66qdUk6XJKidlPj2s/bCHe/Sllcp/IsjdFzwJe58rVJSVdw9JZb3ZrHtM8f7ntB1aON66v8n0oEyw/wHb1njaSPkkZeDOoNbIbcKntN0z9WysVp+tj5aUji0wzS5Ptm9uOP7Qf9wZeZLuzq6+a5n1C1/IV9AxcZ/vKca+vGPdsYMkNoWaAwydr9jAYM4x7cBD/yPblteIMxVtg+9oxyzej3Lj8UO2YzfYfRimyBKXbYitzVErac7r1tg9rI24T+36UgTF7UUovH9jGQBxJPwMePUiyTa+MC2w/unKcTo8VSZ8bs3gD4HGUHlFtTDc5iL068DxKeYPnUq56dmkrXpsmocnlwDHLNlAp2rOH26vRsRdwqEolNlF6TlQdvMH4YdybA/8s6f/ZPnLM+pU2/AFtBqjsSjmIH0wLE3ioqT9i+1JJDxruLTHbUZYrYjhhS7pvs6zV4lzNPZ63Aq+k3Mx7oitPRj3iEsrED4MBP5uxdDRuNV0fK7ZfO255MzjtKEpxt6okPQN4BaVM708pJQC2sD2uK+pEmPdn6FORtAj4iO2/ajnOugBuqi52oUkS363dvNOcRb6UchA/gtJGv5vtTWvGGYq3pIlqTI+eVpqvJP095cbWoPbJLcABtj/ZQqwPUd7PQyiTIrRe2VFlApYnURIQzePFlAqT1cZJdH2szLAv1Y8VSVdRJrP4FHCM7ZslXW679Sn92jQJZ+hj2V48OAurSVNUtRt0TXUHk0DYvr6lvrDXUBLBuyjNOlYpE9wWTfF43PNVDya9C3gKpRTqZc2yhwL/KWkD2++rHPJtlFrh76JcVS3ZFVrqSkjpndGFro+VsVQmurithU0fDexMuQdxl0oxt8k8ux0ysQm9GXzQxn/AnFS1GybpWZQmntr2oxSv+iRwhKQvtxBjWGeTKDdeDTzeQ7XkXSovvpwyR2vVhG6780nWbX8fltxwHq7lUnVqRDo+VqYYmb0BpVjXq2rHcxkN/hbgmZSmpH8H1m2OleO6uNpqw7xvctH44lwbUM7E3mz7m93vVR1T9HnfgDIRxJ62L2op7qAq4R7AlsC7KZNBLDcx8CrGGVRbHK60SPP8obbXmep3VzLez2w/akXXTRJJe1Nq1vyZMtCn1akROzxWnjGyyJT5fC+23Ub35NH4a7L0xujzbG/Ydsw2TEJCH+25MPiPPr2NXgRDcQ+jfGHc0Dxfn9JzodqNUS1fjdDA791hRUdJf0FpJ3257YdX3nbX1Ra/R5nM4nsjy7cH/qXrvs5tkHQx8GTXL2Mwm9htHivb2T615jZXlqS/sv2Dud6PlTEJCX2h52Bm8yn6obc+1FulbO9LKD14/rqlGOtRzrYAftHlDd82SdqKUo3wRyw7+u+pwE62L5irfatF0gnAS7vqidHVsTJyA/1/bT+5jThD8Tqd77Yrk9CGfgxlYAqSvmr7ZR3FXU3S+oMuaE3Pk1ber6YL5l9Tzn6eRxlqfXALcdYC/otyM+hyyuX6QyR9Hfi72pe2kvaiTAryoeb51ZR7EwLebrvq3+gy4e/gLHJQrvcHwN+6hTla58h+lBG4pzF0s9D2m2oG6fpYYdmb5PeuvO1xPsvS+W4/1owsbm2+265MQkIf/o/uZL7NxoHA/0r6SrMPuwBVZ52R9FyWDmY4BfgC8KSp+uRW8M/AmsBmg9F3Tfe0T1AqIP5L5Xh/R5lkeOAa25s0o/FOpIUvLZep7k5h6VRpF/YomUNJsicD5zFULKsFXR8rqzXNmqsNPV7y2W/hpu8i5mC+27ZNQpPLlH2ZO4j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FULL_OOBM850104-0.2837580.5133440.4627120.3347780.3191571.000000-0.230561-0.3362970.275640-0.4527690.155304-0.453287
NT_EFC1950.088068-0.143168-0.169540-0.090058-0.230417-0.2305611.0000000.178683-0.0368440.1459240.0808980.260702
AS_MeanAmphiMoment0.355477-0.431590-0.426097-0.408793-0.160269-0.3362970.1786831.000000-0.3223780.0255800.1715240.693552
AS_DAYM780201-0.3653740.4496210.4562600.894191-0.0290850.275640-0.036844-0.3223781.0000000.045562-0.256060-0.437168
AS_FUKS010112-0.0905700.0023340.0329580.0559150.040480-0.4527690.1459240.0255800.0455621.000000-0.4452840.033432
CT_RACS8201040.232929-0.213543-0.403599-0.326792-0.1519350.1553040.0808980.171524-0.256060-0.4452841.0000000.267652
CLASS0.534602-0.598816-0.584111-0.554838-0.260470-0.4532870.2607020.693552-0.4371680.0334320.2676521.000000
\n", + "
" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 \\\n", + "FULL_Charge 1.000000 -0.612996 -0.490977 \n", + "FULL_AcidicMolPerc -0.612996 1.000000 0.794796 \n", + "FULL_AURR980107 -0.490977 0.794796 1.000000 \n", + "FULL_DAYM780201 -0.434603 0.541481 0.548253 \n", + "FULL_GEOR030101 -0.058725 0.115201 0.346139 \n", + "FULL_OOBM850104 -0.283758 0.513344 0.462712 \n", + "NT_EFC195 0.088068 -0.143168 -0.169540 \n", + "AS_MeanAmphiMoment 0.355477 -0.431590 -0.426097 \n", + "AS_DAYM780201 -0.365374 0.449621 0.456260 \n", + "AS_FUKS010112 -0.090570 0.002334 0.032958 \n", + "CT_RACS820104 0.232929 -0.213543 -0.403599 \n", + "CLASS 0.534602 -0.598816 -0.584111 \n", + "\n", + " FULL_DAYM780201 FULL_GEOR030101 FULL_OOBM850104 \\\n", + "FULL_Charge -0.434603 -0.058725 -0.283758 \n", + "FULL_AcidicMolPerc 0.541481 0.115201 0.513344 \n", + "FULL_AURR980107 0.548253 0.346139 0.462712 \n", + "FULL_DAYM780201 1.000000 0.010118 0.334778 \n", + "FULL_GEOR030101 0.010118 1.000000 0.319157 \n", + "FULL_OOBM850104 0.334778 0.319157 1.000000 \n", + "NT_EFC195 -0.090058 -0.230417 -0.230561 \n", + "AS_MeanAmphiMoment -0.408793 -0.160269 -0.336297 \n", + "AS_DAYM780201 0.894191 -0.029085 0.275640 \n", + "AS_FUKS010112 0.055915 0.040480 -0.452769 \n", + "CT_RACS820104 -0.326792 -0.151935 0.155304 \n", + "CLASS -0.554838 -0.260470 -0.453287 \n", + "\n", + " NT_EFC195 AS_MeanAmphiMoment AS_DAYM780201 \\\n", + "FULL_Charge 0.088068 0.355477 -0.365374 \n", + "FULL_AcidicMolPerc -0.143168 -0.431590 0.449621 \n", + "FULL_AURR980107 -0.169540 -0.426097 0.456260 \n", + "FULL_DAYM780201 -0.090058 -0.408793 0.894191 \n", + "FULL_GEOR030101 -0.230417 -0.160269 -0.029085 \n", + "FULL_OOBM850104 -0.230561 -0.336297 0.275640 \n", + "NT_EFC195 1.000000 0.178683 -0.036844 \n", + "AS_MeanAmphiMoment 0.178683 1.000000 -0.322378 \n", + "AS_DAYM780201 -0.036844 -0.322378 1.000000 \n", + "AS_FUKS010112 0.145924 0.025580 0.045562 \n", + "CT_RACS820104 0.080898 0.171524 -0.256060 \n", + "CLASS 0.260702 0.693552 -0.437168 \n", + "\n", + " AS_FUKS010112 CT_RACS820104 CLASS \n", + "FULL_Charge -0.090570 0.232929 0.534602 \n", + "FULL_AcidicMolPerc 0.002334 -0.213543 -0.598816 \n", + "FULL_AURR980107 0.032958 -0.403599 -0.584111 \n", + "FULL_DAYM780201 0.055915 -0.326792 -0.554838 \n", + "FULL_GEOR030101 0.040480 -0.151935 -0.260470 \n", + "FULL_OOBM850104 -0.452769 0.155304 -0.453287 \n", + "NT_EFC195 0.145924 0.080898 0.260702 \n", + "AS_MeanAmphiMoment 0.025580 0.171524 0.693552 \n", + "AS_DAYM780201 0.045562 -0.256060 -0.437168 \n", + "AS_FUKS010112 1.000000 -0.445284 0.033432 \n", + "CT_RACS820104 -0.445284 1.000000 0.267652 \n", + "CLASS 0.033432 0.267652 1.000000 " + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#first ill review the pairwise correlation of the attributes.\n", + "Train.corr(method='pearson')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + " What did you learn from the correlation?\n", + " \n", + "

What does correlation server, in this instance? Why are we even doing it?\n", + " \n", + " Please write your report as if you are explaining to someone who has never done Machine learning\n", + "

\n", + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + " Please draw better visuals.\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#Reviewing inter-correlation of attributes using heatmap\n", + "#graphical representation\n", + "plt.figure(figsize=(6,6))\n", + "sns.heatmap(Train.corr(method='pearson'))" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "FULL_Charge 0.534602\n", + "FULL_AcidicMolPerc -0.598816\n", + "FULL_AURR980107 -0.584111\n", + "FULL_DAYM780201 -0.554838\n", + "FULL_GEOR030101 -0.260470\n", + "FULL_OOBM850104 -0.453287\n", + "NT_EFC195 0.260702\n", + "AS_MeanAmphiMoment 0.693552\n", + "AS_DAYM780201 -0.437168\n", + "AS_FUKS010112 0.033432\n", + "CT_RACS820104 0.267652\n", + "CLASS 1.000000\n", + "Name: CLASS, dtype: float64" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Ill also check the correlation in regards to the 'CLASS' attribute\n", + "Train.corr(method='pearson')['CLASS']" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Train['CLASS'].value_counts" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + " What did you learn?\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "AxesSubplot(0.125,0.125;0.775x0.755)\n" + ] + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#I need to know the distribution of the class attribute of my data.\n", + "print(Train.groupby('CLASS').size().plot(kind='bar'))\n", + "#train.CLASS.value_counts().plot(kind='bar')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### From the above bar graph, the Class distribution is even which means am dealing with balanced data." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Feature selection \n", + "## Using recursive feature elimination\n", + "\n", + "\n", + "
\n", + " What is Feature Selection?\n", + " \n", + " What are you trying to achieve here? Please write your thoughts.\n", + " \n", + " How did you arrive at 4 features?\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Num Features: 4\n", + "Selected Features: [False False True False False True True False False False True]\n", + "Feature Ranking: [3 7 1 6 2 1 1 4 8 5 1]\n" + ] + } + ], + "source": [ + "from sklearn.feature_selection import RFE\n", + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "# feature extraction\n", + "model = LogisticRegression()\n", + "rfe = RFE(model, 4)\n", + "fit = rfe.fit(X, Y)\n", + "print(\"Num Features: \", fit.n_features_)\n", + "print(\"Selected Features:\", fit.support_)\n", + "print(\"Feature Ranking: \", fit.ranking_)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", + " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", + " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", + " 'CLASS'],\n", + " dtype='object')" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Calling out the column names so I can know which features am going to drop from RFE\n", + "Train.columns" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Using Feature importance\n", + "\n", + "\n", + "
\n", + " When you see \"???\" just know you haven't sufficiently explained your thoughts.\n", + " \n", + " ## ??\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0.08652491 0.1297364 0.09323019 0.09956668 0.05401905 0.07223362\n", + " 0.03333241 0.30103142 0.05143828 0.03167747 0.04720957]\n" + ] + } + ], + "source": [ + "from sklearn.ensemble import ExtraTreesClassifier\n", + "\n", + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "# feature extraction\n", + "model = ExtraTreesClassifier()\n", + "model.fit(X, Y)\n", + "print(model.feature_importances_)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Am going to use 4 features and drop the rest\n", + "\n", + "
\n", + " ## ??\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "# I will call the new Train data with selected features New_Train.\n", + "Train\n", + "New_Train = Train.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "#dropping the same features in the test dataset\n", + "New_Test = Test.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['FULL_AURR980107', 'FULL_OOBM850104', 'NT_EFC195', 'CT_RACS820104',\n", + " 'CLASS'],\n", + " dtype='object')" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#viewing tselected features\n", + "New_Train.columns" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Rescaling data\n", + "\n", + "\n", + "
\n", + " ## ??\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[0.348 0.483 0. 0.182]\n", + " [0.322 0.458 1. 0.475]\n", + " [0.246 0.565 0. 0.666]\n", + " [0.275 0.647 0. 0.424]]\n" + ] + } + ], + "source": [ + "from numpy import set_printoptions\n", + "from sklearn.preprocessing import MinMaxScaler\n", + "array = New_Train.values\n", + "\n", + "#seperating data into onput and output options\n", + "X = array[:,0:4]\n", + "Y = array[:,4]\n", + "scaler = MinMaxScaler(feature_range = (0,1))\n", + "rescaledX = scaler.fit_transform(X)\n", + "\n", + "#summarising transformed data\n", + "set_printoptions(precision = 3)\n", + "print(rescaledX[0:4,:])\n", + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Standardising data\n", + "\n", + "\n", + "
\n", + " ## ??\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.preprocessing import StandardScaler\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Comparing models to use\n", + "\n", + "\n", + "
\n", + " ## ??\n", + " You have less than 10 algorithms, why?\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('LR', 0.798219298245614, 0.04658230982015574)\n", + "('LDA', 0.7955789473684212, 0.045052023551671226)\n", + "('KNN', 0.7985438596491228, 0.05940387146136468)\n", + "('CART', 0.7537807017543859, 0.04398756697084728)\n", + "('NB', 0.7996228070175438, 0.12333496511360942)\n", + "('SVM', 0.8071447368421053, 0.07573362330045245)\n" + ] + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#comparing different models to from which ill choose.\n", + "from matplotlib import pyplot\n", + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "from sklearn.neighbors import KNeighborsClassifier\n", + "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", + "from sklearn.naive_bayes import GaussianNB\n", + "from sklearn.svm import SVC\n", + "\n", + "\n", + "# load dataset\n", + "\n", + "array = New_Train.values\n", + "\n", + "#split the dataset \n", + "X = array[:,0:4] #X = Train.drop(columns=['CLASS'])\n", + "Y = array[:,4] #Y = Train['CLASS']\n", + "\n", + "# prepare models and add them to a list\n", + "models = []\n", + "models.append(('LR', LogisticRegression()))\n", + "models.append(('LDA', LinearDiscriminantAnalysis()))\n", + "models.append(('KNN', KNeighborsClassifier()))\n", + "models.append(('CART', DecisionTreeClassifier()))\n", + "models.append(('NB', GaussianNB()))\n", + "models.append(('SVM', SVC()))\n", + "\n", + "# evaluate each model in turn\n", + "results = []\n", + "names = []\n", + "\n", + "for name, model in models:\n", + " kfold = KFold(n_splits=40, random_state=10)\n", + " cv_results = cross_val_score(model, X, Y, cv=kfold, scoring='accuracy')\n", + " results.append(cv_results)\n", + " names.append(name)\n", + " msg = (name, cv_results.mean(), cv_results.std())\n", + " print(msg)\n", + "\n", + "# boxplot algorithm comparison\n", + "fig = pyplot.figure()\n", + "fig.suptitle('Algorithm Comparison')\n", + "ax = fig.add_subplot(111)\n", + "pyplot.boxplot(results)\n", + "ax.set_xticklabels(names)\n", + "pyplot.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "#now slitting data\n", + "#array = New_Train.values\n", + "X = New_Train.values[:,0:4]\n", + "Y = New_Train.values[:,4]\n", + "from sklearn.model_selection import train_test_split\n", + "X_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size=0.2, random_state=42)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The result is: 62.28 Mathew's Coef\n" + ] + } + ], + "source": [ + "# also train and test the model on Matthews correlation coefficient.\n", + "from sklearn.metrics import matthews_corrcoef\n", + "\n", + "GS = GaussianNB()\n", + "GS.fit(X_Train,Y_Train)\n", + "pred = GS.predict(X_Test)\n", + "\n", + "print(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "LogisticRegression(C=0.05, class_weight=None, dual=False, fit_intercept=True,\n", + " intercept_scaling=1, l1_ratio=None, max_iter=100,\n", + " multi_class='ovr', n_jobs=None, penalty='l2',\n", + " random_state=30, solver='liblinear', tol=0.0001, verbose=0,\n", + " warm_start=False)" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#now creating a model and training it\n", + "model = LogisticRegression(solver='liblinear', C=0.05, multi_class='ovr', random_state=30)\n", + "model.fit(X_Train, Y_Train)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "X_Train, X_Test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2,\n", + "random_state=42)" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The result is: 62.28 Mathew's Coef\n" + ] + } + ], + "source": [ + "from sklearn.metrics import matthews_corrcoef\n", + "\n", + "nv = GaussianNB()\n", + "nv.fit(X_Train,Y_Train)\n", + "pred = nv.predict(X_Test)\n", + "\n", + "print(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "#model = DecisionTreeClassifier()\n", + "\n", + "#model.fit(X_train, y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201FULL_GEOR030101FULL_OOBM850104NT_EFC195AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CT_RACS820104
04.03.7040.87373.5190.987-4.83300.38274.5567.2251.234
14.04.4440.89262.4440.931-0.58400.32056.0564.9421.853
22.00.0000.90147.0001.039-5.66400.16447.0005.9691.174
34.50.0000.86969.2220.982-5.42302.01069.2225.4621.138
4-4.021.5911.06171.6820.976-2.00202.75866.0005.5821.453
\n", + "
" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n", + "0 4.0 3.704 0.873 73.519 \n", + "1 4.0 4.444 0.892 62.444 \n", + "2 2.0 0.000 0.901 47.000 \n", + "3 4.5 0.000 0.869 69.222 \n", + "4 -4.0 21.591 1.061 71.682 \n", + "\n", + " FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n", + "0 0.987 -4.833 0 0.382 \n", + "1 0.931 -0.584 0 0.320 \n", + "2 1.039 -5.664 0 0.164 \n", + "3 0.982 -5.423 0 2.010 \n", + "4 0.976 -2.002 0 2.758 \n", + "\n", + " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 \n", + "0 74.556 7.225 1.234 \n", + "1 56.056 4.942 1.853 \n", + "2 47.000 5.969 1.174 \n", + "3 69.222 5.462 1.138 \n", + "4 66.000 5.582 1.453 " + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Test.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "#we now need to predict on the test dataset\n", + "md = pd.DataFrame((New_Test.index,nv.predict(New_Test))).T\n", + "md = md.rename(columns={0:\"Index\",1:\"CLASS\"}).set_index('Index')\n", + "md.to_csv('maria.csv')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "
\n", + " ## ??\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ls: ../../kaggle/working/: No such file or directory\r\n" + ] + } + ], + "source": [ + "import os\n", + "os.listdir()\n", + "!ls ../../kaggle/working/" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.4" + }, + "varInspector": { + "cols": { + "lenName": 16, + "lenType": 16, + "lenVar": 40 + }, + "kernels_config": { + "python": { + "delete_cmd_postfix": "", + "delete_cmd_prefix": "del ", + "library": "var_list.py", + "varRefreshCmd": "print(var_dic_list())" + }, + "r": { + "delete_cmd_postfix": ") ", + "delete_cmd_prefix": "rm(", + "library": "var_list.r", + "varRefreshCmd": "cat(var_dic_list()) " + } + }, + "types_to_exclude": [ + "module", + "function", + "builtin_function_or_method", + "instance", + "_Feature" + ], + "window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/Assignment Colab/maria.csv b/Assignment Colab/maria.csv new file mode 100644 index 0000000..07d74e8 --- /dev/null +++ b/Assignment Colab/maria.csv @@ -0,0 +1,759 @@ +Index,CLASS +0.0,1.0 +1.0,1.0 +2.0,1.0 +3.0,1.0 +4.0,0.0 +5.0,1.0 +6.0,0.0 +7.0,1.0 +8.0,1.0 +9.0,1.0 +10.0,0.0 +11.0,1.0 +12.0,1.0 +13.0,0.0 +14.0,0.0 +15.0,1.0 +16.0,0.0 +17.0,1.0 +18.0,1.0 +19.0,1.0 +20.0,1.0 +21.0,1.0 +22.0,1.0 +23.0,1.0 +24.0,0.0 +25.0,1.0 +26.0,1.0 +27.0,1.0 +28.0,1.0 +29.0,1.0 +30.0,1.0 +31.0,1.0 +32.0,0.0 +33.0,1.0 +34.0,0.0 +35.0,1.0 +36.0,1.0 +37.0,1.0 +38.0,1.0 +39.0,1.0 +40.0,1.0 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b/Reading Material/Pandas Cookbook/Pandas-Cookbook @@ -0,0 +1 @@ +Subproject commit b45d95ccef24b020fdf28ecb5a07e3348bee62f1 diff --git a/Thur 20 Feb/ACE_ClassML Pipeline.ipynb b/Thur 20 Feb/ACE_ClassML Pipeline.ipynb index e55fe6d..fbe730a 100644 --- a/Thur 20 Feb/ACE_ClassML Pipeline.ipynb +++ b/Thur 20 Feb/ACE_ClassML Pipeline.ipynb @@ -24,14 +24,15 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "#import the necessary libraries\n", "import pandas as pd\n", "import numpy as np\n", - "import matplotlib.pyplot as plt\n", + "import matplotlib.pyplot as plt # like this\n", + "# from matplotlib import pyplot, plt.plot.scatter(x,y)\n", "import seaborn as sns \n", "\n", "#let's remove the annoying warnings from our cells.\n", @@ -41,7 +42,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -58,7 +59,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -77,16 +78,7 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "pd.read" - ] - }, - { - "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -202,7 +194,7 @@ "4 2.288 33 1 " ] }, - "execution_count": 6, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -210,7 +202,7 @@ "source": [ "#let's read in the data\n", "data = pd.read_csv('diabetes.csv')\n", - "data.head(5)" + "data.head(5)\n" ] }, { @@ -228,7 +220,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -237,7 +229,7 @@ "(768, 9)" ] }, - "execution_count": 7, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -252,7 +244,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -263,7 +255,7 @@ " dtype='object')" ] }, - "execution_count": 8, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -286,7 +278,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -304,7 +296,7 @@ "dtype: object" ] }, - "execution_count": 9, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } From f1459a7c9f42ddf6cf20670af8ba43f37df108f2 Mon Sep 17 00:00:00 2001 From: Tendo1434 <58722184+Tendo1434@users.noreply.github.com> Date: Wed, 11 Mar 2020 12:21:28 -0400 Subject: [PATCH 12/29] Add files via upload --- Assignment Colab/nsangi-olga-tendo.ipynb | 2360 ++++++++++++++++++++++ 1 file changed, 2360 insertions(+) create mode 100644 Assignment Colab/nsangi-olga-tendo.ipynb diff --git a/Assignment Colab/nsangi-olga-tendo.ipynb b/Assignment Colab/nsangi-olga-tendo.ipynb new file mode 100644 index 0000000..2fa692c --- /dev/null +++ b/Assignment Colab/nsangi-olga-tendo.ipynb @@ -0,0 +1,2360 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", + "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/kaggle/input/ace-class-assignment/Test.csv\n", + "/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\n" + ] + } + ], + "source": [ + "# This Python 3 environment comes with many helpful analytics libraries installed\n", + "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", + "# For example, here's several helpful packages to load in \n", + "\n", + "import numpy as np # linear algebra\n", + "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "\n", + "\n", + "# Input data files are available in the \"../input/\" directory.\n", + "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", + "\n", + "import os\n", + "for dirname, _, filenames in os.walk('/kaggle/input'):\n", + " for filename in filenames:\n", + " print(os.path.join(dirname, filename))\n", + "# Any results you write to the current directory are saved as output.\n", + "import warnings\n", + "warnings.filterwarnings('ignore')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Naming the Training and test dataset using." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0", + "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a" + }, + "outputs": [], + "source": [ + "Train = pd.read_csv(\"../input/ace-class-assignment/AMP_TrainSet.csv\")\n", + "Test = pd.read_csv(\"../input/ace-class-assignment/Test.csv\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Confirming that the data has been read in and assigned to variables Train and Test" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n", + "0 5.0 0.000 0.951 74.842 \n", + "1 4.0 5.405 0.931 71.595 \n", + "2 5.5 5.405 0.873 73.595 \n", + "3 5.0 4.167 0.895 66.250 \n", + "4 7.5 8.537 0.932 64.720 \n", + "5 5.0 7.692 1.030 78.949 \n", + "6 3.0 6.897 0.930 78.586 \n", + "7 2.0 5.882 0.868 76.588 \n", + "8 7.0 2.632 0.857 60.447 \n", + "9 9.0 0.000 0.911 65.808 \n", + "\n", + " FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n", + "0 0.975 -3.663 0 0.282 \n", + "1 0.957 -4.011 1 0.600 \n", + "2 0.961 -2.512 0 0.593 \n", + "3 0.999 -1.362 0 0.614 \n", + "4 0.979 -2.091 0 0.616 \n", + "5 0.976 -3.091 1 0.511 \n", + "6 0.957 -3.544 1 0.385 \n", + "7 0.949 -5.832 0 0.154 \n", + "8 1.012 -0.292 0 0.188 \n", + "9 1.049 -3.888 0 0.361 \n", + "\n", + " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 CLASS \n", + "0 73.444 5.661 1.041 1 \n", + "1 68.222 6.537 1.453 1 \n", + "2 69.444 4.934 1.722 1 \n", + "3 67.222 4.316 1.382 1 \n", + "4 72.944 4.540 1.539 1 \n", + "5 78.778 5.992 1.091 1 \n", + "6 78.222 6.284 1.467 1 \n", + "7 76.588 6.479 1.086 1 \n", + "8 64.333 3.849 1.925 1 \n", + "9 63.222 6.327 1.216 1 " + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Train.head(10)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Dimensions of the data train set\n", + "### Checking for the number of rows and columns in the data sets" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(3038, 12)" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Train.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Establishing the attributes in the train data set" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", + " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", + " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", + " 'CLASS'],\n", + " dtype='object')" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Train.columns" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Establishing the data types for each attribute in the train data set. This helps in finding out which column has data types like strings that may need to be converted to foating points or integers to represent categorical or ordinal values. This can be done using df.dtype method or the df.info() method as shown in the two cells below, tho the df.info() is more informative." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "FULL_Charge float64\n", + "FULL_AcidicMolPerc float64\n", + "FULL_AURR980107 float64\n", + "FULL_DAYM780201 float64\n", + "FULL_GEOR030101 float64\n", + "FULL_OOBM850104 float64\n", + "NT_EFC195 int64\n", + "AS_MeanAmphiMoment float64\n", + "AS_DAYM780201 float64\n", + "AS_FUKS010112 float64\n", + "CT_RACS820104 float64\n", + "CLASS int64\n", + "dtype: object" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Train.dtypes" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 3038 entries, 0 to 3037\n", + "Data columns (total 12 columns):\n", + "FULL_Charge 3038 non-null float64\n", + "FULL_AcidicMolPerc 3038 non-null float64\n", + "FULL_AURR980107 3038 non-null float64\n", + "FULL_DAYM780201 3038 non-null float64\n", + "FULL_GEOR030101 3038 non-null float64\n", + "FULL_OOBM850104 3038 non-null float64\n", + "NT_EFC195 3038 non-null int64\n", + "AS_MeanAmphiMoment 3038 non-null float64\n", + "AS_DAYM780201 3038 non-null float64\n", + "AS_FUKS010112 3038 non-null float64\n", + "CT_RACS820104 3038 non-null float64\n", + "CLASS 3038 non-null int64\n", + "dtypes: float64(10), int64(2)\n", + "memory usage: 284.9 KB\n" + ] + } + ], + "source": [ + "Train.info()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Statistical summary of the data in each column.\n", + "### This helps understand the distribution of each column as this method returns values like percentiles,standard deviation, minimum and maximum values of each attribute. This way you can also find out if you have negative values in any attribute. This also helps in understanding the scales at which each attribute is at." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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count3038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.000000
mean2.0602378.5215200.97141073.6687600.994007-2.4329270.08854515.68323373.6508285.9113611.2352550.500000
std3.8199297.5866520.1074138.5274890.0313331.7072230.28413311.5756659.1660920.6936890.2100120.500082
min-16.0000000.0000000.68400042.7500000.866000-10.4320000.0000000.04100042.7780003.5330000.7850000.000000
25%0.0000002.5160000.89500068.2940000.974000-3.6060000.0000005.58750067.5560005.4592501.0820000.000000
50%2.0000007.1430000.96300074.0595000.994000-2.2965000.00000014.98850073.6970005.9255001.1840000.500000
75%4.00000013.1580001.04100079.3437501.011000-1.2832500.00000026.80775079.7780006.3820001.3510001.000000
max30.00000046.6670001.451000101.6820001.1960003.5760001.00000051.280000103.1670008.6620002.1920001.000000
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" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n", + "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", + "mean 2.060237 8.521520 0.971410 73.668760 \n", + "std 3.819929 7.586652 0.107413 8.527489 \n", + "min -16.000000 0.000000 0.684000 42.750000 \n", + "25% 0.000000 2.516000 0.895000 68.294000 \n", + "50% 2.000000 7.143000 0.963000 74.059500 \n", + "75% 4.000000 13.158000 1.041000 79.343750 \n", + "max 30.000000 46.667000 1.451000 101.682000 \n", + "\n", + " FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n", + "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", + "mean 0.994007 -2.432927 0.088545 15.683233 \n", + "std 0.031333 1.707223 0.284133 11.575665 \n", + "min 0.866000 -10.432000 0.000000 0.041000 \n", + "25% 0.974000 -3.606000 0.000000 5.587500 \n", + "50% 0.994000 -2.296500 0.000000 14.988500 \n", + "75% 1.011000 -1.283250 0.000000 26.807750 \n", + "max 1.196000 3.576000 1.000000 51.280000 \n", + "\n", + " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 CLASS \n", + "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", + "mean 73.650828 5.911361 1.235255 0.500000 \n", + "std 9.166092 0.693689 0.210012 0.500082 \n", + "min 42.778000 3.533000 0.785000 0.000000 \n", + "25% 67.556000 5.459250 1.082000 0.000000 \n", + "50% 73.697000 5.925500 1.184000 0.500000 \n", + "75% 79.778000 6.382000 1.351000 1.000000 \n", + "max 103.167000 8.662000 2.192000 1.000000 " + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Train.describe()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### From the values above, there are no missing values since all counts in each column is equal. We can also observe that there are negative values in some attributes have a minimum values in negatives." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Since this is a classification problem, its important to check out the propotions of the values in the class to be predicted as its possible one class may have more values as compared to the others." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0, 0.5, 'Distirbution')" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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CLASS0.534602-0.598816-0.584111-0.554838-0.260470-0.4532870.2607020.693552-0.4371680.0334320.2676521.000000
\n", + "
" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 \\\n", + "FULL_Charge 1.000000 -0.612996 -0.490977 \n", + "FULL_AcidicMolPerc -0.612996 1.000000 0.794796 \n", + "FULL_AURR980107 -0.490977 0.794796 1.000000 \n", + "FULL_DAYM780201 -0.434603 0.541481 0.548253 \n", + "FULL_GEOR030101 -0.058725 0.115201 0.346139 \n", + "FULL_OOBM850104 -0.283758 0.513344 0.462712 \n", + "NT_EFC195 0.088068 -0.143168 -0.169540 \n", + "AS_MeanAmphiMoment 0.355477 -0.431590 -0.426097 \n", + "AS_DAYM780201 -0.365374 0.449621 0.456260 \n", + "AS_FUKS010112 -0.090570 0.002334 0.032958 \n", + "CT_RACS820104 0.232929 -0.213543 -0.403599 \n", + "CLASS 0.534602 -0.598816 -0.584111 \n", + "\n", + " FULL_DAYM780201 FULL_GEOR030101 FULL_OOBM850104 \\\n", + "FULL_Charge -0.434603 -0.058725 -0.283758 \n", + "FULL_AcidicMolPerc 0.541481 0.115201 0.513344 \n", + "FULL_AURR980107 0.548253 0.346139 0.462712 \n", + "FULL_DAYM780201 1.000000 0.010118 0.334778 \n", + "FULL_GEOR030101 0.010118 1.000000 0.319157 \n", + "FULL_OOBM850104 0.334778 0.319157 1.000000 \n", + "NT_EFC195 -0.090058 -0.230417 -0.230561 \n", + "AS_MeanAmphiMoment -0.408793 -0.160269 -0.336297 \n", + "AS_DAYM780201 0.894191 -0.029085 0.275640 \n", + "AS_FUKS010112 0.055915 0.040480 -0.452769 \n", + "CT_RACS820104 -0.326792 -0.151935 0.155304 \n", + "CLASS -0.554838 -0.260470 -0.453287 \n", + "\n", + " NT_EFC195 AS_MeanAmphiMoment AS_DAYM780201 \\\n", + "FULL_Charge 0.088068 0.355477 -0.365374 \n", + "FULL_AcidicMolPerc -0.143168 -0.431590 0.449621 \n", + "FULL_AURR980107 -0.169540 -0.426097 0.456260 \n", + "FULL_DAYM780201 -0.090058 -0.408793 0.894191 \n", + "FULL_GEOR030101 -0.230417 -0.160269 -0.029085 \n", + "FULL_OOBM850104 -0.230561 -0.336297 0.275640 \n", + "NT_EFC195 1.000000 0.178683 -0.036844 \n", + "AS_MeanAmphiMoment 0.178683 1.000000 -0.322378 \n", + "AS_DAYM780201 -0.036844 -0.322378 1.000000 \n", + "AS_FUKS010112 0.145924 0.025580 0.045562 \n", + "CT_RACS820104 0.080898 0.171524 -0.256060 \n", + "CLASS 0.260702 0.693552 -0.437168 \n", + "\n", + " AS_FUKS010112 CT_RACS820104 CLASS \n", + "FULL_Charge -0.090570 0.232929 0.534602 \n", + "FULL_AcidicMolPerc 0.002334 -0.213543 -0.598816 \n", + "FULL_AURR980107 0.032958 -0.403599 -0.584111 \n", + "FULL_DAYM780201 0.055915 -0.326792 -0.554838 \n", + "FULL_GEOR030101 0.040480 -0.151935 -0.260470 \n", + "FULL_OOBM850104 -0.452769 0.155304 -0.453287 \n", + "NT_EFC195 0.145924 0.080898 0.260702 \n", + "AS_MeanAmphiMoment 0.025580 0.171524 0.693552 \n", + "AS_DAYM780201 0.045562 -0.256060 -0.437168 \n", + "AS_FUKS010112 1.000000 -0.445284 0.033432 \n", + "CT_RACS820104 -0.445284 1.000000 0.267652 \n", + "CLASS 0.033432 0.267652 1.000000 " + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Train.corr(method='pearson')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## From the summary above, AS_DAYM780201 and FULL_DAYM780201 are the strongest positively correlated with a correlation of 0.894191 while FULL_AcidicMolPerc and FULL_Charge are the strongest negatively correlated attributes. This correlation can further be observed by plotting a heat map using seaborn to show the correlation of attributes with each other as shown below" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize= (10,10))\n", + "sns.heatmap(Train.corr(method = 'pearson'), cmap='Purples', robust=True, square=True, annot= True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Using visualisation to understand the data at hand. Histograms, Density plots and Box and whisker plots are some of the plots used to understand the attribute distribution.\n", + "## Histograms were used." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Using Histograms" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Train.hist(figsize=(10,10))\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## From the histograms above, we can observe that attributes AS_MeanAmphiMoment, AS_DAYM780201, AS_FUKS010112, FULL_DAYM780201, FULL_GEOR030101, FULL_AURR980107,FULL_CHARGE have a normal. We can also tell from these plots that attribute CT_RACS820104 and FULL_AcidicMolPerc are skewed to the right. We can also tell that attributes NT_EFC195 and CLASS are categorical attributes. This can also be observed using density plots as shown below." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Using Density plots\n", + "### With the density plot, we can easily make comparisons between variables in each column because the plot is less cluttered." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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UumOdvda+VwBfKqXyHOu/BKYATc+YrNWQW1RBr5iaN7XAAAuRoVZdDaq1mtVqpU+fPq07SOkZeHIsXP4YnPsbyDkAL02Aa1+DwbNqbvvBXNi1wvj5qn/AqNtad27N7zkKBrYA/YCXlVK67roWpRQHTh9ger/pzdrP2RlhV+4unayZzJvVoO7Mg9iqff12HsQ2lFtcQWx43XY/UWFWXbKm+QabMbgqQY4vFZ0cswwU17qmM1ONRG3CHyFxPKz9K5QXoXVsSqkqpVQKxowgY0SkRndHfZ+A48XHKakscbu9mlPfLn2xWqzszt3tpcg0d3kzWXNnHsRW7auUek0pNUopNSouLq5ZwXUEdrvidEndalCAyLAgzuiSNc0X2EqNZ6tjSqOQSLBYoSSn5nbb3zOqPi/8LVz6ZyjJhd0ft22sms9SSp0BvsGoham+vMPfJ1ydC7o0L1mzWqwMiBrArrz2M1mKv/JmsubOPIje2FdzyC815gWN6VR3QMMuoVYKSnXJmuYDKoqNZ6tjNH8Ro3SteslaVSXsXAEDr4TgcOg1FqISIU23jOjIRCRORLo4fg4FJgN7zI3K9xzOPwxAn8jmN1kYHDOY3bm7dScDk3kzWXNnHsSGfA5cLiJRIhIFXO5YpjWDa17QeqpBI0OtnNHJmuYLnCVrQdXaVobFQnHu2d+Pp0FpHgy6yvhdBIbOgPR1Rps3raPqDnwtIj9i3HO+VEp9YnJMPiejMIPI4EgigyObve/g6MEUVBRwrFiXl5jJa8maO/MgishoEckEbgBeFZGdjn3zgL9iXHybgUecnQ009+UWGYN51lsNGmolXydrmi+wOUvWOp1dVrtk7ch647n3RWeX9bvMGDz30DdeD1HzTUqpH5VS5yqlhiulhiqlHjE7Jl90tOAoPcN7Nr1hPZJjjGnfdLs1c3l1UFyl1CpgVa1lD1b7eTNGFWd9+74JvOnN+No75+wF9VaDhhnVoHa7wmJp5YCmmtYaFY4OBtZqk5p3ioXTh8/+fuR7iOkHEdUmoE4YDcGRcGANDLmmbWLVND90tPAow+OGt2jf/lH9CZAAduXuYnLvyR6OTHOXnhu0HWuqGtSuoLBcDzyqmcxVDVq9ZK2rMdaaUsZUVEe/h94X1twvIBD6ToADXxnbaZpWh63KxvHi4/SK6NWi/YMDgknqkqQ7GZhMJ2vtWG5R3XlBnZwD4+pOBprpXNWg1dqsdellDOlRnAOndkFZfs0qUKd+k6DwGGTvbZtYNc3PHCs+hl3Z6RnRsmpQMNqt6U4G5tLJWjuWV1xO51rzgjo5kzXdbk0zXX3VoFGJxvPpdKMKFIweoLX1vcR41u3WNK1eGYXGkKW9OresZA2MHqF5ZXmcLDnpqbC0ZtLJWjuWU1xBTHjd9mpwNlk7owfG1czmGhS3WjVojWRtHUT2hKh6RlCPSoSoPnDoay8HqWn+6WjBUYBWlaw5ZzLYmbPTIzFpzaeTtXYsr6iCmHp6ggJ0cVSN6pI1zXS2EmMS94Bq71VnYpZ3yChZq68K1CnpUmMIjyr9Xta02jIKMwgNDG3WBO61DYoeRKAE8lPOTx6MTGsOnay1Y/VN4u7kKlkr1bMYaCarKDGG7ag+wbQ1FKL7GrMWFGdDYiPJWt9LjcndMzd7P1ZN8zMZhRn0jOjZrAncawsOCGZA9AB25O7wYGRac+hkrR3LLS6vtyco6DZrmg+xldQcENep90Vw5ojx84ArG96/z3ijZE63W9O0OjIKM1rcE7S6oTFD2ZmzE7uyeyAqrbl0stZOGfOC2uodYw0gxGohKNCikzXNfLaSmp0LnEbOhaBwGHMHhDcyp2NoFJxzLhzU7dY0rboqe5WrZK21hsYOpchWRHpBeusD05pNJ2vtlHNe0IaqQUXEmMVAdzDQzGYrrTl7gVPP0XDfIZj6dNPH6HspZG0xhvjQNA2AUyWnsNlt9Ozc+mRtWOwwAHbk6KpQM+hkrZ3KLTammmqoGhT0lFOaj6gorr8aFCCw/pLhOpIuNaaeOvyd5+LSND/nGrbDA9WgfSL7EBYYppM1k+hkrZ1yDojbUDUoQBedrGm+oKFq0OZIGGMMqntwrWdi0rR24Ghh64ftcAqwBDA0dihp2WmtPpbWfG4layKyXER+JiI6ufMTzqmmGqoGBaNkTY+z1jIzZszg008/xW7XjW1bzVZSfzVocwQGQdJE2POpMT2V5nf0fcbzMgozsFqsxIfFN72xG0bGj2RP3h4KKwo9cjzNfe5eFK8ANwH7ReQJERnkxZg0D3Ama7G6GtQr7rzzTt5//3369+/P/fffz549e9zaT0SmiMheETkgIvfXsz5YRJY61m8SkcRa63uJSJGI/MEjL8QXVDTQG7S5hlwLRScgY2Prj6WZQd9nPCyjMIMe4T0IsAR45Hij40djV3a2ndrmkeNp7nMrWVNKrVFK/RwYCaQDX4rI9yJym4hYvRmg1jJ5znlBGytZC7PquUFbaPLkybz33nts3bqVxMRELrvsMi688ELeeustbLb6/09FJAB4GbgSSAZuFJHkWpv9EjitlOoHPAc8WWv9c8BnHn0xZvNENSjAgCkQGAI7P2z9sbQ2p+8znpdZmElCRILHjjc8bjhWi5XUE6keO6bmHreLm0UkBrgVuB3YBjyPcVF96ZXItFbJdcwLag1o+E8cGWqlsLySyipdbdQSubm5LFy4kH//+9+ce+65/O53v2Pr1q1cdtllDe0yBjiglDqklKoAlgDTa20zHXjb8fMyYJI4RrMUkWuAQ0D7mvPFE9WgAMHh0P8y2PURVFW2/nham9P3Gc/KKsqiR3gPjx0vJDCEYbHD2HxCD0Dd1txts/Zf4DsgDLhaKTVNKbVUKXU3EO7NALWWyS2uILaBeUGdnAPjFpTpG1tzXXfddYwfP56SkhI+/vhjVq5cyaxZs3jxxRcpKipqaLceQEa13zMdy+rdRilVCeQDMSLSCfgj8HBjcYnIHSKSKiKp2dnZLXhlJvBUNSjA8FlQdBIOfuWZ42ltRt9nPCu/PJ+CigKPdC6oblS3UezK20VRRYOfc5oXuFuy9m+lVLJS6m9KqeNgtK0BUEqN8lp0WovlFpU32rkAoEuYczJ3PeVUc91+++3s2rWLP/3pT3Tv3h2A8nJjuJTU1AarCOqb70W5uc3DwHNKqUY/IZVSrymlRimlRsXFNTKQrK+osoHdZvTk9IQBU6BTHGx9xzPH09qSvs94UFZRFgAJ4Z6rBgUY3U23WzODu8nao/Us2+DJQDTPyilyv2RNdzJovgceeKDOsrFjxza1WyZQ/WtuAnCsoW1EJBCIBPKA84GnRCQd+D3wZxH5TQtC9y22EuPZU8lagBVSboK9n0HhCc8cU2sr+j7jQc5krUeE56pBAUbEjSDQEsjmk7oqtC0FNrZSRLphVMuEisi5nP3W3xmjqFprYzabjczMTMrKyhrd7s9jIwgNCmD37t0NbhNTaef1ad3hTBa7i/WNzR3Z2dmcOnWK/Px8li9fTlBQEPHx8ZSUlFBSUtLU7puB/iLSB8gCZmP0fqtuJTAX4yZ1PbBWKaWA8c4NRGQBUKSUeskzr8pEFc5kzQMdDJzOvQXWPw/b34fx93juuJpXtOf7jLuf197QpaIL/0j+B1Unqth9suH7QEu8MOQFgEbvL9pZISEhJCQkYLW2vJ9Mo8kacAVGY88E4O/VlhcCf27xWbUWy8zMJCIigsTERBztzuuwK4UtK5/4ziHEdw5p8FhltirkZCG9osPoEtZ4lalm+OGHH1i4cCGnTp3ipZdewmazUVVVRVxcHI8//nij+yqlKh2lYZ8DAcCbSqmdIvIIkKqUWgm8ASwSkQMYJWqzvfySzOUsWQvyQAcDp9h+xiTwW9+Bi34PFj1sl49r8X1GRHoC7wDdADvwmlLqee+E2XzufF57y7GiY0RURDAo2vMjoJwoPkFeWR4Dowdi0cPiNUopRW5uLpmZmfTp06fFx2k0WVNKvQ28LSIzlFLLW3wWzWPKysqavPCr7EYzqEBL4x8OAY71lfbazaa0hsydO5e5c+eyfPlyZsyYgVKKPXv2MHjwYLf2V0qtAlbVWvZgtZ/LgBuaOMaC5kfuozxdDeo08hb48P/BkfXQZ3zT22umaeV9phK4Vym1VUQigC0i8qVSapfnI20+dz6vvcVmt2G1eGfEk7DAMHJVLmWVZYR5+tptZ0SEmJgYWtvhq6lq0JuVUu8CiSJSpz5BKfX3enbTvKypC985FEdggHvJWpVO1tz27rvvcvPNN5Oens7f/268/U+ePEl8vDFC+D336Gq3ZqnwUrI2eBqsug+2vq2TNR/XmvuMoyPCccfPhSKyG6NK1SeSNWj689pbKqoqCAlsuGalNUIdzRZKKkt0suYGT7wHmqoGddZN6G7TfqTSVbLWePG0RQSLiE7WmqG4uBigxvAcxcXFFBbq6VdaxFUN6uEP/KAwGD7TqAq9Mg/Coj17fM2TPHKfccz2cS6wqZXx+D2lFDa7jc6Wzl45vtVixRpgpcRWAh5sbqo1QinVLh7nnXee6gh27drV5Da5ReUqLeO0KquobPp4x/LV0dziZsVgsVjUiBEjXI/Dhw+rt956S82bN6/GdhMmTFCbN29WSinVu3dvlZ2dXWN9ffs0pLCwUN1xxx2qb9++Kjk5WY0fP15t3LhRHT58WA0ZMqRZ8XtafX8TjDZo+ppoyu5PlHqos1JZ2zx/7GNpxrE3/svzx9aazZvXBEaitwW4rp51dwCpQGqvXr3a6uUqpdz7vPaG8spytSN7h8otzfXa53VGQYbam7u3wRi2bt2qALV69WrXsvo+rx966CH19NNPK6WUmjt3rkpMTFQjRoxQw4cPV2vWrKkR34ABA9Tw4cPVqFGj1LZtZz8zlixZooYNG6aSk5PV/PnzXcuPHDmiLrnkEpWSkqKGDRumPv30U9e6xx9/XCUlJakBAwbUiPG2225TcXFxdeLMzc1VkydPVv369VOTJ09WeXl5SimlnnrqKdf/7ZAhQ5TFYlG5ubl1/j9ae59wd1Dcp0Sks4hYReQrEckRkZu9kTxqrVdpd1aDNv3nDbA0v2QtNDSU7du3ux6JiYktCbNZbr/9dqKjo9m/fz87d+5k4cKF5OTktPq4lZUtGxD4vvvuo6CgAJvNxm233UZsbCzvvvtuq+PpcLxVDQrQfTh0T4Etb4PSpce+rqX3GcdUVMuB95RS/629Xvnb2IMeYLMbwzEFWYK89nkdHBCMzW6j0l7/Z+jixYsZN24cixcvbtZxn376abZv384//vEPfv3rX9dY995775GWlsZdd93F/PnzAWMmmfnz5/PVV1+xc+dOTp48yVdfGYNiP/roo8ycOZNt27axZMkS7rrrLgB27drFkiVL2LlzJ6tXr+auu+6iqqoKgFtvvZXVq1fXieuJJ55g0qRJ7N+/n0mTJvHEE08AMH/+fNf/7d/+9jcmTJhAdLTnS/KbqgZ1ulwpdZ+IXIsxDtQNwNeAvjuZ6OGPd7LrWEGd5RWVdmx2O52Cmv7zltmMN2iI1ZjoN/mczjx09RDPBtpKBw8eZNOmTbz33ntYHFW7ffv2pW/fvqSnp1NVVcWvfvUrvv/+e3r06MFHH31EaGgor7/+Oq+99hoVFRX069ePRYsWERYWxq233kp0dDTbtm1j5MiR3H///dx0003k5uYyevRoVq9ezZYtW1wJ2AsvvEBFRQXnn38+//znPwkICOCLL77gqaee4sMPP6Rbt26sWrWKSy+9lJtv1t9hmsVb1aBO582FT/4HsrZCwnneOYfmKc2+zzimYnsD2K18vA31kz88yZ68PR495qDoQfxxzB/rLK+oMgY6DwrwXi//0ECj/rO8spzAWvcapRTLli3jyy+/ZPz48ZSVlRES0rz2c2PHjiUrK6vBdU8//TQAhw4dYsCAATgT8cmTJ7N8+XImTZqEiFBQYNwj8/PzOeeccwD46KOPmD17NsHBwfTp04d+/frxww8/MHbsWC6++GLS09PrnPOjjz7im2++AYyOZpdccglPPllz6ubFixdz4403Nut1usvdPrfOLiVTgcVKqTyvRKN5hAKk3oHwG96+OUpLS0lJSSElJYVrr722mXs33848vbJ4AAAgAElEQVSdO0lJSSEgIKDe9fv372fevHns3LmTLl26sHy50aHsuuuuY/PmzaSlpTF48GDeeOMN1z779u1jzZo1PPvsszz88MNMnDiRrVu3cu2113L06FHAGENo6dKlrF+/nu3btxMQEMB7770H4JqsfdWqVUydOtUr36Q6BG/1BnUaer1x7G2LvHN8zZNacp+5CJgDTBSR7Y7HVK9F6Ccq7EayFmgJ9NrntbPzQmlVaZ1169evp0+fPiQlJXHJJZewatWqOts0ZfXq1VxzzTVNruvXrx979uwhPT2dyspKVqxYQUaGMavfggULePfdd0lISGDq1Km8+OKLAGRlZdGz59nxyRMSEhpMDJ1Onjzpmq2me/funDp1qsb6kpISVq9ezYwZM5r9Wt3hbsnaxyKyBygF7hKROKDtR/nTamioBOxQdhF2Bf26Nt1eNzOvhMLySgZ3d78hqrNYvbqGeru0RU+oPn36kJKSAsB5553n+la0Y8cOHnjgAc6cOUNRURFXXHGFa58bbrjBlfytW7eODz/8EIApU6YQFRUFwFdffcWWLVsYPXo0YCSpXbt2BeDqq69m0KBBhIaGcvfdd5Odnd3sb44aUGF02PDoOGvVhXSGgVONyd2nPm3McKD5qmbfZ5RS66h/ijafU18JmLfYqmxYA6xYxOK1z+tASyCBlkDKKuv+iRYvXszs2cYQkbNnz2bRokVcd911bp13/vz53HfffZw6dYqNGzfW2O7nP/85xcXFVFVVsXXrVgCioqJ45ZVXmDVrFhaLhQsvvJBDhw654rj11lu599572bBhA3PmzGHHjh3Otowtfu31+fjjj7nooou89sXdrZI1pdT9wFhglFLKBhQD070SkdZqlXbV5BhrTi1ps1afmJgYTp8+XWNZXl4esbGxrT72kCFDSEtLw+5oi1dbcPDZabUCAgJc7dBuvfVWXnrpJX766SceeuihGqOId+p0Njmo78J1Lp87d66rPcLevXtZsGABYLRf2LBhA6mpqVitVjp16sRHH33U2pfa8dhKQALAi9U1DLkWSvPg8P957xxaq+n7jOdU2CsIsjR8TXnq8zokMISyqprJWlVVFcuXL+eRRx4hMTGRu+++m88++4zCwkK3zvv0009z4MABHn30UebOnVtj2/fee4/Dhw9z0003MW/ePNfyq6++mk2bNrFhwwYGDhxI//79AXjjjTeYOXMmYFSdlpWVkZOTQ0JCgqv0DYzBi51VpA2Jj4/n+PHjABw/ftz1xd1pyZIlXqsCBferQQEGA7NE5BaMaXAu905IWmtVVqkmx1hzCrAIdqWwtzJhGz16NOvXr+fECWPaqtTUVMrLy2sUNbdUUlISo0aN4qGHHnIlVvv3728yOSosLKR79+7YbDZX9WV9xo0bxwcffADAF1984fowmTRpEsuWLXMVd+fl5XHkyBHXfs5q0o8++ohly5bxxRdftOp1dkgVJUapmjdLYPtNhqAI2Fmn7bnme/R9xgNsVbZG26t56vM6JCCEisoK7OrsF+k1a9YwYsQIMjIySE9P58iRI8yYMYMVK1YQHh5O9+7dXR0A8vLyWL16NePGjatxXIvFwu9+9zvsdjuff/55jXVWq5VHH32UjRs3uqa7cn5Gnz59mn/+85/cfvvtAPTq1ct1rt27d1NWVkZcXBzTpk1jyZIllJeXc/jwYfbv38+YMWMafa3Tpk3j7bffBuDtt99m+vSz3yPy8/P59ttvayzzNLeqQUVkEZAEbAeqHIsVxjQfmg9RSlFltzc5xppT9VkMgtwsjatPfHw8zz//PFOnTsVutxMeHs7ixYtdHQIAhg8f7vp95syZDB8+nIULF7JixQrXNhs3biQhIaHO8f/9739z77330q9fP8LCwoiJiXE1MG3IX//6V84//3x69+7NsGHDGhwL7aGHHuLGG29k6dKlTJgwge7duxMREUFsbCyPPvool19+OXa7HavVyssvv0zv3r2ZM2cOBw8eJCUlhfz8fLKyshARbrnllpb893VctmLvtVdzsobAoKmw+xP42XMQqKdW80X6PuMZdmWn0l7Z6OwFnvq8/uLbL1CRivKqcleHg8WLF9dpGzdjxgxeeeUV5syZwzvvvMO8efO49957AePzNykpqU6MIsIDDzzAU089VaMJCxhNce69916eeeYZ3njjDX73u9+RlpYGwIMPPsiAAQMAePbZZ/nVr37Fc889h4iwcOFCRIQhQ4Ywc+ZMkpOTCQwM5OWXX3Y1i7nxxhv55ptvXCVwDz/8ML/85S+5//77mTlzJm+88Qa9evXiP//5jyueDz/8kMsvv7xGjY2nSUNVQDU2MkaFTlbubGySUaNGqdTUVLPD8Lrdu3c3OrWRrcrO7uMFnNMllNjw4Aa3cyoss3E4p5ikuHA6BbvbhLF9KS8vJyAggMDAQDZs2MCdd95Zp41HbYMHD2bXrl2ISL1/ExHZopQa5c24m+IX18SyX8KxrfDbbd49z97PYPFsuOk/MEAX1pihqWuiLe4zbX1NNPV57Q1llWUcPHOQhIgEIoMjvXqu8spyDpw5wDnh5xAVEuXVc/m71t4n3L0778CYKPd488LT2lqlm/OCOlkdY7HZqupvD9YRHD16lJkzZ2K32wkKCuL1119vcp+hQ4dy4sQJV+8grYVsJWD13rdRl6SJRlXono91sua79H3GA5xjrHlrXtDqggKCEBHKq8q9fq6Ozt1kLRbYJSI/AK6/ilJqmlei0lqsqsr9AXEBrI62bRU+kqydf/75lJfXvPAXLVrEsGHDvHbO/v37s21b80p2cnJySE5OZsyYMdhsNsLDjZ63K1eu9EaI7VdFMVjbYL6awGDoPxn2rga7HdxsJqC1KX2f8YC2GGPN6YILLqCwpLDG+bz9ed1RuZusLWjJwUVkCvA8EAD8Wyn1RK31wRjtEc4DcoFZSql0xxxvu4G9jk03KqVqDmWs1au5JWsBFgsBFsFW5Rs13Js2+ce0fs5eoQBHjhyhd+/e5gXjz2wl3hu2o7aBP4OdH0JWKvRsvDGxZooFZgfQHlTYK7CIhQCpf1xKT9q0aRPHio5RUFHAwKiBpk1a3xG4lawppb4Vkd5Af6XUGhEJw0jAGiQiAcDLwGUYo1FvFpGVSqld1Tb7JXBaKdVPRGYDTwKzHOsOKqVSmvl6OgSlVIMXhTPpcjdZA6Mq1FbpGyVr/mLChAkcOXKEffv2MXr0aHr37u2arkRrhooS6NS16e08of9lYAmEPZ/oZM0HteQ+4w8a+7z2BucYa211zuCAYKrsVUanBj2OYb080QzT3blBfwUsA151LOoBrGh4DwDGAAeUUoeUUhXAEuqOmTMdeNvx8zJgkujUvFEhISHk5uY2+MevtNsREVcvT3cEBVh8phrUX7z++utcf/313HHHHYSEhJCVldXgaNtaI2zF3ptqqrbQLpA4DvY0fzR1zftaeJ/xaU19XntDU2OseZpzJoPa461pBqUUubm5rR403d1q0HkYydcmx8n3i0hTX4d7ABnVfs8Ezm9oG6VUpYjkAzGOdX1EZBtQADyglPrOzVjbtYSEBDIzM8nOzq53/eniCsoq7ewpcP+NcabURnF5JZW5oV4d7qo9efbZZ1m6dCk33XQTCQkJWK3WOtOPaG6wlXp/6I7qBv4MPpsPOfshtn/bnVdzR0vuMz6tqc9rbzhefJywwDCKg4vb5Hx2ZedE8QmKg4qJCIpok3P6m5CQkHqHpGoOd5O1cqVUhbPQS0QCaXpKyfpu+7X3aWib40AvpVSuiJwHrBCRIUqpGrOWi8gdwB1gDH7XEVitVvr06dPg+lvf+oGconI+uftct4+5+Iej/Omjn/juvkvpGd2GN04/FhkZyYgRIwgKCsJqtVJZWanba7RERRu2WQMYeKWRrO35FMb9vu3Oq7mjJfcZn9bU57Wn5ZTmMPODmfxpzJ+4afBNbXbee5bdw4i4ETw14ak2O2dH426XqG9F5M9AqIhcBvwH+LiJfTKB6sMhJwDHGtrGcWFGAnlKqXKlVC6AUmoLcBAYUPsESqnXlFKjlFKj4uLi3Hwp7VtuUYVb46tVlxRn9GQ8kF3kjZDapQkTJvD4449TWlrKl19+yQ033MDVV19tdlj+Ram2GRS3ui49ofsII1nTfE1L7jNaNZmFmQAkRLSuFKe5BkQPYO/pvU1vqLWYu8na/UA28BPw/4BVwANN7LMZ6C8ifUQkCJgN1B7XYCXgnPzremCtUkqJSJyjgwIi0hfoDxxyM9YOLaeovNnJmnPC94OndLLmrieeeIK4uDiGDRvGq6++ytSpU3n00UfNDsu/VJaDsrddmzWngT+DzM1QpKutfUxL7jNaNVlFWQAkhLdxshY1gPSC9Honddc8w93eoHYRWQGsUEq5VfnuaIP2G+BzjB49byqldorII0CqUmol8AawSEQOAHkYCR3AxcAjIlKJMe3Ir5VSec16ZR2QUqpFyVp0pyCiwqwczG6bNg7tgcVi4ZprruGaa65Bl+q2kK3EeG6LQXGrGzQVvnncmNXgvLlNb6+1iZbcZ7SanCVr54Q3Pim5pw2MGohd2Tl45iBDYoe06bk7ikZL1sSwQERygD3AXhHJFpEH3Tm4UmqVUmqAUipJKfWYY9mDjkQNpVSZUuoGpVQ/pdQYpdQhx/LlSqkhSqkRSqmRSildFO6GvOIKbFWK+M7NS9bAqAo9qKtBm6SUYsGCBcTGxjJo0CAGDhxIXFwcjzzyiNmh+Z8Kx5eDti5Zix8KXXrpqlAf0dr7jHZWZlEmcaFxrh6abWVg9EAA9p3e16bn7Uiaqgb9PXARMFopFaOUisbo0XmRiPyP16PTmuVkgTHod7fOzb9Q+3UN19WgbvjHP/7B+vXr2bx5M7m5ueTl5bFp0ybWr1/Pc889Z3Z4/sVVstbGyZoIDLoaDn0NZQVNb695m77PeEhWUVabt1cD6BnRk9DAUN1uzYuaStZuAW5USh12LnCUft3sWKf5kJMFRnuBri1I1pLiwsktriCvuMLTYbUr77zzDosXL67Rw6tv3768++67vPPOOyZG5odcJWttXA0KkDwNqipg/xdtf26tNn2f8ZDMwsw2b68GYBEL/bv0Z2+eTta8palkzaqUyqm90NGeQA9V7GOcyVq3yOYna/3jjU4G+08WejSm9sZmsxEbG1tneVxcHDabrcn9RWSKiOwVkQMicn8964NFZKlj/SbH1GuIyGUiskVEfnI8T2z9qzGZWSVrAAljIDweduu5XH2Avs94gK3KxoniE/SI6GHK+QdGD2Rv3l7sSg+w7g1NJWuNFbPoIhgf46wGjWtmBwOAAfHGYIb7dFVoo4KCGh4ZvLF1UGMKtiuBZOBGEUmutZlrCjbgOYwp2ABygKuVUsMwelAvakn8PqXCkawFhbf9uS0WGHQV7P/ybByaWfR9xgOOFx9HoUwpWQMYFjuMQlsh6fnpppy/vWuqN+gIEamvUYcAbduCUWvSiYIyYjoFERTo7ogsZ3WPDCE8OFCXrDUhLS2Nzp0711mulKKsrMlu664p2ABExDkFW/X5cqdzdkLrZcBLIiJKqW3VttkJhIhIsFKqvEUvxBeUOz5agk0a9Tx5GqS+AQfXwuCrzIlBA32f8QizxlhzGhE3AoC07DT6dulrSgztWaPJmlLK7yfR7UhOFZQR34L2agAiQr+u4ew/qUvWGtPKydpbMwVb9WqiGcC2+hI1v5rVw+xkrfdFEBoFuz7SyZqJWnOfEZE3gauAU0qpoZ6Lyv9kFBofLT3CzakGTYxMJCIogrTsNK7tf60pMbRnzS+C0XzWiYKyFg3b4TQgPpz9p3TJmhe1Zgo2Y6XIEIyq0f9X3wn8alaPcsd7zaxkLcAKg682hvAo1+97P7UQmGJ2EL7gSOERQgJC6BpmznSqFrEwPHY4adlpppy/vdPJWjtysqC8RZ0LnAbER5BTpHuEelGLp2Bz/J4AfAjcopQ66PVova28EMRiTm9Qp3PnGFNe7fzQvBi0FlNK/R+O66OjO1pwlJ6de2IR827rI+JGcPDMQQor9JcfT9PJWjthq7KTW1xO14iWJ2v9nZ0MdLs1b2nNFGxdgE+BPyml1rdZxN5UXmiUqkl9hYltJGE0xA6Erf7fX0Pr2I4UHKF3RG9TYxgRNwKFYkfODlPjaI90stZOZBeWoxQtbrMG0L+rHr7Dm5RSlYBzCrbdwAfOKdhEZJpjszeAGMcUbPdgzJeIY79+wF9EZLvjYU59h6eUF0Jw3c4abUoERs6BzB/g1G5zY9G8QkTuEJFUEUnNzm6fs1hV2ivJLMqkV2dz26kOjTOaDW7P3m5qHO2RTtbaiROuMdZa3mate2QIEcGB7NfDd3hNK6Zge1Qp1UkplVLt4d8zkZcXmNderboRN0JgCGz8p9mRaF7gV+04W+h48XEq7ZUkdk40NY7OQZ0ZEDWALSe3mBpHe6STtXbiZL5j9oJWVIOKCP3iw9l7QpesaW3AWQ1qtk6xkPJzSFsChSfMjkbTmu1owVEA00vWAMZ0G8P2U9spr/LfUYV8kU7W2omsM6UAJESFtuo4Q8+JZEdWPlX22p0UNc3DfCVZAxg7D6pssOlfZkeiNYOILAY2AANFJFNEfml2TGZIL0gHoHdnc9usAZzf/XzKq8r5MftHs0NpV3Sy1k5kni6lU1AAkaGtm53lvN5RFFdU6dI1zft8KVmLSYLk6fDDv6FEdy70F0qpG5VS3ZVSVqVUglLqDbNjMsPRgqOEBYYRExJjdiicF38eFrGw6fgms0NpV3Sy1k5knSmlR1Qo0sqedSN7RQGw5ehpT4SlaQ3zpWQNYMIfoaIIvn/R7Eg0rVkOnDlAUpekVn/+e0JEUATJ0clsPrHZ7FDaFZ2stRNZp0tJiGr9hNg9o0OJDQ9m6xGdrGle5gu9QauLT4ah18GmV6E41+xoNM1tB84coH9Uf7PDcBnTfQw/Zv9Isa3Y7FDaDZ2stRNZZ0rp0aV17dXA6GRwXu8ubE7XVUGaF9mrjFIsMyZxb8yE+6GyFL5/3uxINM0tOaU55JXl0a9LP7NDcRnfYzyVqpJ1WevMDqXd0MlaO1BYZiO/1EaPVnYucLqgbwyZp0vJyCvxyPE0rY7SM8ZzaJS5cdQWNwCG3QA/vA5F/j0yitYx7D+9H8CnStZSuqYQFRzF2qNrzQ6l3dDJWjvg7AnqiZI1gAuTYgHYcFBXBWleUuoouQ0zv0F0HRffB5VlsF6Xrmm+z5WsdfGdZC3QEsiEnhP4LvM7bFU2s8NpF3Sy1g5knXYkax4qWRsQH05MpyC+P5jjkeNpWh0lji8CYT5WsgYQ2w+Gz4bN/9bjrmk+b0fODrqGdSUm1Le++EzsOZFCWyEbjm8wO5R2QSdr7cCRXKO6sld06zsYgNFubWxSDN8fzEUpPd6a5gUlPlyyBjBhvjHu2rrnzI5E0xr1Y86PjIgbYXYYdYzrMY4uwV1YebD29MdaS+hkrR04mF1EZKiVmE5BHjvmhUmxnCos52C27s2jeYGzZC002tw4GhLdF1JugtS3ID/L7Gg0rV45pTlkFWX5ZLJmDbAytc9U1h5dS355vtnh+D2drLUDB7OLSIrr5NExdi7qZ5R4bNBVoZo3+HKbNaeL54Oyw7dPmB2JptUr7VQagE8mawDX9LsGm93GqsOrzA7F7+lkrR04mF1MUpxnh0DoFR1Gjy6hfK87GWjeUJILAUEQ1MnsSBoW1RvG3AFbF8Gx7WZHo2l1fH/se8ICwxgSM8TsUOo1OGYwg6MHs2TPEt2kppV0subn8kttZBeWk9TVs8mas93ahkO52PU8oZqnFecaVaA+MOJ6oybcZ5T+ffZHsNvNjkbTXJRSfJf1HRd0vwBrQOumGfSmOclzOJR/iPXH1psdil/TyZqf+zHTGK9qcHfPjwR/YVIMZ0ps7D5R4PFjax1c4XHo3N3sKJoW2gUuexgyNsIPr5odjaa5HDhzgOPFxxmfMN7sUBo1JXEKcaFxLNq1yOxQ/JpO1vzc1iNnEIFze3Xx+LHHJjnbremqUM3DCo5B5x5mR+GelJ/DgCnw5UNwarfZ0WgaAJ8d/gyLWJiQMMHsUBplDbBy46Ab+f7Y9+zN22t2OH5LJ2t+buOhXAbGR9A5xPPF4N0jQ+kb20m3W9M8r+AYdD7H7CjcIwLTXjQmnV96M5TqeXM1c9mVnY8PfczYc8YSFxZndjhNmjlwJhHWCF7e/rLZofgtnaz5sZMFZWw6nMtlyfFeO8fYpBg2HcrFVqXb62geUl4I5fn+k6wBhHeFWYvg9BFY9gtjDDZNM8nG4xs5UXyC6UnTzQ7FLZHBkdw69Fa+zviatOw0s8PxSzpZ82PPfbkPEeH68xK8do7x/eMorqhi3X49hIfmIQXHjefO3nvfekXvC+Gqv8PBtbDsNqisMDsirYN6Z9c7RIdEM7HXRLNDcdvNg28mJiSGxzY+pqegagGdrPmpT388zpLNGdw+rg+9Y7w3/MHEQV2JiwjmnQ3pXjuH1sHkHTKeu/QyN46WGHkLTHkCdn8Mi2cZvVo1rQ3tzdvL+qz13Dz4ZoIDgs0Ox21h1jAeHPsgu/N280zqM3ooj2bSyZofSs8p5o/Lf+TcXl34wxUDvXquoEALc8f25uu92fzfvmyvnkvrIHIcjYzjBpgbR0tdcCdMewnS18GrF8O+L8yOSOtAXkl7hbDAMGYOnGl2KM02sddEbh58M+/veZ/HNz2uS9iaQSdrfqa8sop5728lwCK8dNNIrAHe/xPePr4vfeM6cc8H28nIK/H6+bR2LnsvdOoKoT44ibu7Rs6BX3wOQWHw/g2w5OeQe9DsqLR27ofjP/DV0a+4fdjtRAZHmh1Oi8wfPZ9bkm9hyd4l3PzZzbqHqJt0suZn/rZqDzuPFfDsDSPo0SW0Tc4ZYg3gtTmjqKi084uFm8kpKm+T82rtVGYqnHOu2VG0Xo+R8Ov1MOlBox3by2Ng1Xwo0iXQmucVVRTx4PcP0iO8B3OS55gdTotZxML80fN57pLnOFF8gtmfzOa5Lc9xukz3sm6MTtb8yL+/O8TC79P5xUV9mOzFHqD16dc1nFfnjCLjdAk3vraRwzl6gnetBYqyjWrQXuebHYlnBAbB+Hvht9uM9myb34AXUuCbJ6G8yOzotHaivKqc//nmfzhRfIK/jf8bIYEhZofUapN7T2blNSu5Oulq3tzxJpP+M4lbPruFJ394ko8PfkxOqe7UVp1XkzURmSIie0XkgIjcX8/6YBFZ6li/SUQSq637k2P5XhG5wptx+rqKSjuPfrKLRz/dzZVDu/HnqYNMiWNsUgxv3TqGE/llTHz2G658/jvuW5bGkh+OcqqgzJSY/E2HvyZ2/td4HjDF3Dg8LaIbXPUczNsESRPhm8fhhXPhiwdg5wrI2Ayn040ETjes9qimril/l1GYwW2rb2Pj8Y08fOHDnNu1HZRKO0QGR/LIRY/w32n/5eeDfw7A8v3L+fO6PzP5P5OZ99U8Pj30KUUV+ouPeKtHhogEAPuAy4BMYDNwo1JqV7Vt7gKGK6V+LSKzgWuVUrNEJBlYDIwBzgHWAAOUUlUNnW/UqFEqNTXVK6/FW5RSlNnsiBhVjdXZ7YojeSWsO5DDW+sPcyi7mLlje/PAVclt0k6tMacKyliyOYPUI6fZkZVPXrExhMGInl24PDmei/rFEhESyP6TRew+XkBoUAADu0UwrEckseH+03upNURki1JqVK1lHfuaOJMBb1xmzFzwq6/Mjsa7MjbDt0/A4f+DqlpDfASGQFgsdIox2u6FxxvjuDkfnRzPYgFbKVSWOZ7LjTZyodFGe7+waAj0n+upvmvCA8ds8pqqzueuiQZU2ivZk7eHlQdXsmzfMoIDgvnrRX9lcu/JZofmdVX2Kg6cOcBnhz/j40Mfc6rkFAA9I3qSFJlEr8696N25Nz0jetK7c29iQ2MBUBi5jNVixSL+UWnYnGsi0ItxjAEOKKUOOYJaAkwHql9E04EFjp+XAS+JiDiWL1FKlQOHReSA43gbWhLInDc2UV5pB3X2D6oUKIyEyZmuOpc5v/kq1zLl+jJcfT9q7Fdtm+rHrWeZUlBqqyK/xEaFY7DZmE5BRHcKIjQogMKySk4WlFFSYdyHB3WL4M1bRzFxUNtWfTaka+cQfjupP2C8pn0ni/hy1wm+3H2Kpz/fy9Ofn20wKlKzICEqzEpgtWRTHNsIgkWMCeSd+zmXOwUFWgixWggJDCDAYv4E4MN6RPLAVcnN2cU3ronKClh0LcYFoRp/hka2odrvNH28M0cgIBhuXNLskP1Oz9Fw83KoKIHcA8ZcqMXZUJwDJTnGc3EOFJ+CkzuNZ3tl889jDTMSt9AoI3ETi+MR4Hhu4+uk11iY+L9teUZ3rqkm5Zfn8/uvf+/4HK/22e743XXfcLzvz95HjHXVf3dt19j6atvVPmeVquJE8QlsdhuBEsi0ftO4c8SddOvUrVn/Mf4qwBLAwOiBDIweyG9H/pbtp7az+cRm9p7ey+H8w2w4voHyqobbTVvEQrg1nMjgSDoHda53eBPXfQap8bs3jOsxjl8M/UWrj+PNZK0HkFHt90ygdkMV1zZKqUoRyQdiHMs31tq3zkSCInIHcAdAr16Nj9kkOD67sLg+v5zJQPW/k4i4EgjXfrWW4din5nbiSjCcvyNn9z97LOM5xBpAZJiVyFArVVWKY/llnCmpoKSiil7RYUwYEEdy986k9OrCgPiIRl+bmUSEgd0iGNgtgt9M7M/JgjK2HT1DSUUlibGdSO7emfJKO7uPF7AjK5/DOcXYXZ9LRoJbPdm1q+ofiMaHmoiglKKiyk6ZzU6ZrYqqswcxTQsi8I1rwvVGFrBYqi2Tus+NravxTNPbDr4KzrsNovvUH1d7FBQG3Ycbj8bY7cY0VkUnHUldtnFhBAaDNdQojQsMAVuxsV1JnuGRzv0AACAASURBVPFc/VFVAfYqUPZqj7a+Ttr8umzymmrefUKwWCzG57nr/U+N3437gZy9PJz/qiUA9a2vvm/15KDOviJM7j2ZAVEDGN9jvN/2+vQEi1gYGT+SkfEjXcvsys6pklMcLTjK0cKj5JXl1fg/LK0spaC8gIIK4+EcHqRGwk2thNmL14mnju3NZK2+VLV21A1t486+KKVeA14Do3i7oUAW/bKdNGb2A/GdQ5gytOY3wBBrABf0jeGCvjEmReUzfOOaCLDCbZ82GqjWxiwWR7Voh79GmqvJ68KdayIyOJK3przl+eg0j7OIhW6dutGtUzfGdB9jdjhtxpsVu5lAz2q/JwDHGtpGRAKBSCDPzX01zd/oa0LTPEtfF1qH4M1kbTPQX0T6iEgQMBtYWWublcBcx8/XA2uVUWa4Epjt6BnXB+gP/ODFWDWtLehrQtM8y51rStP8nteqQR3tbX4DfA4EAG8qpXaKyCNAqlJqJfAGsMjRWDoP40LDsd0HGI1EK4F5jfV60zR/oK8JTfOshq4pk8PSNI/z2tAdbU1EsoEjJpw6FvD10ft0jK3X3Ph6K6XivBWMOxq4Jtrb/3Nb0/G1nK9eE97iy38Ld/n7a/D1+N2+JtpNsmYWEUn19NhBnqZjbD1fj89dvv46dHyt4+vxdSTt4W/h76/B3+Ovzj9GjtM0TdM0TeugdLKmaZqmaZrmw3Sy1nqvmR2AG3SMrefr8bnL11+Hjq91fD2+jqQ9/C38/TX4e/wuus2apmmapmmaD9Mla5qmaZqmaT5MJ2uapmmapmk+TCdrLSQiT4vIHhH5UUQ+FJEujuWJIlIqItsdj3+ZHOcUEdkrIgdE5H4zY3HE01NEvhaR3SKyU0R+51i+QESyqv2/TTU5znQR+ckRS6pjWbSIfCki+x3PUWbG2Bz+8H71pfeqP7xP29t71F819b4VkVtFJLvae+Z2M+JsiIi8KSKnRGRHA+tFRF5wvL4fRWRkfduZxY34LxGR/Gr//w+2dYweoZTSjxY8gMuBQMfPTwJPOn5OBHaYHZ8jlgDgINAXCALSgGSTY+oOjHT8HAHsA5KBBcAfzP4/qxZnOhBba9lTwP2On+93/s394eHr71dfe6/6w/u0vb1H/fHhzvsWuBV4yexYG3kNFwMjG/ocAKYCnwECXABsMjvmZsZ/CfCJ2XG29qFL1lpIKfWFUqrS8etGjAmEfc0Y4IBS6pBSqgJYAkw3MyCl1HGl1FbHz4XAbqCHmTE1w3TgbcfPbwPXmBhLs/jB+9Wn3qt+/D712/eon/Kp921LKKX+D2Nqu4ZMB95Rho1AFxHp3jbRNc2N+NsFnax5xi8wvnk49RGRbSLyrYiMNysojJtLRrXfM/GhG46IJALnApsci37jKGZ/0weqbxTwhYhsEZE7HMvilVLHwbiZA11Ni651fPH96rPvVR9+n7bn96i/cPd9O8PxnlkmIj3bJjSP8dlrsxnGikiaiHwmIkPMDqYldLLWCBFZIyI76nlMr7bN/2JMrP2eY9FxoJdS6lzgHuB9Eenc9tEb4dWzzCfGahGRcGA58HulVAHwCpAEpGD8Hz5rYngAFymlRgJXAvNE5GKT42mSn79fffK96uPvU797j7ZD7rxvPwYSlVLDgTWcLfn0Fz55bTbDVow5OEcALwIrTI6nRQLNDsCXKaUmN7ZeROYCVwGTlKNyXClVDpQ7ft4iIgeBAUCql8OtTyZQ/VtcAnDMhDhqEBErxg3wPaXUfwGUUif/P3t3Hh91dS5+/PPMJJPJnpCFhEAISUC2ACKg1rpVrbZelwpVrAu1Wm7Vbra19lbr9vMq1tbb3lptrVqXewWXVuX3U3G37iLIvihbgBBIQvZ9mXl+f8xCErJMktlz3i94Jfmuz2S+J99nzvmec7qt/xvw/0IUHgCqWu7+WikiL+Bq7qgQkVxVPehuBqgMZYy9Rfj1GnbXarhfp5F4jUahQa9bVa3u9uPfcD0zGknCrmwOhftDluf7V0TkQRHJVNVwnuD9KKZmbZhE5BzgJuB8VW3ptjxLRKzu7wuBycDu0ETJZ8BkEZkkIjZgMbAyRLEArp5FwKPANlW9v9vy7s9AfAvos2dPMIhIoogke77H9XD+Zly/uyXuzZYAL4UmwqGLgOs1rK7VcL9Oo/EajVCDXre9rpnzcT3/GElWAle6e4WeANR7mtojgYjkuMszIrIAV95TPfBe4cfUrA3fA0Ac8Ib7OvhEVX+Aq2fKnSLSBTiAH6hqSB5+VNUuEfkh8BquXkuPqeqWUMTSzUnAFcAmEVnvXvZr4FIRmYOrer0U+PfQhAfAWOAF9/saAzytqqtE5DPgWRG5GtgHfDuEMQ5VWF+vYXithvt1Go3XaMTp77oVkTuBNaq6EvixiJyP6/GDGly9Q8OGiCzH1WMyU0TKgNuAWABV/QvwCq4eoTuBFuCq0ETaNx/iXwRc6/4b1wos9rQsRBIz3ZRhGIZhGEYYM82ghmEYhmEYYcwka4ZhGIZhGGHMJGuGYRiGYRhhzCRrhmEYhmEYYcwka4ZhGIZhGGHMJGuGYRiGYRhhzCRrhhFm3HNOVorI5m7LbheRAyKy3v3/m6GM0TAMwwieqBlnLTMzUwsKCkIdhmEAsHbt2sOqmjWcfd1zPDYBT6rqTPey24EmVf2dr8cxZcIIJyMpE/5iyoQRToZSJqJmBoOCggLWrAnF9JuGcTQR2TvcfVX1PREpGGkMpkwY4WQkZcJfTJkwwslQyoRpBjWMyPFDEdnobiZND3UwhmEYRnCYZM0wIsNDQBEwBzgI/L6vjURkqYisEZE1VVVVwYzPMAzDCBCTrBl96jx0iIZVq+g8eDDUoRiAqlaoqkNVncDfgAX9bPewqs5T1XlZWSF9PChi1JQ3U3uoOdRhGEbEc3R1sfvzz6g7ZO4b/hY1z6wZ/tP0r39R9uOfoO3tiM1G3n/dT/IZZ4Q6rFFNRHJV1fMX8FvA5oG2N3zTcLiVFXetJtZm4Yr//Ar2xNhQh2QYEeu1h/7Atg/exRoby7k/upHJx38l1CFFDVOzZvTQVVPDgRt/ia2okIlPPUncMcdQ/sub6Dx0KNShjRoishz4GDhGRMpE5GrgtyKySUQ2AqcDN4Q0yCjx5epDqFPpaHNQuulwqMMxjIhVe/AA2z54l5mnf53sgkJe/tN9VJftC3VYUcMka0YP1X97BGdzM3m//S0J8+eTd//vcXZ0UP3w30Id2qihqpeqaq6qxqrqeFV9VFWvUNUSVZ2lqud3q2UzRqBybyNpYxOwxcdwaFd9qMMxjIi1/aP3QISvfPs7XHjjb4iJtfHe04+HOqyoYZI1w8vZ0UH9Cy+QfOaZxBUXA2CbMIHUc8+l7sUXcba0hDhCw/CvuooWxuQmkpWfTOXexlCHYxgRq2zrZrILCknOyCQhNY1jv3Eeuz//jIbDpqOTP5hkzfBq/uADHHV1pC1a2GN56re+hba00PTuu6EJzDACwOFwUl/VSlpOApl5SdQeaiZaBgk3jGByOh0c2vUluZOnepdNPelUUKV0w9oQRhY9TLJmeDW99x6WxEQSjz++x/KEeccRk5VFw+tvhCgyw/C/xsNtOB1Kek4CqdnxdHU4aWnoCHVYhhFxag6U0dHaSm7xFO+yMePGk5g+hn2bN4YwsuhhkjUDAFWl+f0PSDjxBMRm67FOrFYSTzqJlk8+QZ3OEEVoGP7lGa4jfWwiKVnxANRXtYYyJMOISJV7dgGQU3QkWRMRxk+bSfkX20IVVlQxyZoBQOeBcjoPHCDxxBP7XJ9wwvE46upo//LLIEdmGIFRe8j1DGZaTgKpnmSt0iRrhjFUtQcPIGIhLSenx/KsiZNorK6irbkpRJFFD5OsGQC0bdwAQPzsOX2uTzzhBACaP/4kaDEZRiDVVrSQkGojLj6G5Aw7CDRUm2TNMIaq9mA5KdnZWGN6jlOYlV8AwOH9IZ8WNuKZZM0AoHXDRiQuDvsxU/pcH5uTQ2xeHq0bNgQ5MsMIjLpDzaTnJABgtVpISLbRXNce4qgMI/LUHionPTfvqOWZ+RMBqDbJ2oiZZM0AoHXjRuzTpyOx/Y/gbi8poW2zGTjfiHyqSu2hFtLHJnqXJabFmWTNMIZIVak7VE56zrij1iWPycQaG0tdhRlUfaRMsmagDgdt27YRP6tkwO3iZ86gs6yMrtraIEVmGIHR2thJe0sXaWMTvMtMsmYYQ9dSX0dHaytpfSRrYrGQkjWW+kqTrI2USdYMOsvK0LY24qb03QTqYZ/pSuZM7ZoR6eoq3D1Bc44ka0lpcTSZZM0whqT24AEA0nOPTtYAUrOyaaiqDGZIUckkawbtO3YAEDd58oDb2WdMB6Btq+mKbUS27j1BPRLT4mhv7qKrwxGqsAwj4tQeKgfosxkUIDV7LPWVFcEMKSqZZM04kqwVFQ24nTU5mZicHNp37gxGWIYRMLWHWoiJtZCcbvcuS0xzjS/YXG9q1wzDV3UHy7FYraRkZfe5PiVrLG1NjbSb6QpHxCRrBu07dhA7fjyWxMRBt42bPNmb3BlGpKo91EJaTgJiEe+yxNQ4AJrrzCwGhuGr2kPlpI7NxWK19rk+NXssAA1VpnZtJAKarInIOSLyhYjsFJFf9bE+TkSeca//VEQKeq3PF5EmEflFIOMc7dp37By0CdQjrriYjt27UYdpKjIiV11FM+ndOhcAxKe4atZam0yyZhi+qjtYTnpObr/rk9IzAGiqrQlWSFEpYMmaiFiBPwPfAKYDl4rI9F6bXQ3Uqmox8F/Avb3W/xfwaqBiNEA7Omjfs4e44mKfto+bPBnt6KBj374AR2YYgdHV4aChuo20nJ41yfFJ7mStsTMUYRm9+PBh/2cislVENorIWyIyMRRxjmbqdFJbcbDfzgUASWPGANBskrURCWTN2gJgp6ruVtUOYAVwQa9tLgCecH//PHCGiAiAiFwI7Aa2BDDGUa9j717o6iJuio81a5NdSZ1pCjUiVV1lK2jPnqAA8cmuMQZbG03NWqj5+GF/HTBPVWfhun/8NrhRGk21NXS1t5OWc/SAuB6JaWO82xrDF8hkLQ/Y3+3nMveyPrdR1S6gHsgQkUTgJuCOgU4gIktFZI2IrKmqqvJb4KOJrz1BPTydEDp27QpYTIYRSN4J3Hsla9YYC3EJMaZmLTwM+mFfVd9RVc9T658A44Mc46hXe3DgnqAAMTYb9sQkk6yNUCCTNeljmfq4zR3Af6nqgLO/qurDqjpPVedlZWUNM8zRrW3HDrBasU2a5NP2loQEYsaOpaPUTB9iRKbag80gkJadcNQ6e1KseWYtPPjyYb+7q+nnkRnzoT5w6jzDdozrP1kDSEwfY5pBRygmgMcuAyZ0+3k8UN7PNmUiEgOkAjXA8cAiEfktkAY4RaRNVR8IYLyjUsfOndjy87HExfm8jy0/39V8ahgRqKa8mdSseGJsR/deS0i2mWbQ8ODLh33XhiKXA/OAU/tar6oPAw8DzJs3r89jGMNTe6icmFgbyWMyB9zOJGsjF8iatc+AySIySURswGJgZa9tVgJL3N8vAt5Wl5NVtUBVC4A/AHebRC0w2nfs9LlzgYetYKLpYGBErJqDzYzJ7XuYGntSrGkGDQ++fNhHRM4EbgbOV1UzQF6Q1R4sJ3VsDmIZOJVISkunqc4kayMRsGTN/QzaD4HXgG3As6q6RUTuFJHz3Zs9iusZtZ3Az4CjevwYgeNsb6dj3z5sxQMPhtubbeJEHDU1OBobAxSZYQRGV6eDuspWMvKS+lwfn2Jq1sLEoB/2ReRY4K+4EjUzn1EI1B0qH7AnqEfimAyaa2tRpzMIUUWnQDaDoqqvAK/0WnZrt+/bgG8PcozbAxKcQceePeB0DrlmLXaiq4d8R+le4ktmBiI0wwiIuooW1KmMGdd3zVpCso22pk7UqT0GzDWCS1W7RMTzYd8KPOb5sA+sUdWVwH1AEvCcexCBfap6fr8HNfzK6XRQV3GQScfOG3TbpLR0nI4uWpsaSUhJDUJ00SegyZoR3tp3unp0xhX71hPUw+ZJ1vaaZM2ILNUHXD1B+0vW7EmxqEJbS6d33DUjNHz4sH9m0IMyvBoPH8bR2Ul67kD9PlwS013Dd7TU1ZpkbZjMdFOjWPtOT0/QgiHtZ8vPB6Bjn+lkYESWmoPNWCzSZ09QcNWsAbQ2mOfWDGMg3gncfWkGTU0HoLmuLqAxRTOTrI1i7Tt3Yps4EYttaDUIFrudmJwcOk2PUCPC1JQ3k5aTgDWm7z99djMwrmH4pM6HMdY8EtLSAGiurw1oTNHMJGujWMcweoJ62CZONGOtGRGnpryp3yZQ6DblVJOpWTOMgdQePECsPd7bxDmQxDRPzZpJ1obLJGujlLO9nY79+0eWrO3fP/iGhhEmOtsdNBxu63fYDjgy5VRbs0nWDGMgtQcPkJ47DnfnjgHZ4hOIibWZZG0ETLI2SnXs3u3uCTq0YTs8bPkTzPAdRkSpOejqXJAxru9hOwDsie5kzcxiYBgDqj1Y7lMTKICIkJCWTku9eWZtuEyyNkq179wJgG2YNWux3k4GZnBcfxORx0SkUkQ2d1s2RkTeEJEd7q/poYwxEtWUu2avG6gZ1BpjwWa3moFxDWMAjq5O6isrSB83eE9Qj8S0NFOzNgImWRul2rZtR2w24nycE7Q3T4/QTtMUGgiPA+f0WvYr4C1VnQy8hRlAesiqy5uxxlpIyYofcDvX/KAmWTOM/tRVHELV6dOwHR6Jaem0mGRt2EyyNkq1b99G3OTJSGzssPa3TXDNBNOx19Ss+ZuqvodrjtzuLgCecH//BHBhUIOKArXlzaTnJGAZZLDb+GSbeWbNMAZQe9D3YTs8ElJNzdpImGRtFFJV2rZuI27a1GEfw5KYiDUzk479JlkLkrGqehDA/TW7r41EZKmIrBGRNVVVVUENMNxVlzcP+Lyahz0pljZTs2YY/ao9eACA9Jyh1ay1Njbg6OoKVFhRzSRro1DXoUM46uqwT5s2ouPY8vPpNDVrYUVVH1bVeao6LysrK9ThhI32lk6a69oHfF7NIz4x1oyzZhgDqC0vIz4lFXvS4B9+PDzDd7Q21AcqrKhmkrVRqG3bdgDs06aP6Di2/HwzfEfwVIhILoD7q5m4eghqygeeZqo7U7NmGAM7XLaPjLwJQ9onwYy1NiImWRuF2rZtBRHsx0wZ0XFi8yfQdegQzrY2P0VmDGAlsMT9/RLgpRDGEnE8w3b4VLOWbKOr00lnhyPQYRlGxFGnk8N7S8maOLTOad4pp8wsBsPiU7ImIv8QkXNFxCR3UaBt2zbXNFOJg9+4BmLLd03o3llW5o+wotJwyo6ILAc+Bo4RkTIRuRpYBpwlIjuAs9w/Gz6qq2zFGmMhOd0+6Lb2JM9Ya6Z2zR8WLlzIyy+/HOowDD+pr6ygs72NzPyCIe1nZjEYGV9vIA8B3wF2iMgyERn+k+lGyLVv2z6izgUetnx3j1Az1tpAhlx2VPVSVc1V1VhVHa+qj6pqtaqeoaqT3V979xY1BlBf2UJKVjwySE9QODIwrnluzT+uvfZann76aYCZ5v4R+ar27gEge4g1a575QVvMZO7D4lOypqpvquplwFygFHhDRD4SkatEZHhjPxgh4aivp/PAgRE/rwZHxlozw3f0z5Sd8FBf1Upa9sDjq3nEm5o1vzrzzDP53//9X4BtmDIQ8Q7u/AKLNYYMd8uKr2JtcdjiE0wz6DANpWkmA/gucA2wDvgjrhvQGwGJzAiItq1bAUbcExTAmpaGJSWFTjN8x4BM2QktdSr1Va2kZif4tH18spnM3d+qq6sBMjBlIOKVbd9CTtFkYm1xQ943MS2dZlOzNiwxvmwkIv8EpgJPAed5xnsCnhGRNYEKzvC/1o2bAIgvmemX49ny803N2gBM2Qm9prp2HJ1OUgeZucDDPLPmXxdddBHbt28HV+WAKQMRrK25iYpdO5n3b8Mbk9vMYjB8PiVrwCOq+kr3BSISp6rtqjovAHEZAdK6aSO2iROxup8fGClbfj6tmzcPvuHoZcpOiNVXtgD43AwaFx+DCLSaydz94pprruGb3/wmInLIk6iZMhCZdq7+GKeji+IFJw5r/4S0dKpKd/s5qtHB12bQu/pY9rE/AzGCo23jJuyzZvnteLH5E+g8cADtNLUQ/TBlJ8TqKlsBfG4GFYuYsdb86JZbbulrsSkDEaa1qZGPnn+aMXkTyCka3rBPZjL34RuwZk1EcoA8IF5EjgU8XalSAN/+8kWhzs5OysrKaIuw8cXU4aDrtlvpSEmhYds2vxzTefLJOEpK2LZ9OxLja0Vt9LDb7YwfP57Yo+dYjRGR4xhFZSdcy0VXYifzr0in7NAeqPBtn1kXJWOxtrPNT+VkNPGUierqag4cOEBrayvr1q0DSBCRuURxGYDwLQcj1dJQz+zF3yUxNd3TrD1kY0qOY0HhVLZu3YrI4D2zo8UA9wmfDXZ3PRvXg9Hjgfu7LW8Efj3ss0a4srIykpOTKSgoiKgLztHQQAcQV1iIJcE/fysdzc107NnjalpNTvbLMSOFqlJdXU1ZWRmTJh3VjT0V+B2jqOyEa7mor2yhq8vp07ygHrWHXIPopueMbCzC0aZ7mXjvvfd4/PHHKSsr42c/+xm4ysLvieIyAOFbDkaipaGeBlsMyRmZ3vHShn2cqkoy8wuIGUHiEkkGuU/4bMBkTVWfAJ4QkYWq+o9hnyXKtLW1RWRBdLa0gghiH3xgUF+JzdVzTjtG3/M9IkJGRgb9TJheraqnj6ayE67lwtGlWGOGNp63xSp0dToDFFH06l4mlixZwpIlS/jHP/7BwoULEZEvVfX0UMcYaOFaDobL6XDQVHMYW3w8Cakje9bZ6m59cTq6YJQka4PcJ3w2WDPo5ar6P0CBiPys93pVvb+P3UaFSCyIztYWLHF2xOK/iSgkJgYsllGZrMGA18EY99dRVXbCsVw4HE5i44Z2YxCLoA4NUETRzXMN/M///A+XX345paWl3H///QBju5eFaC0DEJ7lYLjamhpxOpwkZ2SO+HVZrFbAlQCOJv64HgZrBvW0AfjefmCEJVVFW1ux+KkXqIeIYIm1jdpkbQCejNiUnRByOhV1KpaYof2xtFjFta9qVN14g6m52dWU3NTU5FlkAUbXsxJRoLWxgdi4OGLjRt4iY7F6atZGV7LmF6oaFf+PO+44DZatW7cG7Vz9sVgsOnv2bO//PXv26N///ne9/vrre2x36qmn6meffaaOtjbNHzdOD+7Y0WN9X/v0Z+LEiTpz5kydOXOmTps2TW+++WZta2vT9r17tfXLL1VV9f7779e4uDitq6tTVdWKigotKCjQgwcPeo9z7bXX6j333KPvvPOOAvrII494133++ecK6H333aeqqhdffLH3NU6cOFFnz56tqqodHR165ZVX6syZM3Xq1Kl69913e4/x6quv6pQpU7SoqEjvuece7/LvfOc7OmXKFJ0xY4ZeddVV2tHRoaqqTqdTf/SjH2lRUZGWlJTo2rVrvfucffbZmpqaqueee26/v5e+rgdgjY6iMqEanuXiyy926h/ve1D/fem1PbbzlAtV13VdVVXVY/1fHvybfu/K76ujyzHoORsbG/UHP/iBFhYW6pw5c3Tu3Ln68MMPq6rqnj171G6394jpiSeeUFXVuro6veKKK7SwsFALCwv1iiuu8Jab7vtNmzZNr7jiCu/1qqp69913a1FRkU6ZMkVXrVqlqqqtra06f/58nTVrlk6fPl1vvfVW7/a7d+/WBQsWaHFxsV588cXa3t6uqqr/+te/9Nhjj1Wr1arPPfdcj9f1+OOPa3FxsRYXF+vjjz/uXf7rX/9ax48fr4mJif3+TkZzmQjHcjDY/UG173Lw6COP6FWXX6ZNtdWDnnOg61lVdfPmzXr66adrYUGBFhVO0jvvvFOdTqequu5DmZmZOnv2bJ0+fbouXLhQm5ubVVX1tttuU0B3dLt33X///Qp4Y3/66ad15syZWlJSomeffbb3ddx22206btw47+/h5Zdf9h6jrzKkqnrVVVdpVlaWzpgxo8frq66u1jPPPFOLi4v1zDPP1Jqamh7rV69erRaL5ahy5DHSMuHrRO6/FZEUEYkVkbdE5LCIXB6wDNIYVHx8POvXr/f+LygoGHB7Z4trrCnLCJ9Xe+edd9i0aROrV69m9+7dLF26FLG5atZUleXLlzN//nxeeOEFALKzs7npppv4xS9+AcDnn3/OBx98wM9//nMASkpKeOaZZ7zHX7FiBbNnz/b+/Mwzz3hf48KFC7nooosAeO6552hvb2fTpk2sXbuWv/71r5SWluJwOLj++ut59dVX2bp1K8uXL2ere9aGyy67jO3bt7Np0yZaW1t55JFHAHj11VfZsWMHO3bs4OGHH+baa6/1nv/GG2/kqaeeGvbvy5Sd4OpdLvLHu6ZEG2rLv8Vdm+Z0Dt4Ues0115Cens6OHTtYt24dq1atoqbmyNStRUVFPWK68sorAbj66qspLCxk165d7Nq1i0mTJnHNNdcctd+mTZsoKyvj2WefBWDr1q2sWLGCLVu2sGrVKq677jocDgdxcXG8/fbbbNiwgfXr17Nq1So++eQTAG666SZuuOEGduzYQXp6Oo8++igA+fn5PP7443znO9/p8Zpqamq44447+PTTT1m9ejV33HEHtbWuIRfOO+88Vq9e7fPv8pe//CUNDQ0AYspAcAz1/tCfrk5Xi4ktfvAOaQNdz62trZx//vn86le/4uN33uKDt9/mo48+4sEHH/Tuf8kll7B+/Xq2bNmCzWbrcV8oKSlhxYoV3p+ff/55pk93TZnY1dXFT37yE9555x02btzIrFmzeOCBB7zb3nDDDd7fwze/+U2g/zIE8N3vfpdVq1Yd9fqWLVvGGWecwY4dOzjjjDNYtmyZd53D4eCmm27i7LPPB3tjEwAAIABJREFUHvyXOky+jrXwdVX9pYh8CygDvg28A/xPwCKLEIfuvpv2bcPrxtyfuGlTyfm1fztLeZI1iRv6FCF9SUpK4i9/+QsTJkzgvltvJVmVnV98QVNTE/fddx9333033/3udwFYunQpTzzxBO+88w4333wzDzzwgLcLc35+Pg0NDVRUVJCdnc2qVau8Bao7VeXZZ5/l7bffdr0OEZqbm+nq6qK1tRWbzUZKSgqrV6+muLiYwsJCABYvXsxLL73E9OnTexx3wYIFlJWVAfDSSy9x5ZVXIiKccMIJ1NXVcfDgQXJzcznjjDN49913R/KrGpVl5/1nv+Tw/qbBNxyCzAlJnHzx0MZ3crifOxtyU6Y7uXM6FAZ43G3Xrl2sXr2ap59+Gos7I8zKyuKmm24a8PA7d+5k7dq1PW5It956K8XFxezatQur+9keAKvVyoIFCzhw4ADgul4XL15MXFwckyZNori4mNWrV3PiiSeSlORqde/s7KSzsxMRQVV5++23PZOps2TJEm6//XauvfZa703c0iubfe211zjrrLMYM8b16OVZZ53FqlWruPTSSznhhBMG+eX19Prrr/Pb3/4WXD2kNzNKygDAO48/TOVe/w4Cmz2xkNO/u9Svx+xPV0cHIhZiBplaarDr+d133+Wkk07i61//Oof378UWG8sDDzzAaaedxvXXX9/znF1dNDc3k55+pNfphRdeyEsvvcQtt9zC7t27SU1N9d5DPDVPzc3NZGRk0NDQQHFx8YDxDlSGTjnlFEpLS/vcx3MvWLJkCaeddhr33nsvAH/6059YuHAhn3322YDnHQlfP296/lx9E1iuqjUDbWwEXmtrK3PmzGHOnDl861vfGnR7Z3MLIuLX529SUlKYNGkSO/e5ppta/vTTXHrppZx88sl88cUXVFZWAq4bwUMPPcTChQuZMmUKp5xySo/jLFq0iOeee46PPvqIuXPnEtdHQvn+++8zduxYJk+e7N0nMTGR3Nxc8vPz+cUvfsGYMWM4cOAAEyZM8O43fvx4703Oo7Ozk6eeeopzzjkHwKd9RsCUnSDqXS6cXU7XCHdDzdXc5UQHqVnbsmULs2fPPirZ6W7Xrl3emObMmcP777/P1q1bmTNnzlFJ2Zw5c9iyZUuP/dva2vj00099ul4dDgdz5swhOzubs846i+OPP57q6mrS0tKIcffE8+X69meZ6DwyYHYqpgwExVDvD/1xdHZiibEOet8Y7HresmULxx13HOB6bs3hcFBUVERTU5On1pVnnnmGOXPmkJeXR01NDeedd573WCkpKUyYMIHNmzezfPlyLrnkEu+62NhYHnroIUpKShg3bhxbt27l6quv9q5/4IEHmDVrFt/73ve8tcPDub4rKirIzc0FIDc313t/O3DgAC+88AI/+MEPBtx/pHytWfu/IrIdaAWuE5EsILpG/Bsmf9eA+cpTzd1dvwXK4UA72ofeFuQDVUXcn3Cefe45Xli5EovFwkUXXcRzzz3n/dQ0Z84cZs6cyXXXXXfUMS6++GIuueQStm/fzqWXXspHH3101DbLly/n0ksv9f68evVqrFYr5eXl1NbWcvLJJ3PmmWfiegygp96/l+uuu45TTjmFk08+2fsaBttnBEZl2RlqDZi/9C4X9VWtWK2WPt/Pgd5j8dSs+dAM2t1//ud/8txzz1FZWUl5eTlwpDmzu5deeqnP86se6dDgSfJ27NjBokWLmOWeeWSg69VqtbJ+/Xrq6ur41re+xebNmxk7dmy/2/fHn2XivPPOY+rUqeDqsPbWaCkDQNBqwHobyv2hv+VOhwOnw+HtwTmQ7tdtX8u7r7fGWOloOzI7iGf5JZdcwgMPPICqcv3113Pffffxq1/9yrvd4sWLWbFiBa+99hpvvfUWf//73wHXh4GHHnqIdevWUVhYyI9+9CPuuecebrnlFq699lp+85vfICL85je/4ec//zmPPfaYX6/vn/70p9x77709EtVA8Onuraq/Ak4E5qlqJ9AMXBDIwIyhy8jI8H5y8KipqWGMZwBcP/dqa2xspLS0lGOmT2fTjh3s2L2bs846i4KCAlasWMHy5ct7bG+xWPqsgcjJySE2NpY33niDM84446j1XV1d/POf/+zxaerpp5/mnHPOITY2luzsbE466STWrFnD+PHj2b9/v3e7srIyxo0b5/35jjvuoKqqyjOUAMCg+4yEKTuh5ehykpGR2We5yMzM7H9HzzNrgwzfMX36dDZs2IDT6RqT7eabb2b9+vXe2oL+zJgxg3Xr1nn3A3A6nWzYsIFp06YBR5K8nTt38sknn7By5UrAt+s1LS2N0047jVWrVpGZmUldXR1dXV39bt+bP8vEsmXL+PjjjwG2mjIQOv3dH/orB53t7cCRHpwDGex6njFjBmvWrPEez9nVxa5du0hKSiK512DqIsJ5553He++912P5eeedx1NPPUV+fj4pKSne5Z6ktKioCBHh4osv9n7gHzt2LFarFYvFwve//33vs5bDub7Hjh3LwYMHATh48CDZ2dkArFmzhsWLF1NQUMDzzz/Pddddx4svvjjo72yohlLVMg24RESuBBYBX/d7NMaIzJ8/nw8//JBDhw4Brouovb2dvDFjXFUFfkzWmpqauO6667jwwgsZM2YMz732Grf85CeUlpZSWlpKeXk5Bw4cYO/evT4d78477+z308mbb77J1KlTGT9+vHdZfn4+b7/9tvdZhU8++YSpU6cyf/58duzYwZ49e+jo6GDFihWcf/75ADzyyCO89tprLF++vEfSeP755/Pkk0+iqnzyySekpqZ6q7v9xJSdEHE6nMw77rg+y0X3ZpDePEVlsGbQ4uJi5s2bxy233OJ9QLmtra3PT+699zv22GO5664jU8feddddzJ0796jnbXJzc1m2bBn33HMP4LpeV6xYQXt7O3v27GHHjh0sWLCAqqoq6urqAFczmKfciAinn346zz//PABPPPEEF1wwcK509tln8/rrr1NbW0ttbS2vv/76iB6edk/bNcaUgdDp7/7QXzno6nBVfvpSszbY9XzZZZfxwQcf8Oabb2KxWmlpbeXHP/4xv/zlL/s83gcffEBRUVGPZfHx8dx7773cfPPNPZbn5eWxdetW76Czb7zxhvcDjye5AnjhhReYOXMm0H8ZGsj555/PE088AfQsQ3v27PHe9xYtWsSDDz7IhRdeOOjvbMh86TIKPAV8BDwI/Mn9/7997XIajP+jbeiO/rrNv/jii3rsscfq7Nmz9aSTTtK1a9dq244d2rZ7t06cOFFzc3M1Ly9P8/Ly9IYbbtC///3vmpiY6F2Wl5en+/fv7/PYnqE7ZsyYodOmTdNf//rX2tra6lo3YYKu79YtWlX1hhtu0GXLlnl/7t5NXFX1nXfe6XNIjNtuu807dIeq6pIlS/Shhx7qsU1jY6MuWrRIp0+frtOmTdPf/va33nUvv/yyTp48WQsLC/Wuu+7yLrdarVpYWOjtxn3HHXeoqmvojuuuu04LCwt15syZPWL86le/qpmZmWq32zUvL69HF2+Pgbpkh7LsjMahO7qXC6fDqRWl9dpU29ZnufDor1wkJCTquNxxg5aL+vp6Xbp0qRYUFOjcuXP1pJNO0j/96U+q2vfQHX/84x9VVbWmpkYvu+wyLSoq0sLCQr3sssu0trbWu1/3oQOcTqfOmjVL33vvPVVVveuuu7SwsFCnTJmir7zyiqqqbtiwQefMmaMlJSU6Y8YM7/Wtqrpr1y6dP3++FhUV6aJFi7StrU1VXcMN5OXlaUJCgo4ZM0anT5/u3efRRx/VoqIiLSoq0scee8y7/MYbb9S8vDwVEc3Ly9PbbrvtqN9J92vh8ssv1xNPPFGBylDfP0bL0B1DuT949C4H1/37Uv3v393n8/1hoOtZVXXjxo166qmn6uTiYi3Iz9dbf/ObPofuKCkp0W984xtaUVGhqkffDzy6308eeughnTp1qpaUlOi//du/6eHDh1XVde15hvQ477zztLy83Lt/X2VIVXXx4sWak5OjMTExmpeX5x1a6vDhw/q1r31Ni4uL9Wtf+5pWVx89nMmSJUsCNnSH6CCfAAFEZBswXX3ZOETmzZunnmrWQNu2bZs3cw936nDQtm0bMVnZxI7NDth5uqqq6KyowD5tGhLgtvtw09f1ICJrVXVeKMtOMMsEhF+56Op0UFPeTHKGnfgk25D3rznYjMUqpGVH7ZzjAdP9Wpg2bRpbt27FYrGsVdV5oYwrGGUi3MrBcFXtKyXWFkdajl9bGWhvaaH24AHGjBuPLT7er8cOZwPdJ3zZ39dm0M1AzhBjM8KAd3y1xMDecDzzjTrbRsVzw0Nhyk6IOLtc+fFQ5wX1sFhk0GfWjMHNnDnT2/RmRAanw4Gjs5MYPw311N2RKae6/H7saOZrb9BMYKuIrAbaPQtV9fyBdhKRc4A/AlbgEVVd1mt9HPAkcBxQDVyiqqUichawDLABHcCNqvq2j7Ea3TibW0AEyxA+wRx//PG0t7f3WPbUU09RUlLS7z6e8du0vR0SE/vdbhQaVtkxRs7hcD3sbLEOL1kTi6BdRx6YHk65MODw4cOeAUwni8hKz3I/3D9OAf4AzAIWq+rz/o59tOrscF3nsX0kayMtB5YYV7LmMFNODYmvydrtQz2wiFiBPwNn4RoM9DMRWamqW7ttdjVQq6rFIrIYuBe4BDgMnKeq5SIyE3gNyBtqDAY4W5qx2O1Dapr89NNPh3weiY11TejeqxAbQy87hn84vDVrw+tY45kf1GM45cKA22+/HYDTTjvtIPB7X/bx8f6xD/gu8As/hmsAXe2eZO3oGW9GWg4sFte4baZmbWh8StZU9V8iMhGYrKpvikgCrk87A1kA7FTV3QAisgJXd+3uhe0CjtzMngceEBFR1XXdttkC2EUkTlXDJhPQfsaVCSfqdOJsbSUmIyPg5xIRLHFxOEdZsjbYo2jDLDsRK5zKhbPLiaWfMdZ8YbEIaiZzH7LeZeLUU0/19AoXd3nwy/1DVUvd65x9HSCUIv2a6Wxvwxob61NP0KESESxWK86u0VOz5o9Hln2dG/T7uJKpv7oX5QGDDSSSB+zv9nMZR9eOebdR1S6gHuidWSwE1vWVqInIUhFZIyJrPN12g8Fut1NdXe2XNyCQnK2toIolITgPSEtcHDqKnllTVaqrq7EPMN/qMMtORAq3cuHocg67Vg1cNWsw+FhrxhF9lYm//e1vLFq0CGCie5G/7h9hKdzKwXB0trcTO8gUUyNhsVpxjpJmUF/uE77wtRn0elyfdD51n3yHiAzWtbCvv5K9r94BtxGRGbiaRvsck0dVHwYeBlcvn0Hi8Zvx48dTVlZGMBPE4XA0NuJsbCRGBAnA7AVHna+pCWdDAzEOR1DOFw7sdnuP8d/6MJyyE5HCrVw01bVjtQqHaofeExSgq8NBa2MnlQ22YXdSGI16l4k///nPrF69mri4OCf49f7hExFZCiwF1/iMgRZu5WCo1OmksfowcYmJxNXWBeQcLfV1OJ1OkurqA3L8cOPDfWJQviZr7ara4anWFZEYBi84ZUD30fbGA+X9bFPmPmYqUOM+x3jgBeBKVd3lY5xBERsby6RJk0IdxqD2X3sdHaWlFL36SlDO1/zRR+y7/ofkP/YoiV/5SlDOGQGGU3YiUjiVC6dT+euP3mXOmROY+62BJ3Xuz+GyJp55aDVnf38mxSVRmV8HRVxcHDbbkYTZj/cPnwT7Q304lYPh2Ld5I6/++T4W/scdFARoCJI3H3mQLz5+n+sfXT74xgbg+9Ad/xKRXwPx7p6azwH/d5B9PsPV+2eSiNiAxcDKXtusBJa4v18EvK2qKiJpwMvAf6jqhz7GaHSjqrSuW0f83GODds44d8Fuc41WbrgMp+wYI9RS34HToSSPGX7TQ/IYVzNQU+3oadoPhFNPPZW7774bQPx8/zACoHLPTgCyC4f3IccXqWNzaGtqpK25KWDniDa+Jmu/AqqATcC/A68Atwy0g/sZtB/i6sm5DXhWVbeIyJ0i4umy/SiQISI7gZ+5z4N7v2LgNyKy3v3ffLQdgo49pTjq6kg4NnjJWkx6OjHjcmnbsnXwjUePIZcdY+Qaa1wJVtIIkjVbfAyxdiuN1SZZG4lly5aRlZUF0Iof7x8iMl9EyoBvA38VkS0BfBmjRuXePSSNySAhJTVg50jNHgtAfWVFwM4RbXztDeoUkReBF1XV54Z4VX0FV8HsvuzWbt+34Spovfe7C7ir93LDd63rXB1q44OYrAHYp083NWvdDLfs9EdESoFGwAF0hXpE+HDVWNMKQHLG8JM1ESF5jN2b+BnDY7FYuPDCC1m6dOk+VV3k634+3D8+w9U8avhR1d49ZE0MbDNuarZrnPCGygrGTioaZGsDBqlZE5fbReQwsB34QkSqROTWgfYzQq91/TosqanYgvzshH3aNDpKS3E2Nwf1vOEogGXndFWdYxK1/nlqw0bSDOrZv6l2dA1H4y+qyu23305mZiZTp04FmGnuH+Gtq7OTmgP7A56spY11JWt1lWZmC18N1gz6U+AkYL6qZqjqGOB44CQRuSHg0RnD1vL5OhLmzAl6r0z7tOmgStsXXwT1vGEoG1N2Qqaxpp24hBhsdl/7UPUtydSsDdsf/vAHPvzwQz777DOqq6sB1mPKQFirLtuH0+Egu6AwoOeJS0jEnphEfYVJ1nw12J38SuBSVd3jWeAepPBy9zojDDnq6ujYtSvoTaAA9hnTAWjbOuqbQjMJTNlR4HURWesekqCHUI09GG4aq9tG1ATqkZJhp62pk45WM9r6UD355JMsX768R89Ic/8Ib1V7XX+uAl2zBq5OBvWmZs1ngyVrsap6uPdC97M3sYEJyRip1g0bgOA/rwYQk52NdcwY2raN+k4GEqCyc5KqzgW+AVzvnh+x+/EfVtV5qjrP/VD3qNRY0zbiJlCA1GzXnLr1Va0jPtZo09nZSWZm5lHLzf0jfFXt3UOMLY60nNyAnys1O4e6ioMBP0+0GCxZ6xjmOiOEWtatA6uV+JKZQT+3iLg6GZiatYGmwBl22VHVcvfXSlzjEC4Y7rGilar6LVlLy3bN/lFX2TLiY4023cdW64O5f4Shqr17yMyfiMUS+BnxxuSNp76igq4Ocyn4YrBkbbaINPTxvxEoCUaAxtC1rluPfdq0oE0z1Zt92jTad+7EOboLYYK/y46IJIpIsud7XDN7bPZjzFGhvbmLrnaHX5pBU7NcNWt1FSZZG6oNGzaQkpLi/Q8ca+4f4UtVg9IT1CNjfD6qTmoPHgjK+SLdgE/fqmrUTjgdrbSzk9aNG0lb5HMPeb+zz5wJnZ20b99O/KxZIYsjxNYGoLfmWOAF92wIMcDTqrrKz+eIeJ4OAf5I1mJsVpLS46ivNM2gQ+XoNfejiKwzPZjDV1NNNW1NjUFN1gAOl+0L2jkj2ci6Shlhp+2LL9HWVuLnzA5ZDJ7m19ZNm0ZzsuZ37oezQ/fGRgh/DdvhkZqdYJpBjagXzM4FAOm5eYjFQvX+fUE5X6QzsxNHmdbP1wKQcNxxIYshJjcXa2YmbZtMC50RfP6sWQNIG2uSNSP6eZO1/OAkazGxsaTnjKO6zCRrvjDJWpRp+XwdsePGEZuTE7IYRIT4mTNp3bwpZDEYo1djdRsxNgv2RP90OEzLjqe9uYu2pk6/HM8wwlHV3j2kZo8lLojPOmeMzzfJmo9MshZFVJXWtWuJnzs31KFgL5lJx67dOJrMTAZGcHl6grqf7RuxVNMj1BgFqvaVkhmkWjWPrImTqD1UTnuLKVuDMclaFOk8cICuqioSjgt9shZfUuKayWCrmVvZCK7GGv8MiOuRPtadrJkeoUaU6urooLb8AFkTC4J63pziKaBKxe6dQT1vJDLJWhRpXet6Xi1+buieV/Owl7h65pvn1oxga6z2zxhrHimZdqwxFmrKTS2xEZ2qy/ah6iQrvyCo5x1bWAzAoV1fBvW8kcgka1Gk+bPPsCQnEze5ONShEJOeTmxennluzQiqjrYu2po7/VqzZrFaSM9NoLq8yW/HNIxwUrWvFCDozaAJKamkZo81yZoPTLIWJVSV5g8/IvGEE4I+eXt/7CUltG00yZoRPJ5poVIy4/163DHjEk3NmhG1Du/zTDMV/I5pOUVTOLRrR9DPG2nC465ujFjH7t10HTxI4le/GupQvOJLZrqeo6upCXUoxijhGbzWM02Uv2SMS6Kptp32FtMj1Ig+VXtLyZyQH5RppnrLKZpM4+EqmmrNfWIgJlmLEs0ffABA4kknhTiSI+wz3c+tbTbPrRnB4emx6ZmA3V/GjEsEMLVrRlRy9QQtCMm586bNAKBsm7lPDMQka1Gi6f0PsBUUYBufF+pQvOwzZoAIrZtMU6gRHPWVLSSk2rDZ/Ts5iydZqzbJmhFlmutqaW2oD3rnAo+xk4qxxcdTttXcJwZikrUo4Kivp/nTT0k6/fRQh9KDNSkRW1Ehres3hDoUY5Sor2z1exMouKauirVbTc2aEXUq9+wCgjfNVG8Wq5W8qTPYt8UkawMxyVoUaHz7HejsJOWcs0MdylESFyygde1atNM862MEXl1li9+bQME1K0dmXhKH9zf6/diGEUqHdu0AEe8wGqEwYXoJteVl5rm1AZhkLQo0vvYaMeNysYfhpOkJx5+As6WFVvPcmhFgrY0dtDZ2kp6TGJDjZ09MoXJfIw6HMyDHN4xQOLTrSzLyJmCLD940U71NmO56vnm/aQrtl0nWIpyjsZHmDz8k5etn+216HX9KWDAfgJZPPw1xJEa0O1zmGgctc0JSQI4/dlIKjk4nNQdMU6gRHVSVQ7t2kFM0OaRxZE8qwp6UTOm6NSGNI5yZZC3CNb7+OhqmTaDgGhw3bvo0mt57P9ShGFHOm6yND0yyll2QAkBFaUNAjm8YwdZYXUVLfR1jQ5ysWaxWJh07j93r1+J0OkIaS7gyyVqEq/vHP7EVFmKfPTvUofQr5ayzaP38czoPHQp1KEYUO1zWSGKqjfgkW0COn5Jpx54US8We+oAc3zCCrfyLbQDkFh8T4kig6LgFtDU2UP7l9lCHEpZMshbB2nfvofXzz0lbeFFYNoF6pHzjGwA0vLoqxJEY0axidwNZE1MCdnwRIacwlfIddQE7h2EE0/4tm7DFJ5BdUBjqUCiYPReLNYZda8wjM30xyVoEq3/hn2C1knr++aEOZUC2ggLss2dRu3w56jBV3Ib/Nde3U1/VyrjitICeZ8K0dBoOt3mntTKMSLZ/60bGT5uBxRr8mQt6i0tIpGD2sWz/8F+mKbQPJlmLUM62Nuqe/wdJp51GTFZWqMMZVMbVV9O5bx/1L74U6lCMKHRwp6tpMndyakDPM2HaGADKtpshBozI1lhzmNqD5UyYET6jCMw87SyaaqrZu2FdqEMJOyZZi1D1K1fiqK1lzJVXhjoUnySfeSbxc+dSce+9dJSWhjocI8rs21qNzW4lKz85oOdJG5tAYloc+7eaZM2IbHs3rgcgf2b4PO9ceNx8ElLTWPPyi6EOJeyYZC0CqSo1Tz5J3PRp3qExwp1YLIxbdg9itbLv6mvorKgIdUhGlFCnUrrxMPkzM7BaA/snTUQoKMlg75ZqOtq6AnouwwiknZ99THJGVshmLuiLNSaW+eddxL5N682Ya72YZC0CNb72Oh07d5Fx1VVh3bGgN1t+PhMefhhHXR37rvoeXdXVoQ7JiAIVpQ20NnYyaVZmUM435fgcujqc7F5fFZTzGYa/dba1sXfDOornnxB295DZX/8myZlZvPG3P9PZ0R7qcMKGSdYijHZ1UfWHPxA3uZiUb34z1OEMWXzJTCb85SE6y8vZd/U1OJvNAKPGyOxaV4XFIuTPyAjK+XKLUknJtLP5XwdQ1aCc0zD8afe6z+jq7KB4/gmhDuUosXF2zv73n1BbXsYHTz8R6nDChknWIkzNU/9DR2kpWT/9KRIGPXiGI2H+fMb/9x9p/+ILDt35f0IdjhHBHA4nX3x6iIklGdgTY4NyThFh7tkTqdjTwK7PTe2aEXk2vvUayRlZjJ8+M9Sh9GnirDkc+43z+PzVlXz5yQehDicsmGQtgrTv2kXVH/5A0umnk/S1r4U6nBFJOuUUMq+7jvqXXqLuny+EOhwjQu3bXE1rQwfTThoX1PNO/UouWfnJvPu/26nca2Y0MCJHTXkZ+zatp+SMr2OxhO8H/lMv/x65xcfw2l/+SE35gVCHE3ImWYsQHWVl7F/671iSksi5/fawe85gODKvu5aE44/n0J130vbll6EOx4hAG98pIyHVRv6MMUE9r9Vq4ZylM7HZY3jhd5+z6/PKoJ7fMIbrwxVPERtnZ9YZ54Q6lAFZY2L5txtuwhITy//9r3vobG8LdUghZZK1MOJsa6Pp/Q+ofvQxKpbdy8Hf3MqBG3/J/ut/yJ7zL8DR2MiEvzxE7NjsUIfqF2K1kve7+7AkJXHgJz/F0WSeXzN8d2hPPWXba5lzRn7Ae4H2JSUznkW/mkfmhCRWPbyZ9W/uC3oMhjEYR1cXnW1tdHa0s/bll/jy0w+Zf8FCEtPSQx3aoFIyszn3hz/n8P69vPnIg6P6GdGYQB5cRM4B/ghYgUdUdVmv9XHAk8BxQDVwiaqWutf9B3A14AB+rKqvBTLWUNKODmqfeZbDDz6Io7YWALHbsSQlYbHbscTHk/S1r5H1kx9jmzAhxNH6V0xWFnm//z37rrqK/d//PhMeehBrWmBHoY9kg5Wp0UKdyofP7cCeFMuMU4LbBNpdQoqNC244ljf/vpUPn99JR5uD+ecWREXNd6iN5P5hQHNdLf966lG+/PRDHJ2d3uWFc+dz/IUXhzCyoSmYcxwnLlzMx88vJzV7LF/59mWhDikkApasiYgV+DNwFlAGfCYiK1V1a7fNrgZqVbVYRBYD9wKXiMh0YDEXLLCvAAAgAElEQVQwAxgHvCkiU1Q1quagUKeTxtffoPK/7qdz7z4STjiBjO9dRfycOViSk0fNH/zE4xeQd//9HLjxRnad+29kXPVdks86i9j8/FHzO/CFj2Uq6qkqn7y0i0O7Gzjju9Ow2QP6mXNQMbFWvn71DN6J285n/28Puz6vJCMvidTseLLGJ5NTlEpCSmAml49WI7l/BD/a8KJOJ5vefp33nv47Xe3tlJxxNskZWajTSXruOIoXnBjWz6r15cSFl9JQVcXHzy+npaGBr15yBfakpFCHFVSB/Cu3ANipqrsBRGQFcAHQvbBdANzu/v554AFx3Z0vAFaoajuwR0R2uo/3cQDjHRJvdazqkf/dftYjG/ZY72xtpXP/flo+X0f9Sy/Rvn07tuIiJvz1LySecsqoTU5Szjkb28R8Ku6+h8rf/Z7K3/0ea3o6cZMnYysocP2f5Poam5OD2O2j8XflS5kKCVUF1z/PAtf3ineh0nub7uXIvanzSDNHW1MnVfsbqT3UgjqVuIQYRIS9mw+zf1stM04exzHH5wTh1Q3OYrXwtSumkVOYyq7PKzm0u56dayq8fxbSxiaQW5xKUloc1lgLMbGum6XToTidTvdXxelQ1KFHfnYqMbEW4hJiiE+2kZQeR1K6nfjkWGLjrMTarIglKsvBsO8fGmZtZeq9J3S71vVIwXB96/4ez/0Curo66WxrdTVhtrXhcDgQEcQiiFhcf/9E3MssdLa1UrZtC1vefZOa8jImTC/hzO9fz5hx40Pzwv1ILBa+/oMfYU9KYu3LL7LprddIzx1HcmYWSeljSEofQ2J6BimZWa7/WdnY4hNCHbZfBTJZywP2d/u5DDi+v21UtUtE6oEM9/JPeu2bN9xAvjzpq2hbW7cCQZ8Jlq/r/SVu6lTG3buMlHPPRWJCWzsQDuzTpjHxqSfpKC2l+dPVtG7cQMfuPTS+/jqOurqeG4u4EjZLP88qDZTI+SnJS5g/nwkP/tkvx/KRL2VqUI5OJ4/d+L43mer5wYIjSRZHEqx+E7Fg8Lxd7vMlpNr46rcnM+v08WGVsItFmHFyHjNOdv2pcnQ6qdrfSPmOOg7uqmfP+sO0NXcOeAyLRRCrYLGK63uL0NXppKu9/0YFa4zFdUlbBBH3rytEv5eCWRmcddUMfxxqJPePw0M9WUtDPY/++PuAHvkz70mwjvq5W5LlTbg8ZafbPSNEcoomc+6Pb+SYr0TXh3+LxcppV17D9FO+xhcfvUf1gf001dRweO8emuvrUKez5/ZWKxaLFbFaXQltiH4X004+jTO+d+2IjxPIDKGv30zvK7i/bXzZFxFZCiwFyM/P7zeQ1AsuAEeX67CeN8z9qQTvj551fa+nx5stR9Z7XkX39Z7j9DiX6xxiiyN2/Hjsx0whNm/Y+WdU89SkpV9y5LmKrtpaOvfupX1PKV1VVWhbK87WNuhVQF36/0Ppzw/dtoICvx3LR4OWC1/KhFhg2lfGHTlit8scEffNvvv9Xo5s0728dP/Zs2+3CEW67dtjefcfQLptI54ypxBrt5I1IZn03ASsVgsdbV04HYo9KTYibkLWWAs5hankFB6ZXF6disPhpKvDdd1aeiVm/b0uh8NJa0MHTbXtNNa00d7SRWebg872Lro6nd7aGVX/XuNDlZHnt6apkdw/em7kQ5mIiY1l5ulnubfvduheN3lvbdaRBT3uCyJ0u9ilRxnyXtt4rnk5cswjJ/b+HBMbS6w9nli7ndg4O1ar1fW5SZ2oU4/U2KkTVcVijSG3eEpEdBwYieyCQrILCnssczodtNTV0XC4iobDlTRUVdLe0ozT4UCdzqMSuWDKmXyMX44TyGStDOj+NPx4oLyfbcpEJAZIBWp83BdVfRh4GGDevHn9/oUa+8sbhxG+EU5i0tOJSU8nfs6cUIcSSoOWC1/KhMVq4asXTw5UjAETlxCcQW8DSSxCjMXqbQb1ldVqISndTlK6vUfyF8VGcv/owZcyYYtP4PQl3/dD2EYoWCxWksZkkDQmg3FTpoY6nIAIZH/3z4DJIjJJRGy4Ogys7LXNSmCJ+/tFwNvu5w1WAotFJE5EJgGTgdUBjNUwIoEvZcowosFI7h+GEXUCVrPmfobgh8BruLpeP6aqW0TkTmCNqq4EHgWecncgqMFVIHFv9yyuh0m7gOujrSeoYQxVf2UqxGEZht+N5P5hGNEooE+1q+orwCu9lt3a7fs24Nv97PufwH8GMj7DiDR9lSnDiEYjuX8YRrSRaKk1FpEqYG+o4wiATIbRuymKROrrn6iqWaEMIIRlIhLfs0iMGSIr7tFcJvwhkt7roYjG1+Xra/K5TERNshatRGSNqs4LdRyhMtpffySKxPcsEmOGyI3bGLpofa+j8XUF4jWZuUENwzAMwzDCmEnWDMMwDMMwwphJ1sLfw6EOIMRG++uPRJH4nkVizBC5cRtDF63vdTS+Lr+/JvPMmmEYhmEYRhgzNWuGYRiGYRhhzCRrhmEYhmEYYcwka2FGREpFZJOIrBeRNe5lY0TkDRHZ4f4aFTP1ishjIlIpIpu7LevztYrLf4vIThHZKCJzQxe5ASAi54jIF+735Fd9rM8XkXdEZJ37PftmKOLsFdNR11yv9WF3nfkQ82XuWDeKyEciMjvYMRqBIyLfFpEtIuIUkXm91v2H+1r9QkTODlWMwzHY349IMZT72EiYZC08na6qc7qN0/Ir4C1VnQy85f45GjwOnNNrWX+v9Ru45oidDCwFHgpSjEYfRMQK/BnX+zIduFREpvfa7BbgWVU9FtdUQA8GN8o+Pc7R11x34XidPc7AMe8BTlXVWcD/ITof2B7NNgMXAe91X+gub4uBGbiujwfd5TLs+fj3I1I8ju/3sWEzyVpkuAB4wv39E8CFIYzFb1T1PVxz+nXX32u9AHhSXT4B0kQkNziRGn1YAOxU1d2q2gGswPUedadAivv7VKA8iPH1qZ9rrruwu84Gi1lVP1LVWvePnwDjgxKYERSquk1Vv+hj1QXAClVtV9U9wE5c5TIS+PL3IyIM8T42bCZZCz8KvC4ia0VkqXvZWFU9COD+mh2y6AKvv9eaB+zvtl2Ze5kRGr68H7cDl4tIGa45Hn8UnNBGJNKvs6uBV0MdhBEUkXytRnLsvvD7PTugE7kbw3KSqpaLSDbwhohsD3VAYUL6WGbGnQkdX96PS4HHVfX3InIi8JSIzFRVZ+DDG7aIvc5E5HRcydpXQx2LMTQi8iaQ08eqm1X1pf5262NZRFyrRHbsIWGStTCjquXur5Ui8gKu6uIKEclV1YPuJpnKkAYZWP291jJgQrftxhMGzWqjmC/vx9W4n+VQ1Y9FxI5rguNwvn4j8joTkVnAI8A3VLU61PEYQ6OqZw5jt4i8Vt0iOXZf+P2ebZpBw4iIJIpIsud74Ou4Hi5dCSxxb7YE6O+TVjTo77WuBK5099Y7Aaj3VDMbIfEZMFlEJonI/2fvzOOjqs7G/31myzpJSAIECBCQfZGIiAuCKPqCVkHFtVpc6quttGqrdXltLbVqrfpKF/21btWCNiAoCLxa0QKtqOwgyCZbkBBJyJ7JZJnl/P6YzJCQPZk1c74f/TBz77nnPjO5Z+5zn9WCJ9B5xWljvgWmAYjISCAWOBlUKTtOxF1nIjIAeB/4gVLqm1DLowkaK4CbRCRGRAbhSYrZFGKZ2kt7fj8iGb/fs3UHgzBCRAYDy+rfmoB/KKWeFpE04F1gAJ4b4PVKqdaCpCMCEckBpuKxthQAvwaW08xnFREBXsJjqbEDdyiltoRCbo2H+lIcfwCMwN/qr9UngS1KqRX12V2vAYl4XBwPK6VWh07iFq85M4BS6q/heJ21Q+bXgdnA0fpDnA0yyTURjohcA/wZ6AmUATuUUtPr9z0O3Ak4gQeUUhETr9jc70eIReoUHbmPdek8WlnTaDQajUajCV+0G1Sj0Wg0Go0mjNHKmkaj0Wg0Gk0Yo5U1jUaj0Wg0mjBGK2sajUaj0Wg0YYxW1jSaINKO5ucxIrK4fv9GEck6bf8AEbGJyEPBklmj0Wg0oUUraxpNkGhn8+IfAqVKqSHAfOD3p+2fj24npNFoNFGFVtY0muDRnubFDRsALwWm1df+QkSuBg4Du4Mkr0aj0WjCgG7Tbio9PV1lZWWFWgyNBoCtW7cWKaV6nra5uebF57Y0RinlFJFyIE1EqoFHgMuAFl2gInI3cDdAQkLC2SNGjOjS59Bo/EULayKo6PuEJpzoyJroNspaVlYWW7bogvaa8EBEjja3uZltp1elbmnMb4D5SilbvaGtWZRSrwKvAkyYMEHpNaEJF1pYE0FF3yc04URH1kS3UdY0mgigPc2LvWPyRMQEJAMleCxw14nIc0AK4BaRGqXUS4EXW6PRaDShRCtrGk3w8DUvBo7jaV78/dPGeBsAfwlcB6xRnp5wk70DRGQeYNOKmkaj0UQHOsEgRNQcKKVqW0GoxdAEEaWUE/gJ8DGwF3hXKbVbRJ4UkZn1w97AE6N2EPg50KS8RzRSVlbGv//9b06ePBlqUTQaDeBwVPDtsTf59ts3cLmqQy1Ot0db1kKA2+6g6I2vATD3iseSafXr/A6Hg7y8PGpqavw6r6YpsbGxZGZmYjab2zVeKfUh8OFp255o8LoGuL6NOeZ1XFIPkXhtKKWorKzEYrFw+PBhTp48SWtxe5rQ0tE1oQl/3O5a9u59jOKSz0hIGEpi4jAKClbhcJQCUFq2iXFnvhJiKbs3WlkLATUHy3yvq/cU+11Zy8vLw2q1kpWVpW9qAUQpRXFxMXl5eQwaNCjU4rSLSLw2bDYbFRUVJCYmYrPZ6NGjB3FxcaEWS9MMkbgmNG1z9OirnCj4gF69rqDafpTjx3PokXIuZwx5mJLi9Rw6/Dxl5VtJST471KJ2W7QbNATUfVsJJgOmnnE4jtv8Pn9NTQ1paWkRczOOVESEtLS0iLJSRdq1oZTCZrNhsViwWq0YDIaI+r6jjc6sCd3VI7xxu+v49thbpKddwtgxf2bixBVcPHUfZ521gCTrGPr3n4PJlMTx4zmhFrVbE9bKmoikiMhSEdknIntF5PxQy+QPHCeqMGfEY+lvpS7f/8oaEDE340gnEr/nSJK5trYWt9tNQkICIoLFYqG2tjbUYmlaoSPXl+7qEf6Ulm7A6Syjb7+bfNsa/o2NxnjS06dRVLQGt9sRChGjgrBW1oA/Av9USo0AxuEJyo54nCU1mNLiMPWMw13pwF3nCrVIGk1YYrfbMRgMxMbGAmCxWHC73bhces10E3RXjzCnqHgtBkMcqT0mtTimZ/plOJ3lVFR8FUTJoouwVdZEJAmYgic7DqVUnVKqrPWjwh/lcuMqq8GUFouph+cG5Crtfm4dEeHBBx/0vX/hhReYN28eTz/9NNnZ2WRnZ2M0Gn2v//SnPzU7z7x58+jXr59vXHZ2NmVlZaxbt47k5GTftksvvdR3zIIFCxgzZgyjR49m1KhRvPDCCwAsWbKE0aNHYzAYGhXGrKur44477mDs2LGMGzeOdevW+fZNnTqV4cOH+85TWFjo528qOlm2bBkiwr59+wBwu93cd999jBkzhrFjx3LOOedw8OBBampqiIuL8z3Je4PWBw8ezOTJkxvNmZ2dzZgxYwIir9PpJD09nccee8yv8yYmJja7/a9//SsLFiwA4Pbbbyc+Pp7Kykrf/vvvvx8RoaioyK/ytJdnnnnGX1M119WjX0tj6jOqvV09EvB09fhNaycQkbtFZIuIbNHZxB2nvHwbyUnjMBpjWxyTknIOAGVlm4MlVtQRtsoaMBg4CbwpIttF5PX6xekjEhehq7QW3GBKjcOY6rn4ncXdT1mLiYnh/fffb3Izefzxx9mxYwc7duwgLi7O9/q+++5rca6f/exnvnE7duwgJSUFgMmTJ/u2ffrppwB89NFH/OEPf2D16tXs3r2bbdu2kZycDMCYMWN4//33mTJlSqP5X3vtNQB27drFJ598woMPPojb7fbtf+edd3zn6dWrV9e/HA05OTlceOGFLFq0CIDFixeTn5/Pzp072bVrF8uWLcNisQAQHx/vO65hhmFlZSXHjnnu83v3Btbovnr1aoYPH867776Lp+xdYPnRj37EnDlzfO+HDBnCBx98AHgU27Vr19Kv3+k6TfDwo7Lml64erZ1AKfWqUmqCUmpCz54h7XYVcbhcNdhs+0hKPqvVcRZLKgkJQykr18paoAjnbFATMB74qVJqo4j8EU/NqV95B5zeWickUnYQZ70VzZQai8mrrAXQsla28hB1+VV+ndPSN4GUq85odYzJZOLuu+9m/vz5PP300349f2v87ne/44UXXqBv376Ap4zAf//3fwMwcuTIZo/Zs2cP06ZNA6BXr16kpKSwZcsWJk6cGByhQ8RHH33EiRMn/DpnRkYGl19+eatjbDYbn3/+OWvXrmXmzJnMmzeP7777jj59+mAweJ4f+/XrR2FhIQaDoZGCZjAYMBgMKKW44YYbWLx4MQ899BA5OTncfPPNLFy4EACXy8Wjjz7KunXrqK2tZe7cudxzzz3YbDZmzZpFaWkpDoeDp556ilmzZpGbm8vll1/OhRdeyBdffEG/fv344IMPfFmnOTk53H///fzlL39hw4YNnH++J3w2KyuL73//+6xduxaHw8Grr77KY489xsGDB/nFL37Bj370I9atW8cTTzxBWloa+/fvZ8qUKfy///f/fJ/18ccfZ9WqVcTFxfHBBx/Qu3dv5s2bR2JiIg895ImZv/nmm1m8eDG33nor69atY9KkSXz00akwrRdffJG//e1vANx111088MAD5ObmMmPGDC688EI2bNjAuHHjuOOOO/j1r39NYWEh77zzDhMnTqSqqoqf/vSn7Nq1C6fTybx585g1axZvvfUWK1aswG63c+jQIa655hqee+45Hn30Uaqrq8nOzmb06NG88847XblkdFePMKay8muUcpKclN3m2JTkCRQUrkIpNyLhbAeKTML5G80D8pRSG+vfL8WjvEU0roo6AIxJFgwJZjAZcJV1z4DpuXPn8s4771BeXt6leebPn+9zQ1588cW+7Z999plvu1ch/Prrrzn77I6lj48bN44PPvgAp9PJkSNH2Lp1q89iA3DHHXeQnZ3Nb3/726BYVbo7y5cvZ8aMGQwbNozU1FS2bdvGDTfcwMqVK8nOzubBBx9k8+bNuFyuRlY1LyaT5xnzuuuu4/333wdg5cqVXHXVVb4xb7zxBsnJyWzevJnNmzfz2muvceTIEWJjY1m2bBnbtm1j7dq1PPjgg76/6YEDB5g7dy67d+8mJSWF9957D4Dq6mr+9a9/ceWVV3LzzTeTk9M4661///58+eWXTJ48mdtvv52lS5eyYcMGnnjCVz6PTZs28b//+7/s2rWLQ4cO+eSuqqrivPPO46uvvmLKlCk+K+/pDB06lJMnT1JaWkpOTg433XQq2Hvr1q28+eabbNy4kQ0bNvDaa6+xfft2AA4ePMj999/Pzp072bdvH//4xz9Yv349L7zwgs869vTTT3PJJZewefNm1q5dyy9+8QuqqjwPeDt27GDx4sXs2rWLxYsXc+zYMZ599lmfVbyLiho06OohIhY8XT1WnDbG29UDGnT1UEpNVkplKaWygD8Az2hFzb9UVOwEICm5bWXNmjQWp7OS6upjbY7VdJywtawppU6IyDERGa6U2g9MA/aEWq6u4rZ5smUMVgsigtFq9m0LBG1ZwAJJUlISc+bM4U9/+lOX6mL97Gc/81kYGjJ58mRWrVrVFREBuPPOO9m7dy8TJkxg4MCBXHDBBT6F4J133qFfv35UVlYye/ZsFi5c2Mg9Fcm0ZQELFDk5OTzwwAMA3HTTTeTk5PD888+zf/9+1qxZw5o1a5g+fTp//etfue6665ocbzKZUEqRmppKjx49WLRoESNHjmyk2K1evZqdO3eydOlSAMrLyzlw4ACZmZn8z//8D//5z38wGAwcP36cggJPJ5FBgwaRne25KZ199tnk5uYCsGrVKi6++GLi4+OZPXs2v/3tb5k/fz5GoxGAmTM9zSfGjh2LzWbDarVitVqJjY2lrMwTZjtx4kQGDx4MeKxk69ev57rrrsNisXDllVf6zvnJJ5+0+L1de+21LFq0iI0bN/LKK6cKkK5fv55rrrmGhIQE37jPPvuMmTNnMmjQIMaOHQvA6NGjmTZtGiLC2LFjfZ9v9erVrFixwhfbWVNTw7fffgvAtGnTfGEEo0aN4ujRo/Tv39AQ1jWUUk4R8Xb1MAJ/83b1ALYopVbgiVteWN/VowSPQqcJAraq/VgsPYmxpLc51modDUClbTfx8QMDLVrUEbbKWj0/Bd6pf+I6DNwRYnm6jKuyDrEYMMR4fuiNVguuyroQSxU4HnjgAcaPH88ddwTnTzd69Gi2bt3KJZdc0u5jTCYT8+fP972/4IILGDp0KIAvLshqtfL973+fTZs2dRtlLRQUFxezZs0avv76a0QEl8uFiPDcc88RExPD5ZdfzuWXX05CQgKffPIJN954Y5M5vIq02+3mxhtvZO7cubz11luNxiil+POf/8z06dMbbX/rrbc4efIkW7duxWw2k5WV5asJFhMT4xtnNBqprva00MnJyeHzzz8nKyvL9xnWrl3rS2rxHmcwGBrNYTAYcDqdQNNyFg0TJryvjUajb3xz3HTTTYwfP57bbrvN50L1ftaWOF2ehrJ6z6WU4r333mP48OGNjt24cWOT76Q1+TpLqLt6aFqmquoQCfHte+BPTBiKiInKyt307nVFgCWLPsLZDYpSakd9YOiZSqmrlVKloZapq7hsdRgSLb73hkQLblv3VdZSU1O54YYbeOONN4Jyvscee4yHH37YF4tVW1vbYqapF7vd7nP7fPLJJ5hMJkaNGoXT6fQlSDgcDlatWhWwbMNoYenSpcyZM4ejR4+Sm5vLsWPHGDRoEP/5z3/Iz/eEKjkcDr7++usWK+B7LVpOp5NrrrmGhx9+uIlSNn36dP7yl7/gcHis1t988w1VVVWUl5fTq1cvzGYza9eu5ejRo63KW1FRwfr16/n222/Jzc0lNzeXl19+uYkrtC02bdrEkSNHcLvdLF68mAsvvLBDxwMMGDCAp59+mnvvvbfR9ilTprB8+XLfdbxs2bImmbKtMX36dP785z/7lD6vC7U1zGaz77vVdE+UUlRVHSAhYWi7xhsMMSQkDKOyUldRCQThblnrdrgr6zBaTylrRquZuqMVIZQo8Dz44IO89FLnQ0nmz5/P22+/7Xu/fPnyFsdeccUVFBQUcOmll6KUQkS48847AU+5iJ/+9KecPHmS733ve2RnZ/Pxxx9TWFjI9OnTMRgM9OvXzxekXltby/Tp03E4HLhcLi699FJfsoKmc+Tk5PDoo42L1M+ePZvbb7+d1NRUamtrUUoxduxYfvrTnzY7h1dZc7lcWK1WHnnkkSZj7rrrLnJzcxk/fjxKKXr27Mny5cu55ZZbuOqqq5gwYQLZ2dmMGDGiVXnff/99LrnkkkYWplmzZvHwww93qDjv+eefz6OPPsquXbuYMmUK11xzTbuPbcg999zTZNv48eO5/fbbfQkxd911F2eddZbPzdkWv/rVr3jggQc488wzUUqRlZXVZnjB3XffzZlnnsn48eP9EbemCUPq6gpxuWzEJ7Q/lMZqHU1R0b98v70a/yHdJWB6woQJqmHtrHDlxItbMfeMI+0HniLd5Z8cpXLNt/R7ahJi9I+hc+/evS1mPmr8T3Pft4hsVUpNCJFIQPNrIhKujfLycux2OxkZGc3+4LtcLgoKCkhKSmqxTlk4sW7dOl544QW/xFdGCpG0JjTNU1LyOdt3zOGs7IWkpl7QrmOO5S3gm29+w6RJnxMbkxFgCSOfjqyJsHaDdkfctjoMjSxrFlDgrtIuBY0GPG5Qk8nU4pO5N15LdzHQaAJHVdVBgHa7QQESEz0Kuq2yWzQbCiu0GzSIKKcbt92JMfFU3Sij1fPaVenAmBTT0qHdnqeffpolS5Y02nb99dfz+OOPh0giTShQSuFwOHzZw+eee24Td+PChQvp3bt3xChrU6dOZerUqaEWQ6PpEFX2g5hMSVjakQnqxZroCSuotO0hPf3iNkZrOoJW1oKIq+pU2Q4v3mSD7pxk0B4ef/xxrZhpcLlcKKV8hXA3btzY7Lji4uKIUdY0mkikquoQCQlDOhR7ZjJZiYsdoC1rAUC7QYOIt56aMaFBRfb4+jIE1f5Nie8usYjhTiR+z+Ess7c0hLc8R0sYjUatrIUp4Xx9adpPVdUBEuKHdPi4ROtIKm1aWfM3WlkLIu7qestafENlzfPanzFrsbGxFBcX6x/NAKOUori4mNjYlhschxvhfm10RFlzu92NerhqQk8krglNU+rqSnA4SkhI6LiyZk0cSXX1UZzOVlu2ajqIdoMGEbfdcyPyWtMADHEmEHDZ/WdZy8zMJC8vj0hpbh/JxMbGkpmZGWox2k24XxvV1dXU1dW12aKsrq4Ou91OSUmJr5SHJjyItDWhaUqV/RBAh8p2eEm0jgIUtqr9pCR3rPWfpmW0shZEvK5OQ9ypr10MgsSacNv9Z1kzm80tFhTVhBYRmQH8EU9rndeVUs+etj8GWACcDRQDNyqlckVkIvCqdxgwTym1rKPnD/drY9GiRRQXFzN37txWxx09epRly5Zx6623MmRIx5/+NRpNy9i9maCdcINaG2SEamXNf2g3aBDxKWvxjXVkQ7zJZ3XTdF9ExAi8DFwOjAJuFpFRpw37IVCqlBoCzAd+X7/9a2CCUiobmAG8IiLd7mGrtLSUlJSUNsd5+1W2ZYHTaDQdp8p+CIMhjtjYvh0+NiamDyZTCpW2iG/lHVZoZS2IuO1OMAlibuy2McSb/Z5goAlLJgIHlVKHlVJ1wCJg1mljZgF/r3+9FJgmIqKUsiulvBdJLBCeQY06k7cAACAASURBVGddQClFWVlZu5Q1q9WKiGhlTaMJAFVVB0lIGIxIx1UEEcGaOEJnhPoZrawFEVXtxBBnbrLdGO9fN6gmbOkHHGvwPq9+W7Nj6pWzciANQETOFZHdwC7gRw2UNx8icreIbBGRLeEal9YSNTU11NbW0qNHjzbHGo1GrFZru5S1kpIS/v3vf1NR0b3bumk0/sJedYj4djZwb45E6yhsVftxu7URwl9oZS2IuO2ORvFqXgxx2g0aJTRXsOh0C1mLY5RSG5VSo4FzgMdEpEnKnVLqVaXUBKXUhJ49e3ZZ4GDiVaaSkpLaNT45OblNZc3pdLJgwQLWrl3Lu+++G7ZZsBpNuOB0VlFTm09CF5Q1a+JI3O5aqqtz/SdYlKOVtSDirnY2iVeDejeobjcVDeQB/Ru8zwTyWxpTH5OWDJQ0HKCU2gtUAWMCJmkIsNk8qf7t7feZkpLSprK2Z88eysrKGD58OHl5eRw/frzLcmo03Rm7/TBAp8p2ePFkhEJlpY5b8xdaWQsi7mpn85a1eBOq1oVy6ZpR3ZzNwFARGSQiFuAmYMVpY1YAt9W/vg5Yo5RS9ceYAERkIDAcyA2O2MGho8qa17LWWq21vXv3kpiYyNVXX43RaGTPHv/cPE6cOMGnn36qXauabkdXynZ4SYgfjIgFmy6O6ze0shZE3PYWlLX6jgY6yaB7Ux9j9hPgY2Av8K5SareIPCkiM+uHvQGkichB4OfAo/XbLwS+EpEdwDLgXqVUUXA/QWCprKwEPMkD7SE5ORm32+1T8k7H7XZz6NAhhg0bRlxcHJmZmeTm5nZZTqfTyaJFi1i/fj3Lly/v8nzRjojMEJH9InJQRB5tZn+MiCyu379RRLLqt08UkR31/38lItcEW/buiL3qECJG4uMGdnoOg8FCYuIwyiu+8qNk0U23S/0PZzxu0KYJBl4FztPk3dJkv6b7oJT6EPjwtG1PNHhdA1zfzHELgYUBFzCE2Gw2zGYzMTEx7RrfsHxHc3FuRUVF1NXVMWDAAAAGDhzIZ599Rm1tbbvP0RyHDx+mrKyM/v37c/jwYYqLi0lLS+v0fNFMg3I2l+EJAdgsIiuUUg1NoL5yNiJyE55yNjdyqpyNU0T64HmYWdlc4o2m/VTZDxEXNxCDoWv3ouTks8nPX4zb7cBgaHrf03QMbVkLEsrpRtW5WnCD1lvWdEaoJoqprKxst1UN2q615o1P69fPk3CbmZmJUorvvvuuS3Lu27ePmJgYZs70GEMPHTrUpfmiHF3OJsyoqjrUpeQCLynJZ+N212hXqJ/QylqQaKkgbsNt7ir9QKiJXmw2W7vj1aBtZS0/Px+LxeKzevXp0wfwxJt1haNHj5KVlUV6ejopKSkcPny4S/NFOQEvZ6NpP263g+rq3C7Fq3lJTvF0Lygr39rluTRaWQsazbWa8uKzrOmYNU0U01HLWmxsLLGxsa1a1vr27YvB4PmZs1qtJCQkdElZq6mpobi4mL59+yIi9O/fn/z80xN6NR0g4OVsIrn2YLCx2w+jlJPEhGFdnis2JoPY2H6Ul2llzR9oZS1ItK6s1VvWqrUbVBO9dNSyBh7rWllZWZPtTqeTEydO0Ldv43Y5GRkZXVLWvIqZ17WakZFBRUUFdru903NGOQEvZxPJtQeDTUXlLgCsVv9UBUpOPpuy8q26vqEf0MpakDjlBm0aaCkxRjCgC+NqohaHw0FdXR0JCQkdOq6lwrgFBQW43W6fUuUlIyODwsJCnM7OrTVvvJtXCczIyAC67lqNYnQ5mzCisnI3RmM88fFZfpkvJfls6uoKqanJ88t80YxW1oKEN3mgOcuaiGCINWk3qCZqqa6uBiA+Pr5Dx7WkrJ2eXOAlIyMDt9tNcXFxp+QsKioiISHBJ2fv3r0Brax1Fl3OJryorNxNYuIoPEm6XSc5Wcet+QtduiNIeK1m0oyyBrqZuya68boR4+LiOnRccnKyr6dow3Icx48fJz4+3peE4MWrXBUUFPhed4TTy3QkJiYSHx9PUZHWETqLLmcTHijlorJyD3373uC3ORMTh2E0JlBRvoM+GVf7bd5oRFvWgkRrMWve7bp0hyZa8SprHbWseZu+l5Q0CmEiPz+ffv36IdI4Nj0tLQ2j0UhBQUGn5CwuLiY9Pb3RttTU1Cbn12giDbv9CG53NUnW0X6bU8SI1TqGCl0ct8sERVkTkfdE5Hsi0uHziYhRRLaLyKpAyBYsVLUTiTUhhuYSmzxJBtqyFjnMnj2b//u//2u11ZGm/XTWDepVnBpatmprazl58mQTFyiA0WikZ8+enVLWqqurqaqqalIANy0trdNu1e6EXhORTWXlbsB/yQVekpPGUWnbi9td69d5o41gWdb+AnwfOCAiz4rIiA4cez+eWIaIpqUm7l4kzqQTDCKIH//4x/zjH/9g6NChPProo+zbty/UIkU0nXWDpqWlISI0LMnQUryal169enVKWfMqZKcra6mpqVRWVlJXV9fhObsTek1ENhWVX2MwxBDvh4K4DUlKykYpB5WVEX8bDylBUdaUUp8qpW4BxuPJ1vlERL4QkTtEpMU+FCKSCXwPeD0YcgYSt93RogsU6t2g2rIWMVx66aW88847bNu2jaysLC677DIuuOAC3nzzTRwO7c7uKJ11g5pMJnr06NHIstaWsta7d28qKys7XG6jJWXN+z7aXaF6TUQ2nuSCkRgM/g1lT0o6E0C7QrtI0GLWRCQNuB24C9gO/BGP8vZJK4f9AXgYaNauHknFDt3VzTdx92KIN6NqnCi3rkcTKRQXF/PWW2/x+uuvc9ZZZ3H//fezbds2LrvsslCLFnFUV1djsVgwmTp+o0hPT29kWcvLyyMtLa1Fxc+bWFBYWNih8xQXFyMivjg5L6mpqYBW1kCviUhFKTeVlbv97gIFiInJwGLpRUXFTr/PHU0EJRtURN4HRuDJ3LlKKeVtzrdYRLa0cMyVQKFSaquITG1ujFLqVeBVgAkTJoS1luOudmJOabl5tCHOBApUjRNpphabJry49tpr2bdvHz/4wQ9YuXKlr5XRjTfeyIQJE0IsXeRht9s77AL10qdPHw4cOEBtbS0Wi4W8vDzOOKNlV07DjNCsrKx2n6e4uJiUlJQmCqVW1jzoNRG5VFcfxeWy+TW5wIuIkJR0pq/grqZzBKt0x+v16dk+RCRGKVWrlGppFU8CZorIFXia9CaJyNtKqVsDLWwgcNvbsqyZTo3TylrYc9ddd3HFFVc02uYtH7Fly5YmWYia1rHb7R12gXrxNmjPz88nLi6OqqoqBg0a1OJ4b7mNjsatNZcJCm23vYoW9JqIXE4lF/hfWQNITBxBUdEaXK4ajMYmHcE07SBYbtCnmtn2ZWsHKKUeU0plKqWy8FS1XhOpippSCne1A0Ncy0qYV5HTcWuRwS9/+csm284///wQSNI9qK6u7rSy5i3RceTIEQ4cOADQqmVNROjdu3eHlDVvId3T49W8pKSkNNv2KprQayJyqazcjYiFhIShAZk/MXEE4KbKfjAg80cDAbWsiUgG0A+IE5GzONWQNwno3C9zBKLqXOCm1WxQ3cw9Mjhx4gTHjx+nurqa7du3+3re6f6QXcNutzeJBWsv8fHxZGVlsXPnTgwGA5mZmSQlJbV6TK9evdi2bRtut9vX6L01KisrcTgcLSprycnJUesG1Wui6zgcDvLy8qipqQnJ+evqLiC1x3ns338oIPO73Zmk9niFb4/WYjRGX1ZobGwsmZmZmM2d95oF2g06HU9SQSbwYoPtlcD/tHcSpdQ6YJ0f5Qoq3pIcbWWDesbqrKlw5uOPP+att94iLy+Pn//8577tVquVZ555JoSSRTZdcYMCnH322SxduhTwZCW2Re/evXE4HJSWlraogDWkpUxQLykpKRw5cgSlVNS5+/Sa6Dp5eXlYrVaysrKCfv0opbDZ9mIyJRMX13wGtT/OUWkTLOY0YmP7BOQc4YpSiuLiYvLy8loNz2iLgCprSqm/A38XkdlKqfcCea5wpq3uBdAgZk1b1sKa2267jdtuu4333nuP2bNnh1qcboHL5aK2trZLytro0aOpra3FYDAwcuTINsc3TDLwl7JWV1fXJXdupKLXRNepqakJiaIGoJQDpVwBjSUTEYyGWFzu6oCdI1wREdLS0uhqxYpAu0FvVUq9DWSJyM9P36+UerGZw7odPstaa27QOFOjsZrw5O233+bWW28lNzeXF19sevk2tCxo2oe3e0Fns0HB84N49tlnt3t8z549EREKCgoYNWpUm+OLi4sxmUxYrdZm96ekpABQVlYWdcqaXhP+IVQWWZfLs/6Mxs6vv/ZgMMTidFZEpfXZH5830G7QhPp/EwN8nrDGXe1xbbaW5SlGA2IxajdomFNVVQWAzWbr1PEiMgNPjUEjnizpZ0/bHwMsAM4GioEblVK5InIZ8CxgAeqAXyil1nTyY4QVnS2I2xUsFgs9e/YkLy+vXeNLSkpIS0trMb7N2zC+rKyMvn37+k3OSKCra0ITWjzKmmAwBDZL02iMxeEoRSknrdTC17RAoN2gr9T/+5tAnifc8bo2pRU3KOj+oJHAPffcA8Cvf/3rDh8rIkbgZeAyIA/YLCIrlFJ7Ggz7IVCqlBoiIjcBvwduBIrw1CjMF5ExwMd4kncins72Be0qWVlZbN++HafT2WYx3uLiYp/rtDm8lrVoLN/RlTWhCT1udzUGYwydaN3dIbzKoNtdg8GglbWOEqxG7s+JSJKImEXkXyJSJCIRWYajM7QnwcC7XytrkcHDDz9MRUUFDoeDadOmkZ6ezttvv93WYROBg0qpw0qpOmARMOu0MbOAv9e/XgpMExFRSm1XSuXXb98NxNZb4SKezvYF7SqDBg3C4XD42lO1hMvlajMRIS4uDovFEtXlOzq5JjQhxuWqwWjwrL1ly5YhIr6+rm63m/vuu48xY8YwduxYzjnnHI4cOdLiXFlZWYwdO5axY8cyatQofvnLX1Jb62ng7lXW5s//Q6O6hIWFhQwaNIgTJ0745rn33nt59tlnWbduHSLCG2+84du3fft2RIQXXngB8BRdzs7OJjs7m6ysLLKzswFPhu1tt93G2LFjGTlyJL/73e98c/zzn/9k+PDhDBkyhGefPeXcuOWWWxg+fDhjxozhzjvv9LVJU0px3333MWTIEM4880y2bdvmO2bGjBmkpKRw5ZVXdvSr7xDBqrP2X0qpCuBKPBaFYcAvgnTukOOudoJJEHPrX7chXjdzjxRWr15NUlISq1atIjMzk2+++Ybnn3++rcP6AccavM+jqXXMN0Yp5QTKgdO1hNnAdqVU7ekniKQWbF5C4QYFGDhwIACHDrVerqCsrAy32+3rVNAcIhL1tdY6uSY0IcTtdqCU05dckJOTw4UXXsiiRYsAWLx4Mfn5+ezcuZNdu3axbNkynxW5JdauXcuuXbvYtGkThw8f5u677wbAYDAhBjOLF7/HOeecw7JlywBPGZ1HHnmEhx56CIBt27axfv16HnzwQQDGjh3L4sWLffMvWrSIcePG+d4vXryYHTt2sGPHDmbPns21114LwJIlS6itrWXXrl1s3bqVV155hdzcXFwuF3PnzuWjjz5iz5495OTksGePx7lxyy23sG/fPnbt2kV1dTWvv+5pS/7RRx9x4MABDhw4wKuvvsqPf/xj3/l/8YtfsHDhwk7+BdpPsDoYeG2eVwA5SqmSaAowVHYnhjhzm0GGhjgTjkJdlygS8D5xffjhh9x8882t3sgb0NwFcHqbtFbHiMhoPK7R/2ruBJHUgs1LqNyg3vpsu3fv5uKLL25xfXqbxLeVNRrtylon14TmNL755rdU2vxbi8yaOJJhw37VZLvb7anrZjDEYbPZ+Pzzz1m7di0zZ85k3rx5fPfdd/Tp08cXq5mZmdnucyYmJvLXv/6V/v37U1JSQmpqKkdzC7DZbPzv//6RZ555httvvx2Au+++m7///e+sXbuWxx9/nJdeeslXk2zAgAFUVFRQUFBAr169+Oc//9mkUwZ4rF/vvvsua9Z4QnlFhKqqKpxOp6/3cFJSEps2bWLIkCEMHjwYgJtuuokPPviAUaNGNZp34sSJvpjWDz74gDlz5iAinHfeeZSVlfm+m2nTprFu3bp2fy+dJViWtZUisg+YAPxLRHoCoan+FwLcdkermaBeDPFm7QaNEK666ipGjBjBli1bmDZtGidPniQ2ts0A3Tygf4P3mUB+S2NExAQkAyX17zOBZcAcpVRgqleGALvdjtFo7FLByM4yduxYiouLW3WFehu+9+rVq9W5kpOTozJmzUsn1wQiMkNE9ovIQRF5tJn9MSKyuH7/RhHJqt9+mYhsFZFd9f9e4vcP1c3xZoIaDLEsX76cGTNmMGzYMFJTU9m2bRs33HADK1euJDs7mwcffJDt27d3aP6kpCQGDRrk6yyydOmHXHfdDC68cBL79+/3rS2DwcBf/vIXZs+ezbBhw5gyZUqjea677jqWLFnCF198wfjx44mJaRoB8tlnn9G7d2+GDh3qOyYhIYE+ffowYMAAHnroIVJTUzl+/Dj9+5/6Gc7MzGyy/h0OBwsXLmTGjBkA7Tom0ATFsqaUelREfg9UKKVcIlJF01idbou7uvW+oF4McR43aDSmNkcazz77LI888ghJSUkYjUYSEhL44IMP2jpsMzBURAYBx/G0Ufv+aWNWALfhacd2HZ42a0pEUoD/Ax5TSn3u1w8TYrwFcUNxzY8ePZrVq1fzxRdfcMMNNzQ7pqCggOTk5DYVj5SUFGpqaqiurg56/F040Jk1oZNumtKcBSxQuOqD/Q0GIzk5OTzwwAOAx9qUk5PD888/z/79+1mzZg1r1qxh2rRpLFmyhGnTprX7HN6OFgBLlqzg7befBxxce+21LFmyhLlz5wKQnZ3NmDFjuPfee5vMccMNN3DjjTeyb98+br75Zr744osmY3Jycrj55pt97zdt2oTRaCQ/P5/S0lImT57MpZde2kgeL6f/9tx7771MmTKFyZMnN/kMLR0TaILlBgUYiafeWsNzLgji+UOG2+7EmNr2E6Yh3gQuhXK4EYsxCJJpusLevXvJzc3F6TxlDZ0zZ06L45VSThH5CZ6bihH4m1Jqt4g8CWxRSq0A3gAWishBPBa1m+oP/wkwBPiViHh/zf9LKVXo788VbEJZSDY2NpaJEyfy2WefceLECTIyMpqMKSgoaDUT1EvDjNBoVNag42uCBkk3ACLiTbppqKzNAubVv14KvORNumkwxpd001wsp6Z53K4aDIY4iouLWbNmDV9//TUigsvlQkR47rnniImJ4fLLL+fyyy+nd+/eLF++vN3KWmVlJbm5uQwbNoydO3dy8OBhrr76HkSM1NU5GTx4sE9ZA4+FrbnyOBkZGZjNZj755BP++Mc/NlHWnE4n77//Plu3bvVt+8c//sGMGTMwm8306tWLSZMmsWXLFvr378+xY6dCh/Py8hqV2/nNb37DyZMneeWVV3zbMjMzWz0mGAQrG3Qh8AJwIXBO/f8TgnHucMDTxL09lrX6/qA6ySDs+cEPfsBDDz3E+vXr2bx5M5s3b2bLli1tHqeU+lApNUwpdYZS6un6bU/UK2oopWqUUtcrpYYopSZ6b2JKqaeUUglKqewG/0e8ogYey1oolZvzzz+fuLg4PvzwwyZP0E6ns82yHV4aFsaNRjq5JnTSTYhQyoXbXYvRGMvSpUuZM2cOR48eJTc3l2PHjjFo0CD+85//kJ/vidRwu93s3LnTl5jTFjabjXvvvZerr76aHj16kJOTw69//Wt2ff0x+/ZtJD8/n+PHj3P06NF2zffkk0/y+9//HqOxqSHj008/ZcSIEY1i6gYMGMCaNWtQSlFVVcWGDRsYMWIE55xzDgcOHODIkSPU1dWxaNEiZs6cCcDrr7/Oxx9/TE5OTiOlcebMmSxYsAClFBs2bCA5OZk+fYLbNitYlrUJwCjVnC0xCnDbne2KWZOG/UFTukVVhm7Lli1b2LNnj3ZX+4Hq6uo248ECSXx8PJdeeikrV65k165dnHnmmb59+fn5uN3udj1FR7uy1sk1oZNuQoTL5S2pEUdOTg6PPto4XHD27NncfvvtpKam+spvTJw4kZ/85CetznvxxRejlMLtdnPNNdfwq195HAGLFi3io48+wmgw+dpOXXPNNSxatIhHHnmkTXkvuOCCFvctWrSokQsUYO7cudxxxx2MGTMGpRR33HGHb22/9NJLTJ8+HZfLxZ133sno0aMB+NGPfsTAgQM5//zzAbj22mt54oknuOKKK/jwww8ZMmQI8fHxvPnmm77zTJ48mX379mGz2cjMzOSNN95g+vTpbX6ejhIsZe1rIAP4LkjnCxuUw41yuNuZYKD7g0YKY8aM4cSJE0F/uuqOdLWJuz8466yz2Lp1K6tXr2bo0KE+S9+3334LeJ7S2yI+Ph6z2Ry1ylon10RHkm7yoiXpJhi43d42U7HNZjPed9993HfffR2aMzc3t8V93vps1dV5vrZTp7cnO12OqVOnMnXq1CZzzZs3r9H7t956q8mYxMRElixZ0qwsV1xxRbMZpQ3d9w0REV5++eVm93322WfNbvc3wVLW0oE9IrIJ8JmplVIzg3T+kHGqiXvbmW5eV6nSylrYU1RUxKhRo5g4cWKjzKQVK1aEUKrIw+12h0VAvsFg4Morr+S1115jzZo1fO973wPg8OHDpKenk5CQ0MYMutZaJ9eETroJES5XDSLGoLd+0m2nOkewlLV5QTpP2HGqL2j7SneAjlmLBE5/stN0jtraWpRSIbesAfTt25eJEyeyceNGxo0bR2pqKkeOHGHSpEntniOalbXOrAmddBM63O5qDIbYToVynHvuuT7XqJeFCxcyduzYNo/Vbac6R7BKd/xbRAYCQ5VSn4pIPJ6F2e1pb6uphmO8Cp4mfLnooos4evQoBw4c4NJLL8Vut+NyuUItVsQRqu4FLXHxxReze/duVq5cSf/+/VFKMWbMmHYfn5KS0ihrLJro7JpQSn0IfHjaticavK4Brm/muKeAp7oueXgQzJJNSilc7hos5s4VLt64cWOnz+1V1lyuGkwma6fniST8Ea4frGzQ/8aTcu3Nhe0HLA/GuUONT1mLb/sJQiwGMIq2rEUAr732Gtddd52vifXx48e5+uqrQyxV5BGqvqAtERsby8yZMzl58iRbtmzhzDPPbLacR0t4a63V1ERNzW8fek10ntjYWIqLi/1yU28PbnctKIXBEPx1ZzCYMBjMvpi57o5SiuLi4nYViG6NYLlB5+Kpp7MRQCl1QERCl/4VRHxu0HZY1kREN3OPEF5++WU2bdrEueeeC8DQoUN91bg17SfcLGsAw4YN45577uHkyZOMGDGiQ8c2zAjtiJLXHdBrovNkZmaSl5dHsEqLuFx2HI5SLBaFwXCi7QP8TF1dMUo5iYmpCvq5Q0FsbGyHWnU1R7CUtVqlVJ3XxFuf0RMVKdSnLGvt+6oN8VpZiwRiYmKwWCy+906nU5fx6ASh6gvaFr17925XbbXTiWZlTa+JzmM2mxk0aFDQznfw4HMUnvwbUy/aicFgafsAP3P48B85kvsSUy/6CqMxvNZ+uBKs3qD/FpH/AeJE5DJgCbAySOcOKe5qJxhAYtoXomeIM3vqrGnCmosuuohnnnmG6upqPvnkE66//nquuuqqUIsVcYSbG7SrRHOtNb0mIgebbS8JCWeERFEDsFpHA25stn0hOX8kEixl7VHgJLALuAdPMOkvg3TukOK2OzDEmdv9hOntD6oJb5599ll69uzJ2LFjeeWVV7jiiit46qluE+scNOx2OyLS5XiOcCGaa63pNRE5VNr2kZjYMRe/P/Eoa1BRuTtkMkQawcoGdYvIcmC5Uiqq+n24q9vXvcCLId6E40R0+PEjGYPBwNVXX83VV19Nz549Qy1OxOLtC9pd3GXRXGtNr4nIoK6umLq6QhITR4ZMhpiYDMzmVCq1stZuAmpZEw/zRKQI2AfsF5GTIvJEW8d2F9x2Z7uSC7zoBIPwRinFvHnzSE9PZ8SIEQwfPpyePXvy5JNPhlq0iCQcuhf4m2hT1vSaiCy8rkdrCJU1EcFqHa2VtQ4QaDfoA8Ak4BylVJpSKhU4F5gkIj8L8LnDAneVA0NC+wv/GeLNqFoXyuUOoFSazvKHP/yBzz//nM2bN1NcXExJSQkbN27k888/Z/78+aEWL+IIdRP3QBBtyppeE5FFpW0vQEjdoABW6xiqqr7xlBHRtEmglbU5wM1KqSPeDUqpw8Ct9ftaRET6i8haEdkrIrtF5P4AyxoQXLaOKmu6P2g4s2DBAnJychplbg0ePJi3336bBQsWhFCyyMTrBu1ORFutNb0mIgubbS8xlt5YLGkhlcNqHY1STmy2b0IqR6QQaGXNrJQqOn1jfdxaWxqME3hQKTUSOA+YKyKjAiBjwFBuhbvKgTGx/Rk3vi4GOskgLHE4HKSnpzfZ3rNnTxwOncXbUbqrGxSiJyNUr4nIwmbbR6I1tFY1gKT6JAPtCm0fgVbW6jq5D6XUd0qpbfWvK4G9eDofRAyqxgluhSGxA5a1OG1ZC2ca1pHqyD5NU5RS3dYNClBaWhpiSYKDXhORg9tdR1XVoZAmF3iJje2PyWSl0qaVtfYQ6GzQcSJS0cx2Adqdqy8iWcBZ1HdAiBRcVZ6nSmNHlDVvM/cq/UQajnz11VckJSU12a6Uihq3l7+oq6vD7XZ3O8taWprHvVRcXBxiSYKDXhORQ1XVQZRyhDxeDeqTDBJ1kkF7CaiyppTqcrN2EUkE3gMeUEpVnLbvbuBugAEDBnT1VH7HbatvNdWRmLVErayFM7pZu/8Ix1ZT/iA2NpaEhISoUdb0mogcbPXJBaHMBG2I1TqavOMLcbsdGAztv09GI8EqitspRMSMR1F7Ryn1/un7lVKvKqUmg49VMAAAIABJREFUKKUmhGNdH5dXWetAzJo3vs1V2aqXWKOJeLpb94KGpKenU1TUJFxXowkpFZVfYzTGEx8fvNZWrWG1jsHtrsNuPxxqUcKesFXWxFMl8w1gr1LqxVDL0xncVR6Fy9gBy5qYDUisUStr3RQRmSEi+0XkoIg82sz+GBFZXL9/Y30IACKSVp8dbRORl4ItdyDorpY18LhCo8WypokcKip2YU0cjUiXnV5+wepLMvg6xJKEP2GrrOGpz/YD4BIR2VH//xWhFqojnHKDdszbbLRafMdqug/i+YV8GbgcGAXc3EyG8w+BUqXUEGA+8Pv67TXAr4CHgiRuwKmq8nTqSExMDLEk/ic9PR273e5rVK/RhBq324HNtgdr0thQi+IjPj4LozFet51qB0FpN9UZlFLr8SQiRCyuKgeGeBNi7JhObEi0aMta92QicLC+1iAisgiYBexpMGYWMK/+9VLgJRERpVQVsF5EhgRR3oBis9kASEhICLEk/sebZFBUVET//v1DLI1Gg68AbZI1fJQ1ESOJiSN1kkE7CGfLWsTj7mBBXC9Gq1lb1ron/YBjDd7n0bQcjW+MUsoJlAOhrV4ZIGw2G2azmZiYmFCL4neiLSO0K+jQgOBQUbETgKSkM0MsSWOs1jHYbHtQSieqtIZW1gKIy+boUI01L0ZtWeuuNGcpVp0Y0/IJRO4WkS0isuXkyZMdEi7YVFVVdUsXKECPHj0wGAxaWWsDHRoQPCoqdmIyJRMXNzDUojQiyToal8uO3Z4balHCGq2sBRB3ZV2Huhd4MVgtqFoX7jr9pNHNyAMa+sQygfyWxoiICUgGStp7gnDPkG6IzWbrli5QAKPRSGpqKoWFhaEWJdzxhQYopeoAb2hAQ2YBf69/vRSY5g0NqA+X0cXc2kFF5S6SrGPx5O6FD1brGEB3MmgLrawFCKUUropajMkdd/EYrfW11rQrtLuxGRgqIoNExALcBKw4bcwK4Lb619cBa5RS7basRRI2m63bWtYAevfuTUFBQajFCHcCHhoQSdbmQOF02rDZ9pOUPC7UojQhPv4MDIYYnRHaBlpZCxCqxoWqc2NM7pxlDXStte5G/Y3mJ8DHeNqnvauU2i0iT4rIzPphbwBpInIQ+Dngi+ERkVzgReB2EcmLtF65p9Od3aAAffr0oaysTGeEtk7AQwMiydocKMrLtwFuUlImhlqUJhgMJhITR2jLWhuEbTZopOMqrwXonGWt3nXq1spat0Mp9SHw4Wnbnmjwuga4voVjswIqXBBxuVzY7fZu6wYFyMjIAKCgoICsrKzQChO+dCQ0IK8zoQEaKCvbjIiR5KSzQi1Ks1itoykoWIlSKuzctOGCtqwFCJ+yltRxy5rXGuesn0Oj6W505xprXrzK2okTJ0IsSVijQwOCQFnZZqzWMZhM4flwZE0cjdNZSXV1bqhFCVu0shYgXBX13Qs6YVkzJJgRswFXqVbWNN0Tb4217qysJSYmkpiYyHfffRdqUcIWHRoQeFyuWsorviIl5ZxQi9IiXvdsSemXIZYkfNFu0ADhKq8F8XQj6CgigjElBleZTnLSdE/Ky8sBSE5ODrEkgaVfv34cO3as7YFRjA4NCCwVFTtQqo6U5PBV1uLjBxEb05eSkvVk9vt+qMUJS7RlLUC4yuswJJoRU+e+YmNKDM4ybVnTdE8qKiqA7q+sDRgwgJKSEiorK0MtiiZKKS75DyImevQ4N9SitIiIkJp6IaWlX+riuC2glbUA4Syr6ZQL1IupR6x2g2q6LeXl5ZhMpm7ZxL0hAwd6CpB+++23IZZEE60UF68jJXkCJpM11KK0SmrqhTidFZSVbwu1KGGJVtYChLOkBlNaXKePN6bE4K5y6MK4mm5JeXk5SUlJ3T7zq0+fPpjNZnJzc0MtiiYKqan5DpttH2npU0MtSpukpV2EwRBLQcGqUIsSlmhlLQAolxtXaQ2mtNhOz2Hs4TnWpTNCNd2QioqKbu8CBU8ng8GDB7N//350AqMm2BQXrwMgLW1qSOVoDyZTIunp0ygs/BC3WxeEPx2trAUAV2ktuMGU2nnLminVo6w5i3WSgab74bWsRQPDhw+noqJCl/DQBJ2Cwg+JixtIQvyQUIvSLjIyZuFwlFBUtCbUooQdWlkLAM5iT8VyU3rnLWvmnh5Fz1lg94tMGk244HA4qKioIDU1NdSiBIXhw4cjIuzerSu0a4JHbe1JSks30Lv3VRETbpCWehGxsZkcO/ZmqEUJO7SyFgCcRfXKWhcsa4Z4MwarBUehVtY03YuSEk/x+bS0drd3jGgSEhIYNmwY27Ztw+l0hlocTZRQWPh/gJuM3leFWpR2YzCY6J95G2Xlm6mo2BlqccIKrawFAEeBHUO8CUN9Q/bOYu4dr5U1TbejuLgYiB5lDeCcc87Bbrezc6e+AWkCj1KK/O+Wkpg4ioSEyHCBeunb93pMpiQOH/lTqEUJK7SyFgDq8m2Y+yR02fRs7hWPs8Ae1YHJtYfLKP/nEWwbv0M53KEWR+MHioqKAKLGDQpwxhln0K9fP9asWUNtrU4a0gSWsvIt2Gx7yex3S6hF6TAmk5WBA+6huHgtZWVbQi1O2KCVNT+j3ApngR1zn6630TH1ikfVuaKy3ppSirJVhzn56i4q/51H2bKDFLy03dfGSxO5FBcXY7VaiYnpfB3CSENEmDFjBjabjVWrVkX1A5gm8OTlLcBkSiIjY1aoRekU/fvfhsXSk4OHntdrpR6trPkZZ1E1yuHG3KfrDXMtmR6Fr+5YRZfnijTsWwuxrT9Ownl96PfkBaTdPhpXaQ1Ff9ula89FOCdOnKB3796hFiPo9O/fn4svvphdu3bx8ccf65uQJiDYbPspLPyIfn1vxmjsfNx0KDEa4xg06D7Ky7dQUKjrroFW1vxO7RFPz0PLwK6XJTD3SUTMBuqORlerGkehnbIPDhIzOJmUmWcgZiNxI1JJu3UUjgI7ZSsOhVpETSdxOBwUFhbSp0+fUIsSEqZMmcK5557Lhg0bePfdd6murg61SJpuxqHDL2I0JjBw4H+HWpQu0a/vjVitYzlw4CkcjvJQixNytLLmZ2oPl2NIsnSpIK4XMQqW/lZqc6PnQlUOFyX/2ItYDKTeNBwxnIr7ix3WA+vU/ti3FGD/6mQIpdR0lhMnTqCUom/fvqEWJSR43aGXXXYZ+/bt45VXXuHAgQOhFkvTTThRsJKiok/JyroXs7lHqMXpEiJGRo54GoejlL37Hot6S7RW1vyIcitqD5URMzjZb3VtYoam4MivippOBmWrDuM4YafHDcMxJjWNaUq6dACW/lZKlx3AWaYLBkcaR44cATwNzqMVEWHSpEnccccdGI1G3nnnHZYsWUJpaWmoRdNEMEVFa9i791GSks5iQP8fhlocv2C1juaMMx7m5MmPORLl2aGmUAvQnag9Uo7b5iBulP9KEsSNTqfi46NU7y4m8YLubY2w7zxJ1cYTJE7pR9zw5jMFxeixuBX8cTsli/bT8+4zG1nfNOHNoUOHyMjIICGh6zGdkc6AAQP48Y9/zPr16/nss8/Yu3cv2dnZnHvuuVEZ06dpH3Z7LkePvkJp2SbcrmoMxjjcrmpq6wpITBzBuDP/isHQfW7tA/r/kCrbfo7k/gmlHAwe/HNEos/O1H3+omGAfUsBYjESO8J/JQnMveIxZ8RTtfkECef3iZhK1B3FUVBF6dJvsAywkvxfWa2ONaXFkTLrDEqXfEPl2mMkTYteK00kUV5eztGjR7noootCLUrYYDKZmDp1KuPHj2f9+vVs3bqVbdu20bdvX8aMGcPIkSPp0SOy3Vka//HdieXs3/8ESrlJS5uM2ZSCy2VHDGaSk8fTt89sDIbulWUtIowc+SwiJnKP/gWbbT+jRj2P2ZwSatGCSlgrayIyA/gjYAReV0o9G2KRWsRRaMf+VSGJF/TDYDH6de7ECzMpXfoNNXuKiRud7te5wwFnSQ1Fb+5GLEbSbhmJmNp+aoof34uaA6VUfHIUY5KFhHMygiBp12nrmhaRGGABcDZQDNyolMqt3/cY8EPABdynlPo4iKJ3mS1bPDWTxo0bF2JJwo+kpCSuuOIKLrroInbt2sWOHTtYvXo1q1evJiMjg5EjRzJy5Eh69uzZ7R7YonlNtBens4pvvvkN3514j+TkCYwZPZ/Y2O7taWmIiJERI54h0TqKAwee4ssN/8XQIY/Qu/dMDIauFZ+PFMJWWRMRI/AycBmQB2wWkRVKqT2hlawpbruDkpx9SIwJ60WZfp8/PrsntvV5lC47iKl3Aub0yEzHPh2lFDV7Syh9/wDKpeh511iMye17KhQRUq8bRlGVg9L3DuA4WU3StAEYYvyrKPuTdl7TPwRKlVJDROQm4PfAjSIyCrgJGA30BT4VkWFKqYioY1JYWMiGDRsYPXp0VBXD7SgJCQmcd955nHfeeZSUlLB371727dvH2rVrWbt2LampqYwcOZIRI0bQt29fjMbwvd7bQzSvifaglKKk5DP27/811TXHyMr6CYOyftqt3JztRUTon/kDUpLPZt/+X7Jn78McPPQC6emXkJY6hR49zu3W1rZw/otPBA4qpQ4DiMgiYBbQYWXNWVIDSoHnP99rvK/Bs081ft/oNZ6F0/A4t91J3XEbVZtP4K5ykD5nFEarpcMftC3EZCD15hGcfHUnhX/aTsLEDGKykjyKjcmAGMUTtxWmD9xKgXK4UQ4XON24bA4cJ6qo2VuC47sqTL3jSfv+CMy9OxbHJCYD6XNGU7byELb/5GHfcoK4MelYMq0Ye8RgiDUhFgPIqe9GGrymixYKMRkwJnXo792ea3oWMK/+9VLgJfGYUmYBi5RStcARETlYP9+XHZVbKUVpaakvu6or/7Y1xul0kpeXx5dffklMTAzTp0/vqLhRS2pqKpMmTWLSpElUVFSwf/9+9u7dy5dffsnnn3+OyWSib9++ZGRk0KNHD1JSUoiNjcVisWA2mxERnxWupX/9jdlsJjGxQwXBw2RNuKipOV5/3Xr/9+5r+F6hfDcLfNvVqZtEo+NPjW0wX5PjVaPjlXJTW3sCW9U3FBetwVa1n7jYAYwfn0OPlHM6+tG6HVbrKCacvZTi4n+Tn7+YgoJV5OcvAiAhYSgpKRNJTh5PbEwfzOYUREz1MW7i+zeYGI3xWCxdj2MPZ2WtH3Cswfs84NzOTHTixS3gDFzab8zgZJJ/MApLf2vAzmHunUCve7Mp/2cuti/zsa0/HrBz/X/23js+rvJK+P+eUe+yJBdZlots2ZbcBLbBGBJsU2JKTLFZYBM6L0sahASy2SS78SbZQCBLQt7wZmn7CxAwARKwAQMOYEIwGNwL7l2yJduSrN6mnN8fd0aWbZXR9NE8389nNKN7n/vcc+/cZ+655zklJAgkFmaQffU40mYM9Wrqs9tuEmwMuraY1OlDaVp1mJaNx2n+vCrAwnZP0rhsBt85pT+beHNNd7ZRVYeI1AO57uWrT9u2oL8yAzidTn73u9BGVo0ZM4Yrr7ySzEz/8w/GIpmZmcycOZOZM2fS2trK3r17KS8vp6Kigo0bN9LRERmVPUpKSrj++uv7s0lEjAm7/QSffDrXl02DiI3srOlMnPBf5OdfM+B80fxBxEZe3lzy8ubictmpb9hIXd3n1NWtoapqKYcPvxBuETvJz7+O0hL/PbgiWVnrTv09ReMSkbuAu6D3VACDFo4Hl1o9ipw0qIj7j5z8LF2tLl3buf8XzzpAkuNIGJKKLTk0pzE+N4Xcr5XganfiqG7F2dCOOhRcLtQZwTloRJB4G5JgvWypCSTkJSMJgZvCSRqVSdKoTNSlOE+04WzowNXmQDtcdJpUPYZRV2DOlQ9W1D6v6V7aeLOtV2PCZrNx9dVX92l18ea9rzZxcXEMHjzYRH8GkJSUFCZPnszkyZMBy/LT0tJCfX09HR0dtLe3Y7fbe7V8BousrKz+bhIRYyIuLoPSkkdO7k4EOeUGwMnffc8No8uNRE7eRNz3iS7/d2l76nK67KdLX2IjMWkIKcmFxMX5n69zoGOzJTAoe2an1dHlctDSso+OjuPYHfWoOi2LJS4Iwwx5SsqogPQTycpaBVDY5f8RwJGuDVT1SeBJgBkzZvT4K5R21pBgyBc2bElxJBakQ4H/9UcHGmIT4nNTiM+NSL++Pq/pLm0qRCQeyAJqvdzWqzFhs9koKyvz8RAMkYaIkJaWFq0KcUSMibi4JPLzr/XxEAyRhM0WT3r6eGB8uEUJKJGcrGQNUCwiY0QkEcuRdFmYZTIY/MGba3oZcIv78yLgA7XMIcuAG0QkSUTGAMXA5yGS22AIFmZMGAxeELGWNbdvwreBd7FCuv9XVb8Is1gGg8/0dE2LyM+Ataq6DHgGeN7tLF2LdfPC3e5lLMdrB/CtgRT1ZohNzJgwGLxDBkq9rRkzZqgnj5PBEG5EZJ2qzginDGZMGCIJMyYMhlPpz5gYMMqaiBwHDvbSJA+oDpE43mJk8p5IlKs3mUap6uBQCnM6XowJiLzzauTpm0iTyVt5omVMRCORdk2Eimg/bq/HxIBR1vpCRNaG+6nudIxM3hOJckWiTP0l0o7ByNM3kSZTpMkTi8TqdxBLxx3JAQYGg8FgMBgMMY9R1gwGg8FgMBgimFhS1p4MtwDdYGTynkiUKxJl6i+RdgxGnr6JNJkiTZ5YJFa/g5g57pjxWTMYDAaDwWCIRmLJsmYwGAwGg8EQdQxYZU1EckTkbyKy2/0+qId2ThHZ6H4FpUKCiMwXkZ0iskdEftjN+iQR+bN7/WciMjoYcvRTpltF5HiXc3NnCGT6XxE5JiJbe1gvIvI7t8ybReTsCJBpjojUdzlP/xFsmfxFRB4RkR3uc/iaiGS7l48WkdYux/I/IZSp1+sxRDIUishKEdkuIl+IyL3u5YtF5HCX83J5CGU6ICJb3Ptd617m1W9bkOSZ0OU8bBSRBhH5bjjPUawRaddEsOjut7en4wzHvSHkeIr9DrQX8DDwQ/fnHwK/6qFdU5DliAP2AkVAIrAJKD2tzTeB/3F/vgH4cwTIdCvw+xB/Z18Gzga29rD+cuBtrKrHs4DPIkCmOcCboTxPATimS4F49+dfecYGMLqn4wyyPH1ejyGSIx842/05A9gFlAKLgfvD9F0dAPJOW+bVb1uIvrcqYFQ4z1GsvSL5mgjwcZ7x29vTcYbj3hDq14C1rAFXAc+6Pz8LXB0mOc4B9qjqPlXtAF5yy9aVrrK+ClwkIhJmmUKOqn6EVU6mJ64CnlOL1UC2iOSHWaaoQ1VXqKrD/e9qrALY4SQirkdVrVTV9e7PjcB2oCDUcnhBpPy2XQTsVdWBmGQ22oiUayJg9PDb29NxhvzeEGoGsrI2VFUrwfoRBob00C5ZRNaKyGoRCcYFXgCUd/m/gjNvAJ1t3DfReiA3CLL0RyaAhW6T8qsiUhhEebzFW7lDzXkisklE3haRSeEWpp/cjvVE6mGMiGwQkb+LyJdCJEPEfa9uV4SzgM/ci77tHgv/G+IpJgVWiMg6EbnLvczb37ZgcwOwpMv/4TpHsUYkXxPBpqfjjLjfkEATsYXcvUFE3gOGdbPqx/3oZqSqHhGRIuADEdmiqnsDIyFgmWVP5/QQXG/aBBJv9vcGsERV20XkbqynmHlBlMkbQn2evGE9VsmQJrefzutAcZhl6nVsqOpSd5sfYxXAfsG9rhJrPNSIyHTgdRGZpKoNwRa3m2Vh+15FJB34C/BdVW0QkT8AP3fL9HPgv7GU3FBwvvv3aQjwNxHZEaL99oqIJAILgH9zLwrnOYo1IvKaCDMR9RsSDKJaWVPVi3taJyJHRSRfVSvd5tBjPfRxxP2+T0Q+xHqaDqSyVgF0tUqNAI700KZCROKBLII79danTKpa0+Xfp7B8m8KNN+cypHRVZFR1uYj8PxHJU9Ww1qvrbWwAiMgtwJXARep2+lDVdqDd/XmdiOwFxgPBrnwdMd+riCRgKWovqOpfAVT1aJf1TwFvhkqeLr9Px0TkNawpY69+24LMZcB6z7kJ5zmKNSL4mggFPR1nxPyGBIuBPA26DLjF/fkWYOnpDURkkIgkuT/nAecD2wIsxxqgWETGuJ9Gb3DL1pOsi4APPDfQINGnTKfN9y/A8t8JN8uAm92RP7OAeo9JPFyIyDCPf6GInIM1pmp63yq8iMh84F+BBara0mX5YBGJc38uwrIQ7guBSN6MkaDj/h6fAbar6qNdlncdC9cA3UYGB0GeNBHJ8HzGCgzZihe/bSHgRrpMgYbrHMUaEX5NhIKejjPi7g0BJ9wRDsF6Yfl8vQ/sdr/nuJfPAJ52f54NbMGKPtsC3BEkWS7HiizbizUNBfAzrJslQDLwCrAH+BwoCsH56UumB4Ev3OdmJTAxBDItwZqKs2M9Kd0B3A3c7V4vwONumbcAMyJApm93OU+rgdmhvM59PKY9WP4dG90vTyTywi7Hsh74aghlOuN6DMN5uQBr6mRzl3NzOfC8+3rbjHVTyA+RPEXu72KT+3vxjNNuf9tCeJ5SsR5IsrosC8s5irVXpF4TQTrW7n57e7qvh/zeEOqXqWBgMBgMBoPBEMEM5GlQg8FgMBgMhqjHKGsGg8FgMBgMEYxR1gwGg8FgMBgiGKOsGQwGg8FgMEQwYVHWxIuizSLyTyKyTayCyi+GWkaDwWAwGAyGSCDk0aDuPE67gEuwwnHXADeq6rYubYqBl4F5qnpCRIao6kBN8mcwGAwGg8HQI+GwrHlTtPn/AI+r6gmwMjWHWEaDwWAwGAyGiCAcypo3BVfHA+NFZJW7wPr8kElnMBgMBoPBEEGEozaoNwVX47FK3czBqvH1DxGZrKp1p3QkchdwF0BaWtr0iRMnBl5ag8EH1q1bV62qg8MpQ15eno4ePTqcIhgMnZgxYTCcSn/GRDiUNW8Lm69WVTuwX0R2Yilva7o2UtUngScBZsyYoWvXBrvetMHgHSJyMNwyjB49GjMmDJFCf8aEiBQCzwHDABfwpKo+dlobAR7DKgnWAtyqqut769eMCUMk0Z8xEY5pUG+KNr8OzIXOAuvjCU1BaYPBYDCEHwfwfVUtAWYB3xKR0tPaXIb1EF+MNcPyh9CKaDCEjpAra6rqwCp+/S6wHXhZVb8QkZ+JyAJ3s3eBGhHZhlVE/AFVrQm1rAaDwWAIPapa6bGSqWoj1r3idN/mq4Dn1GI1kC0i+SEW1WAICeGYBkVVlwPLT1v2H10+K/A998sQZKo7HDy47wjtLuXHY/PJT0oMt0gGg0/8cdV+Ptlbw/cuHc/EYZnhFscQAERkNHAW8Nlpq3oKVqs8bftO3+aRI0cGS8zA094I7/4I4pLg0l9AQnK4JYpcDqyCT34H026ASdeEW5qgEBZlzRA5nLA7+Or6XRxuswOwv7WdN88uxnIHMRiih0/2VLP4DStd45bD9fztexeSnmR+4qIZEUkH/gJ8V1UbTl/dzSZnJA493bc54EIGi3d/BOufsz7HJ8FX/gu73U5FRQVtbW3hlS0CSE5OZsSIESTYG+Glf4a2OtjzHgyeCENKwi1ewDG/ZDGMqnLv9kNUtNl5tWwse1ra+f7Ocj6ta2b2oPRwi2cw9IvnPj1IXnoiv7vxLP75qc946fND3PmlonCLZfAREUnAUtReUNW/dtPEm2C16KShEja8AOf8i2VhW/M0XPivVFTWkJGRwejRo2P6gVpVqampoaKigjGHXrUUtVvfghevh09+D1c/Hm4RA46pDRrDvHW8nhU1DfxkbD7nZqdzzdBBZMTZeLmqNtyiGQz9wuF0sWpPNZeUDmP22Dxmjh7Ei58dItQVWgyBwR3p+QywXVUf7aHZMuBmsZgF1KtqZQ9to4ttS0GdMPNOmH4rONpgx1u0tbWRm5sb04oagIiQm5trWRi3vAIjZ8PoC6BkAWx/Axwd4RYx4BhlLUZxqvKLfUcoSUvmjgIrzUtqnI15uZmsrG0wNzlDVLH1SAON7Q5mj80FYEFZAfuqm9lzrCnMkhl85HzgJmCeiGx0vy4XkbtF5G53m+VYWQL2AE8B3wyTrIFn53IYXAKDx0PhOZCRD7tXAMS8ouZBRMDlgOqdUOouglR6FbTXw8FV4RUuCBhlLUZ5v6aBA60d3Dd6GPG2k4P/wkEZHO1wsKPZ+EQYooeth+sBOHvUIAAuKRkKwMqdplJdNKKqH6uqqOpUVS1zv5ar6v+o6v+426iqfktVx6rqFFUdGAnUHB1Q/jmM+bL1vwiM/hIc+Di8cnWhqqqKG264gbFjx1JaWsrll1/Orl27mDx5crftHQ4HeXl5/Nu//dspy998803OOusspk2bRmlpKU888QQAO3fuZM6cOZSVlVFSUsJdd93VvSCOduvdc65GzQaxwaFPA3KckYRR1mKUPx6uZlhiApflZZ2y/Lxsy1dtXUNLOMQyGHxiz7Em0hLjGJ5lRcwNy0pmdG4qn+8/EWbJDIZ+UrkJHK2W4uFh9PnQfAyc9vDJ5UZVueaaa5gzZw579+5l27Zt/PKXv+To0aM9brNixQomTJjAyy+/3DlrY7fbueuuu3jjjTfYtGkTGzZsYM6cOQDcc8893HfffWzcuJHt27fzne98p/uOHW2QmmsFFQAkZ8KwqXDwk0AeckRglLUYpMHh5KMTjSwcNogE26km9dEpiWTHx7HRKGuGKGL3sUbGDc04ZYpo5ugc1h6sxeUyU/qGKKLcnaFk5Hknl3k+O8Pvi7Vy5UoSEhK4++67O5eVlZVRWFjY4zZLlizh3nvvZeTIkaxevRqAxsZGHA4HubmW60JSUhITJkwAoLKykhEjRnRuP2XKlO47dnZA4blg66LKjJoNFWvA6fD1ECMSEw0ag3xQ04BD4Su5Z+ahEhGmZaSysdEoa4boYffRJr48/tQSezNH5/DKugr2VTczboiJbjZECUe3Wj5qGUNPLssdB/Eppyo3tT6yAAAgAElEQVRrb/8QqrYEdt/DpsBlD/XaZOvWrUyfPt3rLltbW3n//fd54oknqKurY8mSJZx33nnk5OSwYMECRo0axUUXXcSVV17JjTfeiM1m47777mPevHnMnj2bSy+9lNtuu43s7OxTO3Y5LYVs2NRTl+dPsyxuNXtgyMCpF24sazHIezUN5CTEMT0rrdv1ZZmpbG9updXpCrFkBkP/aWizc6yx/QyFrHS49TCyvfL09FwGQwRTtRWGTjp1mS3OWhYB06D95c0332Tu3LmkpqaycOFCXnvtNZxOJwBPP/0077//Pueccw6//vWvuf322wG47bbb2L59O9dddx0ffvghs2bNor29/dSOHW2AwrDT/OSGuv8/ujXIRxZajGUtBlld38Ts7HTieogqmpaRglNhe3MrZ2d2r9AZDJHCkbpWAEYMSjllefHQdOJtwo6qBr46bXg4RDMY+ofTDsd3wLh5Z67Ln2pZ1lStoIM+LGDBYtKkSbz66qtet1+yZAmrVq1i9OjRANTU1LBy5UouvvhiwJrinDJlCjfddBNjxozhj3/8IwDDhw/n9ttv5/bbb2fy5MlnWvTs1rjvVM485I0HW4JldZyyyNfDjDiMZS3GONpup6LNzoxelLCSNOumt9NEhBqigMo66zodnn2qspYUH8fYwelsr2wMh1gGQ/+p3g0uOwztxkdr2BRQV9j91ubNm0d7eztPPfVU57I1a9Zw8ODBM9o2NDTw8ccfc+jQIQ4cOMCBAwd4/PHHWbJkCU1NTXz44YedbTdu3MioUaMAeOedd7DbLStiVVUVNTU1FBScVhrW3mpFfmaPOnV5fKIVcDDALGtGWYsx1jc0AzCjhylQgJEpiaTYhB1NRlkzRD6H3Za14VkpZ6wryc8w06CG6OHoF9b76dOgYOVdA/f0X/gQEV577TX+9re/MXbsWCZNmsTixYsZPnw4O3fuZMSIEZ2vJ554gnnz5pGUlNS5/VVXXcWyZctwOp08/PDDTJgwgbKyMn760592WtVWrFjB5MmTmTZtGl/5yld45JFHGDZs2KmCOFohLuHU4AIPQyfB0W1BPAuhx0yDxhjrGlpIEGFy+pk3Ng9xIhSnJZtca4aooLK+lXibMDgj6Yx1E/MzeX3jEepb7WSlJIRBOoOhHxzbBrZ4yCs+c11eMRxZdzK3WBgZPnw4L7/88hnLPdaw3sjJyeH48eMALF++vNs2jz76KI8+2lPhCjeOdmu6szvyimHzS9DeBEkDI7jIWNZijG1NrYxPSyI5rvevviQthR3NrSGSymDwnSN1bQzNTCbOdqYPZlGeZUE+UN0carEMhv5Tu9ea1ovrRglJzbWm/SJAWQs7Lof1iuvB3pQ7znqv3Rs6mYKMUdZijN0t7RSnJvfZbmJaMkc7HNTaB1auGsPA40hdKwXZ3VuKiwZbytq+alN2yhAF1OyD3LHdrxOxLElhngaNCDwKa0+WNY+yVrMnNPKEAKOsxRAtThcVbR1eK2uA8VuLIESkUERWish2EflCRO4Nt0yRwPHGdgZnnjkFClCYk4pNYP9xY1kzRDiqULsPcnpQ1sCyJBnLWhdlrQfLWk6R9V5jLGuGKGRvSxsKFKd5oaylu5U1MxUaSTiA76tqCTAL+JaIlIZZprBT09xBblpit+uS4uMozElln5kGNUQ6jVVgb+7ZsgZgi0edHVZC2FjG0W6VreppGjQxFbIKrejaAYJR1mKI3S3W00hxavdWiK4MS0wgKz7OBBlEEKpaqarr3Z8bge1AQe9bDWzsThf1rXZyelDWAMbkpbHPWNYMkY7Hv8pjFeqG5DilptmB2mP7d1ntbdS0QnJyz4Fy5I4dUNOgJho0htjd3IYNKPJCWRMRSkxEaMQiIqOBs4DPwitJeDnRYuWc6smyBpay9tm+WlT1lNqhBkNEUdO3sjYiJ5WKras43hYHCakhEiwCaawkub2aEbOu6blNzljY6n3y3kjHKGsxxO6WNkalJJLUXV6abpiYnsJfj5qbXKQhIunAX4DvqmrDaevuAu4CGDlyZBikCy21zZayNqgXZa1ocDqtdidHG9oZltW3C4DBEBZq91kO81k9F0RPyBvNmNVfhkt+BufHqMuqKjx0KUy9HhL+qed2g0ZBWz201kFKds/togQzDRpDeBsJ6mFiWjINDheH26OvHt1ARUQSsBS1F1T1r6evV9UnVXWGqs4YPHjwmR0MMDzKWm/ToJ70HfuOm4hQQwRTuw8Gje7ZDwsgOQuSs+HEmdUCYobWE9DeYJ2r3vBUNqg7FHSRQoFR1mIEh0vZ19LOuH4oayXuQITtTSbIIBIQy7z5DLBdVfvIGBkbeJS13LSep/bHuJW1vSbIwBDJ1B2CbC+s4YNGQV0MK2v15dZ7ds8WSGu9+1waZc0QTRxsa8euSnEvN7XT6UzfYfzWIoXzgZuAeSKy0f26PNxChRNvLGvDMpNJSYgz6TsMkU19ed8KCFgWo1i2rNVXWO+9TBcDJy1vA0SxNT5rMcIedyTo+H5Y1rIS4ilISmC7UdYiAlX9GDDOg12oaXL7rKX2XErKZhMrItQkxo0aROR/gSuBY6o6uZv1c4ClwH73or+q6s9CJ2GA6WiGlpq+FRCwLGu73gWXq/u6mAOdOrdlra9zlTIIEtONZc0QXexyK1zjvIgE7crEtBQzDWqIWGqbO8hOTSC+j/JpYwansd9Mg0YTfwTm99HmH6pa5n5Fr6IGJ61F3kyDZo8CZzs0HQ2uTJFKfTnEp0BaXu/tRAaUFdIoazHC7pY2hiTGk5XQP2NqSXoye1rasbs0SJIZDL5T29zR6xSoh7F5aZTXttDuiPFkolGCqn4E1IZbjpDhrbUIBtz0Xr+pL4esEZYy1hfZI41lzRBd7G7uXySoh5K0ZOyq7G01U6GGyKOmub3XHGseigan41I4VNMSAqkMIeI8EdkkIm+LyKSeGonIXSKyVkTWHj9+PJTyeU+9W6Hw1mcNBozFqN/UuZU1b/AEY2j0GxuMshYDqCq7W9q8KjN1OiXpVoZoUyPUEIl4a1nrjAg1QQYDhfXAKFWdBvxf4PWeGkZFOpu6Q1ady4z8vtt2RjnGqLLmbSAGWOeqo8lK9xHlGGUtBjja4aDJ6fKqzNTpjEtNIl4wQQaGiMRS1vq+rosGW8qa8VsbGKhqg6o2uT8vBxJEpA8npgimrhwyh4Mtru+2CcmQPiw2LWv2Vmg+DlleJvzuzLUW/ecqLMqaiMwXkZ0iskdEfthLu0UioiIyI5TyDTQ8wQX9iQT1kGizMTY12QQZGCIOl0s50WL3aho0IzmBwRlJJjHuAEFEhrnzDiIi52Ddy2rCK5Uf1Jd7r4CAZTGqHxi+WP2i/rD17u00qMcKOQAU25Cn7hCROOBx4BKgAlgjIstUddtp7TKAe4jx2oeBYFeLpaxN8GEaFKx8a+sbjK+PIbKob7XjdGmvpaa6YqXvMJa1aEBElgBzgDwRqQB+CiQAqOr/AIuAb4iIA2gFblCNYsekunIoutD79tmFcHh98OSJVLxNiOthACXGDUeetXOAPaq6D0BEXgKuArad1u7nwMPA/aEVb+Cxs7mN7Pg4Bif69nWXpqWw9FgdTQ4n6fFemOkNhhBQ09x3EfeujB2cxrtfxGi6gyhDVW/sY/3vgd+HSJzg4uiAxkrvIkE9ZBXCtmWxl2utvh9Rs2DVBE3KPLldFBOOb7kA6HrmKtzLOhGRs4BCVX2zt46iIsonAtjV3MaEtGSfi7GXpJtKBobI40RL39ULulKUl05tcwd17u0Mhoig4TCg3luLwLIYuezQVBU0sSKSunIQm+Xf5y1ZhSdTo0Qx4VDWutMYOs3XImIDfgN8v6+OoiLKJ8yoKjub2xjv4xQonCw7tc34rRkiCE/1Aq+VtcEmItQQgfTXWgQDanqvX9RXWBGzcT1XLDmD7JHGsuYjFUDXq3IEcKTL/xnAZOBDETkAzAKWmSAD3zje4aDO4fTZXw2gMDmR9DibiQg1RBSdRdzTvfdZA0yQgSGy8Fh9vKle4KFTWYt+JaRf1Pcjx5qHbGNZ85U1QLGIjBGRROAGYJlnparWq2qeqo5W1dHAamCBqq4Ng6xRjye4wJdIUA8iwsQ0ExFqiCxqm616t95a1kbmpJIYZzOWNUNk4bH6ZBb03q4rHoUl1iJC68v7Z4EEq317PbTWBUemEBFyZU1VHcC3gXeB7cDLqvqFiPxMRBaEWp6BztZGS8Hy+J35Skl6Cjua24jmgCvDwKKmuYP0pHiSvAx6iY+zUTQ4jZ1VDUGWzGDoB3XlkD7Uyp/mLYlpkJobW9OgLpeVuqM/vn1wsn2UT4X6payJyF9E5Aq3n5nXqOpyVR2vqmNV9b/cy/5DVZd103aOsar5zqbGFoYnJTA4sR9z/N0wMS2ZOoeTqg57gCSLbXwdO4aTeFu9oCsThmWw66iZBg0lCxcu5K233gq3GJFL/aH+W4vAXfcyuhWQftFUZQVV9HcaNGtgTBn7e6P4A/DPwG4ReUhEJgZAJkMA2dzYyrSMVL/7KUmzyk5tN2WnAoUZO37ii7I2fmgGh+taaWwzDx2h4hvf+AYvvvgiwGRzrXdDXXn//NU8ZBXGlmWtvsJ670/yYDCWNQBVfU9VvwacDRwA/iYin4jIbSLinynH4DcNDid7W9uZlpHid1+eaVQTERoYzNjxn5qmDq9zrHmYMDQDwFjXQsjFF1/MCy+8AJbbywHMtX4Sl8tK3dFfaxGcjHKMFdeUun4Uu+9K2mCIT456xdbvKRgRyQVuBe4ENgCPYd2A/uZv3wb/2NxoVR0IhGVtUEI8+UkJJtdaADFjxz9qmzu8rl7gYcIwj7LWGAyRDD1QU1MDkIu51k+l+Tg4O3yzrGWPBEeb1Ucs0JnipJ+KrYi1TZRb1vyqYCAifwUmAs8DX1XVSveqP4uI8TMLM5vcwQVTA6CsgeW3tr3ZWNYCgRk7/qGq1Db337JWkJ1CWmIcO6uMshYqrr32Wnbs2AGWccBc613pnNrz0bIG7gCFIYGTKVKpr4DkbEjK6P+2AyAxrr+WtadVtVRVH/QMQBFJAlBVkxctzGxqbKEwOZFcH8tMnU5JWgq7m9txuGLE7B5czNjxg6Z2Bx1OV7991mw2oXhohrGshZA777yTbdu2AVSZa/00fLUWwcmghFhJ31FX3v8pUA/ZhVFvWfNXWftFN8s+9bNPQ4DY1NASEH81DxPSkulQ5WBbe8D6jGHM2PEDT0Lc/iprYPmtGWUtdPzkJz/pbrG51sFPy5pbcYlyXyyvqa/wLWoWLCtk83GwR+/MkE8mFxEZhlXPM8Vdx9NTQioTCMyc2wDEbrdTUVFBW1vw/b5cqvw82U6Wuti+fXtA+pzocvFctlC/by/b40zGCYDk5GRGjBhBQoJ3ftJm7JyKr2Oiw+HiqQX55CXWs317/4IFFo0VLh6ey9YvthFn861erqFnPGOipqaGw4cP09rayoYNGwBSReRsYvRa75b6CkhMt6b3+ktylvWK8uk9r6kvh9EX+LatJ4K0vgLyigMnUwjxdX7sK1iO0SOAR7ssbwR+5KdMA5aKigoyMjIYPXq0z0XVvaXR4cTR0k5RahIZXiYN7QunKjS2MiwpgaFJsR3EBZbfVE1NDRUVFYwZM8bbzczY6YKvY6Kh1Y7UNDNuSDqp/Zzmb2yzs7+6mdF5aaQnm+s4kHQdEx999BF//OMfqaio4Hvf+x5Y1/x/E6PXerd4yif5ej/IGhkblrXWOmhv8M0CCV2skAdjS1lT1WeBZ0Vkoar+JcAyDVja2tpCoqgBtDhdAKTYAmcBixMhwSa0uVwB6zOaERFyc3M5ftz7aCwzdk7F1zHh8ZuM98EylpxgPby0OVyk93trQ290HRO33HILt9xyC3/5y19YuHAhIrJLVeeGW8aIor7CdwUErOm9E/sDJ0+k4pku9tVnzTN9GsVWSF+nQb+uqn8CRovI905fr6qPdrOZAUKiqAG0ulwk2sSnm1lvJNuEdhNg0El/v08zds7ElzHhcD8wxPnwMBJvE+JtNtrszn5va+gbz/f5pz/9ia9//escOHCARx99FGBo12s+Fq/1M6ivgOFlvm+fXQj7P7JyrYXo3hIWOgMxfFTWMvJB4qI6yMDXadA097t5MI1QWpwuUoPgV5Zks9Fkd6CqIVM8Bxhm7AQAp0uxieDLs4iIkJRgo81uLMTBpLm5GYCmpk6fQhvgQ96FAYq9FVqq/bOsZRVCRyO0noDUnMDJFmnU+amsxcVDZkHsWdZU9Qn3+38GVhxDIHC4FLtLSUkIvLKWbLOhCh2qJBllrd+YsRMYHE4l3iY+PzAkJ8RR19xhHjqCyL/8y78A8NOf/hSAxYsXV5rrvgv1h613XxUQOJlrrb58YCtr9YcgLsmqRuArUZ6+w99C7g+LSKaIJIjI+yJSLSJfD5RwBt9odU8R9WZZe+211xART7JKXC4X99xzD5MnT2bKlCnMnDmT/fvP9IVIdpsyxhcVMWXKFMrKyigrK+OTTz7hww8/5Morrzyl/a233sqrr74KwJw5c1i71sqBeeDAAYqLi3n33XdpaWnha1/7GlOmTGHy5MlccMEFnU/j77zzDhMmTGDcuHE89NBDnf3+/ve/Z9y4cYgI1dXVnctVlXvuuYdx48YxdepU1q9f37lu/vz5ZGdnnyFjT3298MILTJ06lalTpzJ79mw2bdrU4/nsL2bs+IfDpcTF+a5kJSfYcKrS4XRRVVXFDTfcwNixYyktLWXu3LmkpqZSVlZGTk4OY8aMoaysjIsvvrjbvg4cOEBKSgplZWWUlpZy8803Y7efWnv03nvvpaCgANdp/p5vv/02M2bMoKSkhIkTJ3L//fcDsHPnTubMmUNZWRklJSXcddddgBU9e8sttzBlyhRKSkp48MEHASgvL2fu3LmUlJQwadIkHnvssc591NbWcskll1BcXMwll1zCiRMnANixYwfnnXceSUlJ/PrXvz5Frp7GnYfvfOc7pKd7Zxz+wQ9+QENDA4B4e62LyP+KyDER2drDehGR34nIHhHZ7I4yjS78ybHmIVbSd9S5AzH88cGO9sS4qurzC9jofr8GeBbIATb506evr+nTp2uks23btpDs52hbh26sb1a709Vjm+uuu04vuOAC/elPf6qqqi+++KIuXLhQnU6nqqqWl5drbW3tGdvZnS7dWN+shSNH6fHjx09Zt3LlSr3iiitOWXbLLbfoK6+8oqqqF154oa5Zs0bLy8t1/PjxunTpUlVV/eUvf6n33Xdf5zY7duzQtrY2dTgcWlRUpHv37tX29nadOnWqfvHFF6qqun79et2/f7+OGnWqHG+99ZbOnz9fXS6Xfvrpp3rOOed0rnvvvfd02bJlZ8jYU1+rVq3qPAfLly8/pa+udPe9Ams1zGNnII+JXVUNuu94k8/7bW6366byE3qiqU1nzZqlf/jDHzrXbdiwQT/66CNVPfX67Yn9+/frpEmTVFXV4XDo3Llz9U9/+lPneqfTqYWFhXruuefqypUrO5dv2bJFi4qKdPv27aqqarfb9fHHH1dV1UsvvVRff/31zrabN29WVdUXXnhBr7/+eusYmpt11KhRun//fj1y5IiuW7dOVVUbGhq0uLi4c6w88MAD+uCDD6qq6oMPPqg/+MEPVFX16NGj+vnnn+uPfvQjfeSRRzr31du4U1Vds2aNfv3rX9e0tLQez0nX73XatGmqqgrs8fZaB76MVY5qaw/rLwfexkp9Mwv4rLf+NBLHxLrnVH+aqVq73/c+mmusPj55PGBiRSRPzlN9doF/fbz/c9XF2aqOjsDIFAD6uk90ffmb2t4T9345sERVa82Ugnf8++4Ktga4KPrk9BR+XjyCVpeLhF6CC5qamli1ahUrV65kwYIFLF68mMrKSvLz87G5n1xGjOj+aS/e3a/iW5BBVVUVN998M7/4xS9YsGABAJWVlYwaNaqzzYQJEwD49NNPGTduHEVFRQDccMMNLF26lNLSUs4666xu+1+6dCk333wzIsKsWbOoq6vrPLaLLrqIDz/88Ixteupr9uzZnZ9nzZpFRUWFT8fcA2bsnMZ/vvEF2440eNW2pcNJnE1Iiu/9Sbt0eCY//eqkM5Ynx8chCO+9v5KEhATuvvvuznVlZb47fMfFxXHOOedw+PDhzmUrV65k8uTJXH/99SxZsoQ5c+YA8PDDD/PjH/+YiRMnAhAfH883v/lNwBoTXcfglClTAMvfrrm5GYfDQWtrK4mJiWRmZpKTk0N+fj4AGRkZlJSUcPjwYUpLS1m6dGnndX/LLbcwZ84cfvWrXzFkyBCGDBnCW2+9dcoxfP755z2OO6fTyQMPPMCLL77Ia6+95tU56WJlzMLLa11VPxKR0b00uQp4zn3DWy0i2SKSrydLWUU+9RWAQMZw3/tIGQQJaQPfslZfDsWX+tdHViGoCxqOwKBRfbePMPx1anpDRHYAM4D3RWQwYCp9h5lWp6vXlB2vv/468+fPZ/z48eTk5LB+/Xr+6Z/+iTfeeIOysjK+//3ve5JYdkuyTVBg7ty5lJWVce6553ot280338y3v/1trrvuus5lt99+O7/61a8477zz+MlPfsLu3bsBOHz4MIWFJ/05RowYccpNsDt82cYbnnnmGS677DK/++mCGTt+oKhfwW82mxVksGXrFqZPnx4wudra2vjss8+YP39+57IlS5Zw4403cs011/Dmm292Ki9bt27tcd/33Xcf8+bN47LLLuM3v/kNdXV1ACxatIi0tDTy8/MZOXIk999/Pzk5p/oqHThwgA0bNnSOy6NHj3Yqcvn5+Rw7dqzXY+htDP3+979nwYIFnf15w1e/+lWPQppG4K71AqDrnFaFe9kZiMhdIrJWRNb2J81O0KmvgIxhEN//KhydiFh+a1Hsi9Un9jZoOupbsfuueKaMo/Rc+WVZU9UfisivgAZVdYpIM9YTj6EPfl7sh59CLzhVaXcp2b0EFyxZsoTvfve7gPXUvGTJEh555BF27tzJBx98wAcffMBFF13EK6+8wkUXXXTG9sk2Gwp88MEHDB580uGzp6flrssvvvhinn/+eW699VZSU60k5mVlZezbt48VK1bw3nvvMXPmTD799FPPdEePfXWHL9v0xcqVK3nmmWf4+OOP/eqnK2bsnEl3FrDucLqUL47Uk5+VzOCMZJ/3l5IQh90ZmDQ0e/fupaysjN27d7No0SKmTp0KQEdHB8uXL+c3v/kNGRkZnHvuuaxYsYIrrrii1/5uu+02vvKVr/DOO++wdOlSnnjiCTZt2sTatWuJi4vjyJEjnDhxgi996UtcfPHFnVawpqYmFi5cyG9/+1syMzN9OpaextCRI0d45ZVXurVO98ZDDz3Ev/7rv5KTk7NNVe0Buta7G9Tdfpmq+iTwJMCMGTMiJ++QJyGuv2QXDmzLWoMnEMPPc5XttqZFqd9aICp8l2DljOra13MB6NfgA22dyXC7V1Bqamr44IMP2Lp1KyKC0+lERHj44YdJSkrisssu47LLLmPo0KG8/vrr3SprSW7Lmv20H/Xc3NxO52UPtbW15OXldf7/gx/8gD/96U9cd911LF26lPh467JJT0/n2muv5dprr8Vms7F8+XJmz55NefnJgVVRUcHw4b1PGYwYMaLf2/TG5s2bufPOO3n77bfJzc31uZ8eMGPHB/zJsdaV5IQ4xhRP4LnH3/RbprFjx7Jx40YqKyuZM2cOy5YtY8GCBbzzzjvU19d3TmO2tLSQmprKFVdcwaRJk1i3bh3Tpk3rts/hw4dz++23c/vttzN58mS2bt3Kiy++yPz580lISGDIkCGcf/75rF27lqKiIux2OwsXLuRrX/sa1157bWc/Q4cO7XQFqKysZMiQIb0eS09jaMOGDezZs4dx48Z1Hsu4cePYs2dPn+fHXfIuR0Ru7rLYn2u9AugaRjkCOOJHf6GnvgLyp/rfT1YhlH/ufz+RikcR9SdqFqzUHV37izL8jQZ9Hvg1cAEw0/2aEQC5DD7S4r6RpfQQCfrqq69y8803c/DgQQ4cOEB5eTljxozho48+4sgR67fO5XKxefPmU/zIupLsvkl2nJYct7i4mCNHjnTWIj148CCbNm06wwfoN7/5DZmZmdxxxx2oKqtWrepU8jo6Oti2bRujRo1i5syZ7N69m/3799PR0cFLL73U6efWEwsWLOC5555DVVm9ejVZWVn9mrLpyqFDh7j22mt5/vnnGT9+vE999IQZO77jcPpevaArKQk2zjn/y7S2tfHUU091Ll+zZg1///vffeozPz+fhx56qDNKc8mSJTz99NMcOHCAAwcOsH//flasWEFLSwsPPPAAv/zlL9m1axdgjTt38ljeeeedzunSqqoqampqKCgoYOTIkXzwwQeoKs3NzaxevZqJEyeiqtxxxx2UlJR4Sjt1smDBAp599lkAnn32Wa66qnejVk/j7oorrqCqqqrzWFJTU71S1G666SZPlGs6gbvWlwE3u6NCZwH1UeWvpupfYfKuZI+Etjpo887fM+rwTFv6Wr3AQ0IypA+10oBEI95GInT3ArYD4k8fgXpFVJRPD4QiGvRgS5tubWhRl6v7SNALL7xQ33777VOWPfbYYzp69Gg9++yzddKkSTpp0iS97bbbtLW1tds+OpwuzR85UrcfPnLGuo8//ljPPfdcnTZtms6YMUNXrFhxyr7XrFmjqqrt7e16ySWX6P3336/PPvusTpkyRSdPnqylpaX6wAMPdMr/1ltvaXFxsRYVFekvfvGLU2QuKCjQuLg4zc/P1zvuuENVVV0ul37zm9/UoqIinTx5cuf+VFUvuOACzcvL0+TkZC0oKNB33nmn177uuOMOzc7O1mnTpum0adO0p2vMx2jQoI+dgTom6ls6dFP5CW1ut/u1b7vDqZvKT+imnXv1uuuu06KiIi0tLdXLL79cd2EyQzMAACAASURBVO3apar9jwZVta7BqVOn6ocffqiDBg3S+vr6U9pfc801+tJLL6mq6htvvKFnn322Tpw4UUtKSvT+++9XVdX77rtPx48fr1OnTtWpU6fq888/r6qqjY2NumjRIi0tLdWSkhJ9+OGHVVX1H//4hwI6ZcqUzuv1rbfeUlXV6upqnTdvno4bN07nzZunNTU1qqpaWVmpBQUFmpGRoVlZWVpQUNApa0/jriveRoNOnDhRXS5XvyLfgCVAJWDHsqLdAdwN3O1eL8DjwF5gCzDDm34jZkw0HrOiOFc/4X9fW161+qra6n9fkcj7vwhcFOeT81T/+FX/+wkQ/RoT3jbsdmN4Bcj3p49AvSJmEPZCKJS1HU0ture5eyUrkGxpaNZDLe1B30804KOyFvSxM1DHRE1Tm24qP6Htdqff+99+pF4PVPueAsTQPV2/10WLFumRI0f6dWMK1itixkTFOkvB2v6W/32Vr7H62vF2322jkb/erfrfJYHp6+VbVB8rC0xfAaA/Y8Jfn7U8YJuIfA60d7HW9T5XZQgKLlXaXEpmYlzQ95Vss5mC7v5hxo6PBGoaFCA1KZ7mdlM+LZhUV1dTWloKUCwiyzzLY/pa70yI220Aa//Iiu4oxz6pLw/MdDFY/ex4C1wu/xLshgF/lbXFgRDCEBjaXC5Qek3b0V/OPfdc2tvbT1n2/PPPM6h4AnWmRqg/LO7vBiLyv8CVwDFVnRxwiaIEh6cuaACUtbTEOOpaOuhwukiK7/0hZ8uWLdx0002nLEtKSuKzzz7zW46BzOLFiwGYM2dOJfDfYRUmUjhxwHofNNr/vtKHQHwy1B30v69IpO4QFJ4TmL6yR4KzA5qPWWlTogh/U3f8XURGAcWq+p6IpALBN+tEMcFUblqdvQcX+EJPN6LjHXacCg5VEmJYWbMs2T5t58vY+SPwewZYxGh/x4TDpcT7UWqqK6lJ1k9gS7uzT2VtypQpbNy4MSD7HcicPiYuvPBCDh48CJaP5t/NfQI4cRCSsyE5y/++RKy0FlGakqJXXE4rdUcgUpzASQtdXXnUKWv+RoP+H+BV4An3ogLgdX+FGqgkJydTU1Pj8w2+L1pdik0gMQTKkycitM0VOWmLQo2qUlNTQ3Jy/3N9+TJ2VPUjoLbfO4tgfBkTDqeL+ABZj5PjbcTZhOYOR0D6i3W6GxNPPfUUixYtAvCEl5v7RN3BwFjVPGQN0FxrjVXgcgRuGrQzMW70nSt/p0G/BZwDfAagqrtFpPckPjHMiBEjqKioIFhZtI+227EJ7EhM6LuxnzhVOdpupyM+jvQ+LBIDmeTk5B5Lc/VBUMaOiNwF3AUwcqSfGb9DgC9j4mhDG/E2G/YaPzK/d+FEUzvHnEpjlu8Jdg0nOX1MPP7443z++eckJSW5wNwnAGsadKh3SaC9Insk7FweuP4ihc60HQH6LetqWYsy/FXW2lW1wzOF4U7uGbumlj5ISEhgzJgxQenb7lLm/2MztxXksXhcAJxW+0BVWfjxVq4Zms1D44NTjWGAE5Sxo5Garb0HfBkT1y9+l2vOKuA/ryoJiAzPf3qAf1/6Be9970LGDUkPSJ+GkyQlJZGYeFKxjvn7hMtlWcEm9l7Fol9kF0LzcbC3QkJK4PoNN7X7rfdAWSGTM62p5yi0Qvo7l/B3EfkRkCIil2ClI3jDf7EM/WV3SxvtLmVqRmpI9icijE9NZlezKWfpI2bs+EBrh5OGNgdDMgNnBbuoZCgA720/GrA+DSe58MIL+eUvfwkg5loHGistJ3dP+aNAEOWllHrkxH5AAmdZg6itpeqvsvZD4DhWUsJ/AZYDP+lrIxGZLyI7RWSPiPywm/XfE5FtIrJZRN53O2IbemFzYwsAU9JD91RVnJZklDXf8WnsxDrHGq3rbWgAlbXh2SlMGp7J8i3RkwA/mnjooYc8NYRbMdf6yajNQQG8rWVFry9Wr9Tut4IL4pMC12fWyKhUav1S1lTVheUo+k1VXaSqT2kfnsIiEoeVefoyoBS4UURKT2u2ASsj9VQsJ+yH/ZEzFtjS2EpqnI2i1ABe1H0wPjWZaruDGuOc3W98HDtLgE+BCSJSISJ3hELWSOJYo5VGZkhGYK/zRdNHsLminq2H6wParwFsNhtXX301wCFvr/UBzQmPshZAlxiP43wUTu/1yon9gQ3EAOtc1ZdbJb+iCJ+UNXc9tsUiUg3sAHaKyHER+Q8vNj8H2KOq+1S1A3gJOKVYnaquVNUW97+rsYr0GnphS1Mrk9NTiAthGo3xaZZ1Y3eLsa55iz9jR1VvVNV8VU1Q1RGq+kzwJY4sjjYE3rIGcO1ZI0hJiOPxlX3XujR4h6qyePFi8vLymDhxIsDkftwnBi4nDgASuHQUABn5YIuPSotRr9Tuh5wA+3lnFUJHE7SeCGy/QcZXy9p3gfOBmaqaq6o5wLnA+SJyXx/bFgBdr6gK97KeuAN420c5YwKnKlubWpmaEVrHUo+yttNMhfYHf8ZOzHO0wbKsDc0MrGUtKzWBb8wZy9tbq1i68XBA+45Vfvvb37Jq1SrWrFlDTU0NwEbMtW5Ng2YWBHZqzxZn9TmQLGvtjdBSHVgLJHRJ3xFdiq2vytrNwI2qut+zQFX3AV93r+uN7kw/3dojReTrwAzgkR7W3yUia0VkbbDSYUQD+1raaXG6mJIemuACDwVJCWTFx/FFU2tI9xvl+DN2Yp5jDW0kxtvISgl8epq7vlzEzNGDuPeljdyzZAOHalr63sjQI8899xxLliw5JdrXXOtYlrVA+qt5iFLH+R7xRIIGw7IGUWeF9FVZS1DV6tMXqupxoK9f0Qqga4a7EcCR0xuJyMXAj4EFqtp++nr3/p5U1RmqOsPtwBqTbHErS6G2rIkIU9JT2NRobmr9wJ+xE/McbWhjSEZSUKqAJCfE8fwd5/KdeeNYsa2KS3/7dz7dWxPw/cQKdrudvLy8M5bH/LVeszfwCghYylqUKSC9csKjrBUFtl9PZGmUWSF9VdY6fFwHsAaroO8YEUkEbgCWdW0gImdhZXZfoKrHfJQxZtjc2EKyTShODX1Sz6kZqWxvaqPDFHX3Fn/GTsxT1dAWcH+1riQnxPH9Syew8v45FA5K5ZsvrKO6qdtnRUMfdM2t1g2xea231Vt1KXOLA9939kgrLYhjgJzazhxrAVZsU3MhKRNq9wW23yDjq7I2TUQaunk1AlN621BVHcC3gXeB7cDLqvqFiPxMRBa4mz0CpAOviMhGEVnWQ3cGrEjQkrQU4gNQ2Lq/TMtMoUOVHcZvzVt8HjsGOFzXSkF28C3I+Vkp/L+vnU1zu5OH39kR9P0NRDZt2kRmZmbnCzgr5q/1GncAS14QlLWsQkChoSLwfYeDE/stxSo5M7D9ikDuOKjZHdh+g4xPFQxU1a/6Qqq6HCvXTtdl/9Hl88X+9B9LqCpbmlq4esigsOx/mjsJ7+bG1pAl5I1m/B07sYzTpVTWtXHl1NBM9xcPzeBrs0by3KcH+caccYzJSwvJfgcKTqfzlP9FZIOqzgiTOJFBtVtZyx0X+L4903snDgR+6jAc1O4LvFXNQ14xHPg4OH0HicBUQzaEjUNtHTQ4XGFTlEYlJ5IVH9eZlNdgCBbHGttwuDQkljUP35gzlsQ4G797P7qewg0RSs1ukLjgKCF546336gFyrR7fdfKYAk1uMTQcho7m4PQfBIyyFuVsaHBXLghxcIEHE2RgCBWHT1iBNAWDQnetD8lI5uuzRrJ042ETHWrwn+rdViRofK/+fL6RPsSqe3l8Z+D7DjVt9dBUBYODpKx5pqFroievolHWopwNDVZwQWla+Ir3miADQyg4XGcpayNCaFkDuPNLRcTbbDzx0d6Q7jfW8aIs4a3uJLsb3a87wyFnv6jZG5wpULB8sfImDAxl7fgu6z1vQnD69yhrUWSFNMpalLO+oYWpGakkhCG4wMPUDBNkYAg+FWGwrIFVLWHh9BG8sraCYw3mGg8FXpYlBPizqpa5X0+HVMj+4nJZlpxgRIJ6GDwBqgeAsuY5hmBNg+aMBcQoa4bQ0OFysaWphbMyw+vY3zXIwGAIFhUnWhmUmkBqok9xUX5x94VFOFwunvl4f9+NDYGgz7KEUUfDYXC0Qu7Y4O1j8ARoPg4ttcHbRyio3gVxiYGvC+ohIdkKyIiiiFCjrEUx25raaHMpZ4dZWRudkkhmvM0EGRiCyuG6VkYMClMgTW4aV04dzp9WH6S+xR4WGWIMb8sSLhSRzSLyqogUdrM+cirdHNtuvQ/pzkAYIDzThtE+FXp8l2X9igvig1ne+JPTrVGAUdaimPUNViTL9MzwphQQEaamp5ogA0NQKa9toTAnfL6Z35gzluYOJ89+eiBsMsQQ3pQlfAMYrapTgfeAZ7vrKGIq3Rzdar0PDaKy5nHIj/ap0OqdwQsu8DCkxNqPMzoevoyyFsWsb2hhSGI8BUnhr9xiggwMwcTudHGotoWivPSwyVCSn8m8iUP4/1btp6XDETY5YoQ+yxKqak2XUoRPAdNDJJtvHP0CskZaEZvBImskxKdEt2WtvcmqXhBMCyTAsCng7LCmXKMAo6xFMZ/XNzMjMy0odRL7iwkyMAST8toWnC4Ne2Lab80dy4kWO0s+H0A1GCMTb8oS5nf5dwFWRZzI5egXMHRScPdhs1mWu6otwd1PMDn6BaAwbGpw9zPMXUSjamtw9xMgjLIWpZS3dXCorYPZg8JnaeiKCTIwBJP91daU/5jB4VXWpo/K4ZwxOTz10T46HMaKHCy8LEt4j4h8ISKbgHuAW8MjrRc42i0LTrCVNYD8aVC5GfT0WeMooWqz9Z4fZGUttxjikuBodCi2RlmLUj450QTA+dmRoayZIANDMPEoa0URUPLpG3PGUtXQxttbK8MtyoBGVZer6nhVHauq/+Ve9h+qusz9+d9UdZKqTlPVuaoauUVcj+8EdYZOWWuvt8pORSNVmyElBzK7iycJIHHxMGSisawZgssndU3kJMQxIS053KIAVpDBtIxU1tZHT/kOQ/Swr7qZQakJZKcGIfN7P7mweDCFOSm8ZKZCDd7isRYNnRz8feVPs94rNwZ/X8GgcrM1RRkK956hU04GfkQ4RlmLQlSVVXWNnJedji0C/NU8nJ+dzrbmNqqN87UhwOw/3hx2fzUPNptw/YxCPt1Xw4Fq83Bi8IKKtZCUFbzqBV0ZUgq2eKjcFPx9BRqnHY5tC/4UqIf8aVZeurrIf/AyyloUsqulnYo2O18elBFuUU7hS255VtU1hlkSw0Bj97FGxg6OjCl/gOtmFBJnE/68NvJ/5A0RQMVaKDjbCgAINvFJVlqKI1FoWTv6hRWhmV8Wmv0VzrTeKz4Pzf78wChrUciK6noALs3LDLMkpzItI5X0OBur3P50BkMgONbYRnVTByX5kXO9D81MZu6EIbyytgK70wQaGHqhoxmOfQEjZoRunwXT4fA6cDlDt89AUP6Z9V54bmj2N3Syleqk3ChrhiCworqBqRkp5CeF33+nK/E24fxB6bxX04ArWiORDBHHjkrLUjsxP7IsyTfMLKS6qZ33tx8LtyiGSObIRlAXFIRQWRt1PrQ3RI0/VieHVkPmCMjuthhF4IlLsBRbo6wZAs3xDjtrG5q5NDeIiRX94KohgzjSbudzE2hgCBDbKxsAKI0gyxrAnAmDGZqZxJ/XHAq3KIZI5tAn1vuImaHb56jZ1vvBT0K3T39RtZS1kSGyqnkonGkFgHREdiYDo6xFGUuP1aHAFYMjU1n7Sm4mKTbh1aoT4RbFMEDYXtlAflZyRESCdiU+zsb1Mwr5cNfxToXSYDiDfX+3og7TckO3z6wRVqHyaFLW6g5B4xEonBXa/RbOApcDKtaEdr/9xChrUcZfj55gUnoyJenhq5HYG2nxcVw9dBCvHq3leEd01FwzRDbbKxuZOCyypkA93H7BGLJTEvjJ61uN75rhTDpaLD+sogtDv++Rsy1lLVpKAO5933oP9bkafb4VPbv3g9Dut58YZS2K2NfSzvqGFhYOzQm3KL3yrZFDaHcpT1dUh1sUQ5TT2GZn97FGphVmh1uUbslOTWTxgkmsO3iCf/3LZqOwGU7l0KdWdGPRnNDve+xcaKmGyg2h37cv7H7Pqm2aF+QC7qeTlAEjz4M974d2v/3EKGtRxCtVtQhwzdDIvHF5GJeazJWDs3m64rixrhn8YlN5PS6F6aMGhVuUHrmqrID7Lh7PX9cf5oYnV1NeG9m+L4YQsnuFVdJo5Hmh33fxpSA22PlO6PfdXxwdsP/vUHxxaJLhns64i6yyU41Vod+3lxhlLUpod7l47kgNl+RmRlwUaHf8sGgYbS4Xjx44Gm5RDFHMuoMnEIGyCLWsebj34mJ+d+NZ7Kpq5LLH/sFf1lWgJiI6tnG5YNtSKL4EksKQIzA1x1ISd74d+n33l/0fQUeTpWCGg+KvWO/b3wjP/r3AKGtRwutH66ixO7hzxOBwi+IVY1OT+Vp+Ls8fqWZfS3u4xTFEKWsP1jJhaAYZyQnhFqVPFkwbzvJ7v0Rpfibff2UT335xA60dUZbnyhA4KtZAYyWUXhU+GSZeYVmMju8KnwzesOVlSM6CsfPCs/+hpVblhy2vhmf/XmCUtSig3eXivw9UMSk9mS8Nipws7n1x/+hhJIiNh/abgteG/tPa4eSz/bXMHpsXblG8pjAnlSV3zeIH8yewfGsl33xhnfFji1U2vwTxyTB+fvhkmHIdSBxseD58MvRFe5Nl0Zp0jVV9IVxMWQTlq+HEwfDJ0AtGWYsCHj90jENtHfz72OFIBNUC7YshSQncXTiYZcfq2NBg/HgM/ePTfdV0OFzMnRgd1mQPcTbhm3PG8V9XT2HlzuP8+LUtZko01mhrgE1/hskLITmM+QHTh1jK4qYlll9YJLLlFbC3wNQbwivHlH+yfPzWPB1eOXrAKGsRzpvH6vj1/iquGZLNnJzISgrqDd8aOYTchHh+vveIuWEZ+sXKHcdJSYjjnDGRHf3cE/987kjuuaiYl9dW8P8+3BtucQyhZN0fwd4MM+4ItyQw83arWPmmF8MtyZm4XPDp761aoCNDnF/tdLILofRq67tri7y8iUZZi1AcLuVX+yq564sDTM9M45EJISq/EWDS4+P43uihfFLXxAe1psC7wTs6HC7e2lLJvIlDSIqPC7c4PnPfxcVcc1YBj7y7k6UbD4dbHEMoaG+EVb+1/K9GTA+3NDD2IqvU1Ue/BkeE+Q9vWgI1e+D8e8MTBXo6s79jlen65P+GW5IzMMpaBHKwtZ1rNuzhNwePsmjYIF6aVkR6FN+wbhqey+iURH6x9whOY10zeMEHO45R29zBwukF4RbFL0SEhxZO4ZwxOTzwymZW76sJt0iGYPPef0JLLcz793BLYiECF/071JfD338VbmlO0lIL7y22ynCVXh1uaSwKzobJi2DVY1ATWdZwo6xFEO0uF48dOMqcz3ewo7mVP5SO4nclo0iLYkUNINFm44dj8tne3MaLleZmZegdVeUPH+5hxKAUvlwcXf5q3ZEUH8eTN01nRE4KNz3zGY+v3ENjm8k/OCDZthTWPAWzvmHd+COFojlQ9nX4+LeRkfzVaYe/3gVtdXDFf4MtglSRS38BCcnw8s1W8EOEEJYzJCLzRWSniOwRkR92sz5JRP7sXv+ZiIwOvZShw6nKK1W1fOmzHTy4v5J5uZl8eM5ErhkauYlA+8uC/7+9cw+So7ru8HfmtU9pH6xYCYReQQFHMkhCEIEFweFhRZVCdpnEcsVEDsaUTKgEl8s2Ni7KxuXCj6r8QZkqCsdUkZhgYh627CCEEohTcSxALBJIwiAJRFitVsJotXrv7M6c/NF3tK1hdqdXO9PdMzlf1Z1+3e7+3Tt9zr19+/bts9tZ3t7KN3bu5b8H7HHomVLOduqBJ3v2srV3kNs/ej6pZIyc+CRob87w5Beu4JoLu/nBhjdY8u2N/OUDv+Xe9a+zYXs/B46cjFpi7Ki5cmLbE/DE52HmZXDN3ZFKKcmKe73hKR67Cd7cEJ2O7DF44nOwayOs+C7MuDg6LaWYOgNufAgO7ICffBKOxaOBQcLu9C0iSeBN4DqgF3gJ+LSq7vDFuQ24SFXXishq4BOq+qnxjrt06VLdvHlzFZVXnv6hYX713iEe3vt7dh4f4sOtTXx93gw+elbtvUgQhIPDI3y8Zxdvnxjii3O6uWXmNKbWeKvhWIjIy6q6tMLHLGs7fmrRJp5/4wC3/aSHD5/bxqO3LiOZiEE/lgqz9d1DPP3aPja9fZAdfYMM5zwfPLerhavmd7F8/jT+YFoL3VMbac4ka+oN8PGYiE3UTDmhCn09Xh+n7U95g9Cu/hdvQNo4cqQfHrkR+rfBxavh8tuhe0E4/cWyx2DHOu9R7MAe+Nh34PK/rf55z5TtT3mtfw1T4E++Chd9CpoqOzj3RGwiVdEzB+MyYJeqvgUgIj8FVgH+AmcV8E03/zjwQxERPcOa5fr3DjGiUNhZUfxH0kJwK9UXwLNHRX37ez962v6jx/zg/npq+eDwCHtOZNl6+Di7T3idPRdNaebBBXP482ltJOrEMZeiM51i3ZLz+fIbvXz/7X7ue2c/i6Y0M6epgampJK2pBI2JBGkR0gkhAeSBvCp5l5nphNCQSJBJCBkRUhHmV1cmxbL2UMe9C2I7ZcnllWe397tr3ltXuH791yyltvuvcZ+94GyksE+pY4/G1dNsaziXp3fgBFt7D/HK/x7igu4p3P9XS+qyogZw8Xntp751enI4x/a+QXreOcT/7P49/7q5l4d/OzrOU0MqQWdLho7mDJ0tGdqa07Q3pWlrStOUTpJJJUgnE2RSXmhwy1HlXHdbI0tmVeSJQLjlxPBJ2LkB8jnQvJvmRqen1uW9FwiO7ofBvbD3ZTjaD+lmuPprsPyL0Y4VVo4p0+HmZ+HX34VND3gd/NtmwYyLoH0WtEzzKifJjAtpbziLgsUWZ636SkH/fPaY90WCoaPewMDv74K9PZAbgu6FsOaXMPfKkBJ9hiz4hPed0n/7Eqz/Cmz4utcK2HUBTD0Hmjq8x6WpJi+vCmWRCCCj047ZcM7iScuJorJ2LvCub7kX+OOx4qjqiIgMAmcBp30ZXERuBW4FmDVr1pgnXLvjHYbyE7ffaiDAzMYMF7Y08plzzuLqzil8qLUpalmh0Z5O8aOFc9hy+DhP7h9gy5Hj/HrgCEdGchytscFDr+xo5WeLzg/zlGVtJ4hNjOTzfOGRnipJPDOaM0nmn93KXSs/xE2Xz6YxXZ8trsU0ppNcMruTS2Z38vmr5jE0kuPV3kF6B46z//AQA8eyHDyWZeB4lvePZek7dILBE8MMnhhmJCY+zc+KBdN54KaKvAEZbjkxdMTroxSUhjav4jP3Kpiz3CvYoxxPbSJkmuG6e+CKv4MdP4c9v4H+V2H3895wIxVFoKXLq/RcegtcsAJmL49XH7Xx6F4ANz8Dfa94rYLvvuh9w/TIPq/iHoTFn4FV909aShSVtVI3fcVeJ0gcVPVB4EHwmrfHOuEzl/zh6IELlV8E8Z1IBLcspwQU1vlFFR5JiC+M7i+jy75z+c/XmkrQUCsXahVZNLWZRVObT1uXUyWbV0ZUGVYlp0pShCSQEEGBbF7J5vNkVRnKK/kI3y5tDr8/VVm7CGIT6USCZ+640h1QfDZRuGbdNS4lrnm//fivb/HifcAefMemaN9C3FQiwdSmVN087psMDakkl87p5NI54z9GU1VyeSWby5Md8cLQSJ7hXJ5shDc9rQ0VK1LCLSeaOmDtbyCR9Eb8TyTdRZwsWpf0KjvpOrjBbunyKlCX3jK6LnsMsschlx0NBR8r/tJtvGUg0wKZVq/FsR7Ku3MWn946lhvxKrbDJ2HkhPfChLrnZ8XTxso8Oo2istYL+AcNmwn0jRGnV0RSQBtw8ExP+P+p5aqWSYrQlLQCexyC2E5ZEgnhwuk10gpglERESCWFVDJBcyZqNVUh3HIimYLpC89o17oi0+IFY3ySKUi2ed8zDYkoqrwvAfNFZK6IZIDVwLqiOOuANW7+RuC5M+2vZhh1RBDbMYx6wMoJw/AResua61twO7ABSAIPqep2EbkH2Kyq64AfA/8sIrvw7pQi/miYYUTPWLYTsSzDqDhWThjG6UTxGBRVfRp4umjd3b75k8BfhK3LMOJOKdsxjHrEygnDGCX0cdaqhYi8B7xTNmLl6aLo7aOIiZseiJ+mMPTMVtVIh98vsom4/QeVwNJUGxTSFDebKEUc8980BSeOusbTFNgm6qayFhUisrnSg59OhrjpgfhpipueMKjHNFuaaoNaSlMctZqm4MRRV6U01cE7tYZhGIZhGPWLVdYMwzAMwzBijFXWJs+DUQsoIm56IH6a4qYnDOoxzZam2qCW0hRHraYpOHHUVRFN1mfNMAzDMAwjxljLmmEYhmEYRoyxyloAROQ8EXleRF4Xke0i8vcl4lwtIoMissWFu0sdq4Ka9ojIa+5cm0tsFxG5T0R2icirIrKkynou8KV9i4gcFpE7iuJUNY9E5CEROSAi23zrOkVko4jsdNOOMfZd4+LsFJE1peLUKiKyQkTecNfCnVHrmSyl/udaJ4iPqTVEpFFEXhSRrS5N34paUzET8A85n9+qyldDytmpiDSIyGNu+wsiMqcaOiao6bMi8p4vb24pdZwKaxrX/sMu+wJqmnzZp6oWygRgBrDEzU8B3gT+qCjO1cCvQtS0B+gaZ/tKYD3eV3aXAS+EqC0J9OONIRNaHgFXAUuAbb513wfudPN3At8rsV8n8Jabdrj5jqivuwr+F7uBeUAG2Fp87dZaKPU/13oI4mNqLTjf0+rm08ALwLKodRVpLOsf3LajVdZR1k6B24AH3Pxq4LEYaPos8MOQ/7Nx7T+Ksi+ApkmXfdayFgBV3aeqPW7+CPA6cG60qsqytBDXqwAAA/tJREFUCvgn9dgEtIvIjJDOfQ2wW1VDHaRYVf+LD37IeRXwsJt/GPh4iV0/BmxU1YOqOgBsBFZUTWi4XAbsUtW3VDUL/BQvT2qWMf7nmqZGfcy4ON9z1C2mXYhbJ+kg/iEMgtipX+vjwDUiIhFrCp0A9h962ReGT7LK2gRxTc+L8e4Si7ncNfmvF5EFVZaiwLMi8rKI3Fpi+7nAu77lXsJz/quBR8fYFmYeAXSr6j7wCkTg7BJxosyralPPaatLyviYmkJEkiKyBTiAd0MUtzQF8Q8AjSKyWUQ2iUg1KnRB7PRUHFUdAQaBs6qgZSKaAD7pHjc+LiLnVVFPUOLq8yZV9kXybdBaRURagSeAO1T1cNHmHrzHfkdFZCXwc2B+FeV8RFX7RORsYKOI/M7V7k/JLbFP1e9qRSQD3AB8rcTmsPMoKJHkVUjUc9rqjjI+puZQ1RywSETagadEZKGqhtrXUET+HZheYtNdEzjMLOdv5wHPichrqrq7MgqBYHYati0HOd8vgUdVdUhE1uK1/P1pFTUFIY4+b9Jln7WsBURE0nhO9BFVfbJ4u6oeLjT5q/cB4rSIdFVLj6r2uekB4Cm8Jms/vYD/Lmcm0FctPT7+DOhR1f3FG8LOI8f+QhO4mx4oESeqvAqDek5bXVHOx9QyqnoI+E8i6F6gqteq6sIS4RcE8w9+f/sWXjoWV1hmEDs9FUdEUkAb1X30VlaTqr6vqkNu8UfAJVXUE5TY+bxKlH1WWQuA6xfwY+B1Vf2HMeJML/QfEJHL8PL2/SrpaRGRKYV54Hqg+G51HfDX7s2YZcBgobm/ynyaMR6BhplHPtYBhbc71wC/KBFnA3C9iHS4t8Gud+vqgZeA+SIy17V6rsbLEyNGBPExtYaITHMtaohIE3At8LtoVX2Asv7B+YUGN98FfATYUWEdQezUr/VG4Dl1vderRFlNRX3BbsDraxk1UZV9Y1KRsq8ab0bUWwCW4zWjvgpscWElsBZY6+LcDmzHe2NmE3BFFfXMc+fZ6s55l1vv1yPA/Xhv87wGLA0hn5rdBdjmWxdaHuFVEvcBw3h3V5/D69PxH8BON+10cZcC/+jb92Zglwt/E/U1V+F8WYn3duHuwrVSy6HU/xy1pgqkqaSPiVrXJNN0EfCKS9M24O6oNZXQWNY/AFc4H7rVTatyvZWyU+Ae4AY33wj8zPmoF4F5IeRPOU33+nz688CFIWgq5eejLvvKaZp02WdfMDAMwzAMw4gx9hjUMAzDMAwjxlhlzTAMwzAMI8ZYZc0wDMMwDCPGWGXNMAzDMAwjxlhlzTAMwzAMI8ZYZc0wDMMwDCPGWGXNMAzDMAwjxlhlzTAMwzAMI8b8H+CIYk8adFHQAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Train.plot(kind='density', figsize=(10,10), subplots=True, layout=(4,3), sharex=False)\n", + "plt.show" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Checking for the skewness of the data. Since many machine learning algorithms assume normal distribution,this allows one to know what attributes need to be corrected of skewness to improve the accuracy of the model. Skewness can be observed with bar plots of .skew()." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Train.skew().plot(kind='bar', figsize=(10,6))" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "NT_EFC195\n", + "0 2769\n", + "1 269\n", + "dtype: int64" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# From above, attribute NT_EFC195 shows that its, skewed.\n", + "Train.groupby('NT_EFC195').size()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Separating the train data set into output and input components" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "A = Train.values\n", + "X = A[:, 0:11]\n", + "Y = A[:,11]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Spot checking classification algorithms since its a classification problem at hand.\n", + "### This is done to know which algorithm is best suited for the problem at hand. Two linear machine learning algorithms(Logistic regression and Linear discriminant analysis) and four non-linear machine learning algorithm were used(k-nearest neighbors, naive bayes, support vector machines and classific regression tress. " + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('LR', 0.8342865299822478)\n", + "('LDA', 0.8377162908048379)\n", + "('KNN', 0.8690586462107053)\n", + "('CART', 1.0)\n", + "('NB', 0.8407203694376205)\n", + "('SVM', 0.8187103751493263)\n" + ] + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "from pandas import read_csv\n", + "from matplotlib import pyplot\n", + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "from sklearn.neighbors import KNeighborsClassifier\n", + "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", + "from sklearn.naive_bayes import GaussianNB\n", + "from sklearn.svm import SVC\n", + "from sklearn.metrics import matthews_corrcoef\n", + "\n", + "#split the dataset \n", + "#A = Train.values\n", + "# Separating A into output and input components\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "# prepare models and add them to a list\n", + "models = []\n", + "models.append(('LR', LogisticRegression()))\n", + "models.append(('LDA', LinearDiscriminantAnalysis()))\n", + "models.append(('KNN', KNeighborsClassifier()))\n", + "models.append(('CART', DecisionTreeClassifier()))\n", + "models.append(('NB', GaussianNB()))\n", + "models.append(('SVM', SVC()))\n", + "#print(models)\n", + "\n", + "# evaluate each model in turn\n", + "results = []\n", + "names = []\n", + "scoring = 'accuracy'\n", + "\n", + "for name, model in models:\n", + " kfold = KFold(n_splits=20, random_state=7)\n", + " cv_results = cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\n", + " results.append(cv_results)\n", + " names.append(name)\n", + " model.fit(X, Y)\n", + "\n", + " Prediction = model.predict(X)\n", + " msg = (name, matthews_corrcoef(Y, Prediction))\n", + " print(msg)\n", + "\n", + "# boxplot algorithm comparison\n", + "fig = pyplot.figure()\n", + "fig.suptitle('Algorithm Comparison')\n", + "ax = fig.add_subplot(111)\n", + "pyplot.boxplot(results)\n", + "ax.set_xticklabels(names)\n", + "pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### From these results, it would suggest that both DecisionTreeClassifier, KNeighborsClassifier and GaussianNB are worthy of further study on this problem." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Data Preparation.\n", + "### This is important because this finds a way to best expose the structure of the problem to machine learning algorithim intended to be used. Since the data has attributes of varying scales, its important to use one of the methods for data preparation like rescaling, standardization, normalization or binarization for better prediction. Here, rescaling is used to have all the attribute on the same scale." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[0.457 0. 0.348 0.545 0.33 0.483 0. 0.005 0.508 0.415 0.182]\n", + " [0.435 0.116 0.322 0.489 0.276 0.458 1. 0.011 0.421 0.586 0.475]\n", + " [0.467 0.116 0.246 0.523 0.288 0.565 0. 0.011 0.442 0.273 0.666]\n", + " [0.457 0.089 0.275 0.399 0.403 0.647 0. 0.011 0.405 0.153 0.424]\n", + " [0.511 0.183 0.323 0.373 0.342 0.595 0. 0.011 0.5 0.196 0.536]]\n" + ] + } + ], + "source": [ + "from numpy import set_printoptions\n", + "from sklearn.preprocessing import MinMaxScaler\n", + "\n", + "A = Train.values\n", + "# Separating A into output and input components\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "scaler = MinMaxScaler(feature_range= (0,1))\n", + "rescaledX = scaler.fit_transform(X)\n", + "\n", + "# Summary of the transformed data\n", + "set_printoptions(precision = 3) # This sets the number of floating point output after rescaling the data\n", + "print(rescaledX[0:5, :]) # This is used as check to confirm that the data has been rescaled" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Standardization\n", + "### It is a useful technique to transform attributes with a Gaussian distribution and differing means and standard deviations to a standard Gaussian distribution with a mean of 0 and a standard deviation of 1" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[ 7.697e-01 -1.123e+00 -1.900e-01 1.376e-01 -6.067e-01 -7.206e-01\n", + " -3.117e-01 -1.331e+00 -2.257e-02 -3.610e-01 -9.251e-01]\n", + " [ 5.079e-01 -4.109e-01 -3.763e-01 -2.432e-01 -1.181e+00 -9.245e-01\n", + " 3.208e+00 -1.303e+00 -5.924e-01 9.021e-01 1.037e+00]\n", + " [ 9.006e-01 -4.109e-01 -9.163e-01 -8.651e-03 -1.054e+00 -4.632e-02\n", + " -3.117e-01 -1.304e+00 -4.590e-01 -1.409e+00 2.318e+00]\n", + " [ 7.697e-01 -5.741e-01 -7.115e-01 -8.701e-01 1.594e-01 6.274e-01\n", + " -3.117e-01 -1.302e+00 -7.015e-01 -2.300e+00 6.989e-01]\n", + " [ 1.424e+00 2.041e-03 -3.670e-01 -1.050e+00 -4.790e-01 2.003e-01\n", + " -3.117e-01 -1.302e+00 -7.713e-02 -1.977e+00 1.447e+00]]\n" + ] + } + ], + "source": [ + "from numpy import set_printoptions\n", + "from sklearn.preprocessing import StandardScaler\n", + "B= Train.values\n", + "#Separating the array into intput and output components\n", + "X = B[:, 0:11]\n", + "Y = B[:, 11]\n", + "scaler2 = StandardScaler()\n", + "standardizedX = scaler2.fit_transform(X)\n", + "# A portion of the transformed data\n", + "set_printoptions(precision = 3) # This sets the number of floating point output after rescaling the data\n", + "print(standardizedX[0:5,:]) # This is used as check to confirm that the data has been rescaled" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Feature selection\n", + "### Statistical tests can be used to select those features that have the strongest relationship with the output variable. Feature selection is done on non transformed data using select k best using he univariate statistic F was used since it can work best with data containg negative values as opposed to chi2 that doesnt take in negative values." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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featuresscorespvalue
7AS_MeanAmphiMoment2813.8681780.000000e+00
1FULL_AcidicMolPerc1697.2495654.220004e-295
2FULL_AURR9801071572.2806771.887905e-277
3FULL_DAYM7802011350.3007436.997934e-245
0FULL_Charge1214.9028383.404241e-224
5FULL_OOBM850104785.1247987.441087e-154
8AS_DAYM780201717.3174084.911002e-142
10CT_RACS820104234.2741975.329249e-51
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" + ], + "text/plain": [ + " features scores pvalue\n", + "7 AS_MeanAmphiMoment 2813.868178 0.000000e+00\n", + "1 FULL_AcidicMolPerc 1697.249565 4.220004e-295\n", + "2 FULL_AURR980107 1572.280677 1.887905e-277\n", + "3 FULL_DAYM780201 1350.300743 6.997934e-245\n", + "0 FULL_Charge 1214.902838 3.404241e-224\n", + "5 FULL_OOBM850104 785.124798 7.441087e-154\n", + "8 AS_DAYM780201 717.317408 4.911002e-142\n", + "10 CT_RACS820104 234.274197 5.329249e-51" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sklearn.feature_selection import SelectKBest, f_classif\n", + "from numpy import set_printoptions\n", + "\n", + "#Feature Extraction\n", + "bestfeat = SelectKBest(score_func=f_classif, k=8)\n", + "fit = bestfeat.fit(X,Y)\n", + "\n", + "set_printoptions(precision=3) # This sets the number of floating point output after rescaling the data\n", + "selected_features = fit.transform(X)\n", + "\n", + "scores = pd.DataFrame(fit.scores_)\n", + "pvalues = pd.DataFrame(fit.pvalues_)\n", + "columns = pd.DataFrame(Train.columns[0:11])\n", + "\n", + "selected_features = pd.concat([columns,scores, pvalues,], axis=1)\n", + "selected_features.columns = ['features', 'scores', 'pvalue']\n", + "selected_features.nlargest(8, \"scores\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### SelectKBest using the f statistic, gives scores to each attribute and takes the specified number of attributes with the highest scores. Attributes AS_MeanAmphiMoment, FULL_AcidicMolPerc, FULL_AURR980107, FULL_DAYM780201, FULL_Charge, FULL_OOBM850104, AS_DAYM780201 and CT_RACS820104 were the selected features." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Chi2 statistical test was used to since there were no negative values in the attributes after rescaling with the minmax scaler." + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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featuresscorespvalue
7AS_MeanAmphiMoment244.2277284.708742e-55
6NT_EFC195188.1970267.868482e-43
1FULL_AcidicMolPerc157.6175133.751602e-36
2FULL_AURR98010754.2314481.782118e-13
3FULL_DAYM78020137.3117801.006747e-09
8AS_DAYM78020126.1562243.148806e-07
5FULL_OOBM85010416.2314335.605627e-05
0FULL_Charge15.2452499.441397e-05
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" + ], + "text/plain": [ + " features scores pvalue\n", + "7 AS_MeanAmphiMoment 244.227728 4.708742e-55\n", + "6 NT_EFC195 188.197026 7.868482e-43\n", + "1 FULL_AcidicMolPerc 157.617513 3.751602e-36\n", + "2 FULL_AURR980107 54.231448 1.782118e-13\n", + "3 FULL_DAYM780201 37.311780 1.006747e-09\n", + "8 AS_DAYM780201 26.156224 3.148806e-07\n", + "5 FULL_OOBM850104 16.231433 5.605627e-05\n", + "0 FULL_Charge 15.245249 9.441397e-05" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sklearn.feature_selection import SelectKBest\n", + "from sklearn.feature_selection import chi2\n", + "\n", + "#Feature Extraction\n", + "test = SelectKBest(score_func=chi2, k=8)\n", + "fit = test.fit(rescaledX,Y)\n", + "\n", + "# Summary of scores \n", + "set_printoptions(precision=3) # This sets the number of floating point output after rescaling the data\n", + "#print(fit.scores_)\n", + "selected_features1 = fit.transform(rescaledX)\n", + "\n", + "scores = pd.DataFrame(fit.scores_)\n", + "pvalues = pd.DataFrame(fit.pvalues_)\n", + "columns = pd.DataFrame(Train.columns[0:11])\n", + "\n", + "selected_features1 = pd.concat([columns,scores, pvalues,], axis=1)\n", + "selected_features1.columns = ['features', 'scores', 'pvalue']\n", + "selected_features1.nlargest(8, \"scores\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Feature selection using the recursive feature selection method with LG" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'rescaledX2' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mmodel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mLogisticRegression\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mrfe\u001b[0m\u001b[0;34m=\u001b[0m \u001b[0mRFE\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0mfit\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrfe\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrescaledX2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 6\u001b[0m \u001b[0mselectedfeaturesRFE\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrescaledX2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msupport_\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'rescaledX2' is not defined" + ] + } + ], + "source": [ + "from sklearn.feature_selection import RFE\n", + "from sklearn.linear_model import LogisticRegression\n", + "model = LogisticRegression()\n", + "rfe= RFE(model,5)\n", + "fit = rfe.fit(rescaledX2, Y)\n", + "selectedfeaturesRFE = rescaledX2[:, fit.support_]\n", + "\n", + "print(\"Num_Feature:\", fit.n_features_)\n", + "print(\"Selected Features:\", fit.support_)\n", + "print(\"Feature Ranking:\", fit.ranking_)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Evaluating Machine learning Alogorithms\n", + "## K-fold Cross Validation\n", + "### Cross validation is an approach that you can use to estimate the performance of a machine learning algorithm with less variance than a single train-test set split. It works by splitting the dataset into k-parts (e.g. k = 5 or k = 10). Each split of the data is called a fold. The algorithm is trained on k1 folds with one held back and tested on the held back fold. This is repeated so that each fold of the dataset is given a chance to be the held back test set. The choice of k must allow the size of each test partition to be large enough to be a reasonable sample of the problem, whilst allowing enough repetitions of the train-test evaluation of the algorithm to provide a fair estimate of the algorithms performance on unseen data. For modest sized datasets in the thousands or tens of thousands of records, k values of 3, 5 and 10 are common. In the example below we use 10-fold cross validation." + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'selected_features_train' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mkfold\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mKFold\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn_splits\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnum_folds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrandom_state\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mseed\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mmodel11\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mLogisticRegression\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mmodel11\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mselected_features_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcross_val_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel11\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mselected_features\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcv\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkfold\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'selected_features_train' is not defined" + ] + } + ], + "source": [ + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "num_folds = 10\n", + "seed = 11\n", + "kfold = KFold(n_splits=num_folds, random_state=seed)\n", + "model11 = LogisticRegression()\n", + "model11.fit(selected_features_train, Y_train)\n", + "\n", + "results = cross_val_score(model11, selected_features, Y, cv=kfold)\n", + "Prediction = model11.predict(selected_features_train)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (results.mean()*100.0))\n", + "#Assigning the preditions of the model to variable AssignmentOutPut\n", + "AssignmentOutPut11 = model11.predict(Test.values) \n", + "#Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut11 = pd.DataFrame(AssignmentOutPut11)\n", + "\n", + "AssignmentOutPut11.columns = ['Class'] # Naming the output column\n", + "AssignmentOutPut11.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut11['Class'] = AssignmentOutPut11['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut11.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut11.groupby('Class').size()[1].sum())\n", + "\n", + "AssignmentOutPut11.to_csv('AssignmentOutPut1.csv') # Writing AssignmentOutPut1 to a csv file" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'selected_features_train' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mkfold\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mKFold\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn_splits\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnum_folds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrandom_state\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mseed\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mmodel22\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mGaussianNB\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mmodel22\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mselected_features_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcross_val_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel22\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mselected_features\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcv\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkfold\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'selected_features_train' is not defined" + ] + } + ], + "source": [ + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.naive_bayes import GaussianNB\n", + "\n", + "num_folds = 10\n", + "seed = 22\n", + "kfold = KFold(n_splits=num_folds, random_state=seed)\n", + "model22 = GaussianNB()\n", + "model22.fit(selected_features_train, Y_train)\n", + "\n", + "results = cross_val_score(model22, selected_features, Y, cv=kfold)\n", + "Prediction = model22.predict(selected_features_train)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (results.mean()*100.0))\n", + "\n", + "#Assigning the preditions of the model to variable AssignmentOutPut\n", + "AssignmentOutPut22 = model22.predict(Test.values) \n", + "#Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut22 = pd.DataFrame(AssignmentOutPut22)\n", + "\n", + "AssignmentOutPut22.columns = ['Class'] # Naming the output column\n", + "AssignmentOutPut22.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut22['Class'] = AssignmentOutPut22['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut22.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut22.groupby('Class').size()[1].sum())\n", + "\n", + "AssignmentOutPut22.to_csv('AssignmentOutPut22.csv') # Writing AssignmentOutPut1 to a csv file" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'selected_features_train' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mkfold\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mKFold\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn_splits\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnum_folds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrandom_state\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mseed\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mmodel33\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mKNeighborsClassifier\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mmodel33\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mselected_features_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcross_val_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel33\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mselected_features\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcv\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkfold\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'selected_features_train' is not defined" + ] + } + ], + "source": [ + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.neighbors import KNeighborsClassifier\n", + "\n", + "num_folds = 10\n", + "seed = 33\n", + "kfold = KFold(n_splits=num_folds, random_state=seed)\n", + "model33 = KNeighborsClassifier()\n", + "model33.fit(selected_features_train, Y_train)\n", + "\n", + "results = cross_val_score(model33, selected_features, Y, cv=kfold)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (results.mean()*100.0))\n", + "\n", + "#Assigning the preditions of the model to variable AssignmentOutPut\n", + "AssignmentOutPut33 = model33.predict(Test.values) \n", + "#Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut33 = pd.DataFrame(AssignmentOutPut33)\n", + "\n", + "AssignmentOutPut33.columns = ['Class'] # Naming the output column\n", + "AssignmentOutPut33.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut33['Class'] = AssignmentOutPut33['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut33.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut33.groupby('Class').size()[1].sum())\n", + "\n", + "AssignmentOutPut33.to_csv('AssignmentOutPut33.csv') # Writing AssignmentOutPut1 to a csv file" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'selected_features_train' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mkfold\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mKFold\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn_splits\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnum_folds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrandom_state\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mseed\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mmodel44\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mDecisionTreeClassifier\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mmodel44\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mselected_features_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcross_val_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel44\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mselected_features\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcv\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkfold\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'selected_features_train' is not defined" + ] + } + ], + "source": [ + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "\n", + "num_folds = 10\n", + "seed = 44\n", + "kfold = KFold(n_splits=num_folds, random_state=seed)\n", + "model44 = DecisionTreeClassifier()\n", + "model44.fit(selected_features_train, Y_train)\n", + "\n", + "results = cross_val_score(model44, selected_features, Y, cv=kfold)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (results.mean()*100.0))\n", + "\n", + "#Assigning the preditions of the model to variable AssignmentOutPut\n", + "AssignmentOutPut44 = model44.predict(Test.values) \n", + "#Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut44 = pd.DataFrame(AssignmentOutPut44)\n", + "\n", + "AssignmentOutPut44.columns = ['Class'] # Naming the output column\n", + "AssignmentOutPut44.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut44['Class'] = AssignmentOutPut44['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut44.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut44.groupby('Class').size()[1].sum())\n", + "\n", + "AssignmentOutPut44.to_csv('AssignmentOutPut44.csv') # Writing AssignmentOutPut1 to a csv file" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'selected_features_train' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mkfold\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mKFold\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn_splits\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnum_folds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrandom_state\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mseed\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mmodel55\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mSVC\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mmodel55\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mselected_features_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcross_val_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel55\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mselected_features\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcv\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkfold\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'selected_features_train' is not defined" + ] + } + ], + "source": [ + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.svm import SVC\n", + "\n", + "num_folds = 55\n", + "seed = 6\n", + "kfold = KFold(n_splits=num_folds, random_state=seed)\n", + "model55 = SVC()\n", + "model55.fit(selected_features_train, Y_train)\n", + "\n", + "results = cross_val_score(model55, selected_features, Y, cv=kfold)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (results.mean()*100.0))\n", + "\n", + "#Assigning the preditions of the model to variable AssignmentOutPut\n", + "AssignmentOutPut55 = model55.predict(Test.values) \n", + "#Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut55 = pd.DataFrame(AssignmentOutPut55)\n", + "\n", + "AssignmentOutPut55.columns = ['Class'] # Naming the output column\n", + "AssignmentOutPut55.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut55['Class'] = AssignmentOutPut55['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut55.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut55.groupby('Class').size()[1].sum())\n", + "\n", + "AssignmentOutPut55.to_csv('AssignmentOutPut55.csv') # Writing AssignmentOutPut1 to a csv file" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Evaluating Machine learning Alogorithms\n", + "## Split into Train and Test set" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Non rescaled data" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MCC: 0.8283116428616907\n", + "Accuracy: 91.92422731804587\n", + "387\n", + "371\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import matthews_corrcoef\n", + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "A = Train.values\n", + "# Separating A into output and input components\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "test_size = 0.33\n", + "seed = 1\n", + "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", + "my_model1 = LogisticRegression()\n", + "my_model1.fit(selected_features_train, Y_train)\n", + "result = my_model1.score(selected_features_test, Y_test)\n", + "\n", + "Prediction = my_model1.predict(selected_features_train)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (result*100.0))\n", + "\n", + "#Assigning the preditions of the model to variable AssignmentOutPut\n", + "AssignmentOutPut1 = my_model1.predict(Test.values) \n", + "#Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut1 = pd.DataFrame(AssignmentOutPut1)\n", + "\n", + "AssignmentOutPut1.columns = ['Class'] # Naming the output column\n", + "AssignmentOutPut1.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut1['Class'] = AssignmentOutPut1['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut1.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut1.groupby('Class').size()[1].sum())\n", + "\n", + "AssignmentOutPut1.to_csv('AssignmentOutPut1.csv') # Writing AssignmentOutPut1 to a csv file" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MCC: 0.8566012373350099\n", + "Accuracy: 90.62811565304088\n", + "397\n", + "361\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import matthews_corrcoef\n", + "from sklearn.neighbors import KNeighborsClassifier\n", + "\n", + "A = Train.values\n", + "# Separating A into output and input components\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "test_size = 0.33\n", + "seed = 2\n", + "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", + "my_model2 = KNeighborsClassifier()\n", + "my_model2.fit(selected_features_train, Y_train)\n", + "result = my_model2.score(selected_features_test, Y_test)\n", + "\n", + "Prediction = my_model2.predict(selected_features_train)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (result*100.0))\n", + "\n", + "#Assigning the preditions of the model to variable AssignmentOutPut\n", + "AssignmentOutPut2 = my_model2.predict(Test.values) \n", + "#Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut2 = pd.DataFrame(AssignmentOutPut2)\n", + "# Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut2.columns = ['Class'] # Naming the out\n", + "AssignmentOutPut2.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut2['Class'] = AssignmentOutPut2['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut2.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut2.groupby('Class').size()[1].sum())\n", + "\n", + "AssignmentOutPut2.to_csv('AssignmentOutPut2.csv') # Writing AssignmentOutPut1 to a csv file" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MCC: 1.0\n", + "Accuracy: 90.72781655034895\n", + "387\n", + "371\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import matthews_corrcoef\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "\n", + "A = Train.values\n", + "# Separating A into output and input components\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "test_size = 0.33\n", + "seed = 3\n", + "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", + "my_model3 = DecisionTreeClassifier()\n", + "my_model3.fit(selected_features_train, Y_train)\n", + "result = my_model3.score(selected_features_test, Y_test)\n", + "\n", + "Prediction = my_model3.predict(selected_features_train)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (result*100.0))\n", + "AssignmentOutPut3 = my_model3.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut\n", + "\n", + "AssignmentOutPut3 = pd.DataFrame(AssignmentOutPut3)\n", + "# Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut3.columns = ['Class'] # Naming the out\n", + "AssignmentOutPut3.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut3['Class'] = AssignmentOutPut3['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut3.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut3.groupby('Class').size()[1].sum())\n", + "\n", + "AssignmentOutPut1.to_csv('AssignmentOutPut3.csv') # Writing AssignmentOutPut1 to a csv file\n" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MCC: 0.8417648773342619\n", + "Accuracy: 91.92422731804587\n", + "369\n", + "389\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import matthews_corrcoef\n", + "from sklearn.naive_bayes import GaussianNB\n", + "\n", + "A = Train.values\n", + "# Separating A into output and input components\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "test_size = 0.33\n", + "seed = 4\n", + "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", + "my_model4 = GaussianNB()\n", + "my_model4.fit(selected_features_train, Y_train)\n", + "result = my_model4.score(selected_features_test, Y_test)\n", + "\n", + "Prediction = my_model4.predict(selected_features_train)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (result*100.0))\n", + "\n", + "AssignmentOutPut4 = my_model4.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut\n", + "\n", + "AssignmentOutPut4 = pd.DataFrame(AssignmentOutPut4)\n", + "# Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut4.columns = ['Class'] # Naming the out\n", + "AssignmentOutPut4.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut4['Class'] = AssignmentOutPut4['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "AssignmentOutPut4.to_csv('AssignmentOutPut4.csv') # Writing AssignmentOutPut1 to a csv file\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut4.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut4.groupby('Class').size()[1].sum())" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MCC: 0.8164151115601915\n", + "Accuracy: 91.12662013958126\n", + "405\n", + "353\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import matthews_corrcoef\n", + "from sklearn.svm import SVC\n", + "\n", + "A = Train.values\n", + "# Separating A into output and input components\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "test_size = 0.33\n", + "seed = 5\n", + "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", + "my_model5 = SVC()\n", + "my_model5.fit(selected_features_train, Y_train)\n", + "result = my_model5.score(selected_features_test, Y_test)\n", + "\n", + "Prediction = my_model5.predict(selected_features_train)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (result*100.0))\n", + "AssignmentOutPut5 = my_model5.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut\n", + "\n", + "AssignmentOutPut5 = pd.DataFrame(AssignmentOutPut5)\n", + "# Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut5.columns = ['Class'] # Naming the out\n", + "AssignmentOutPut5.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut5['Class'] = AssignmentOutPut5['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "AssignmentOutPut1.to_csv('AssignmentOutPut5.csv') # Writing AssignmentOutPut1 to a csv file\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut5.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut5.groupby('Class').size()[1].sum())" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MCC: 0.8376165100283083\n", + "Accuracy: 91.72482552342971\n", + "403\n", + "355\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", + "from sklearn.metrics import matthews_corrcoef\n", + "\n", + "A = Train.values\n", + "# Separating A into output and input components\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "test_size = 0.33\n", + "seed = 6\n", + "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", + "my_model6 = LinearDiscriminantAnalysis()\n", + "my_model6.fit(selected_features_train, Y_train)\n", + "result = my_model6.score(selected_features_test, Y_test)\n", + "\n", + "Prediction = my_model6.predict(selected_features_train)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (result*100.0))\n", + "AssignmentOutPut6 = my_model6.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut\n", + "\n", + "AssignmentOutPut6 = pd.DataFrame(AssignmentOutPut6)\n", + "# Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut6.columns = ['Class'] # Naming the out\n", + "AssignmentOutPut6.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut6['Class'] = AssignmentOutPut6['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "AssignmentOutPut6.to_csv('AssignmentOutPut6.csv') # Writing AssignmentOutPut1 to a csv file\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut6.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut6.groupby('Class').size()[1].sum())" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.6" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} From 0e173359efbc245815183945eed083bc97dec923 Mon Sep 17 00:00:00 2001 From: Lwasampijja Baker Date: Thu, 12 Mar 2020 11:09:29 +0300 Subject: [PATCH 13/29] Add files via upload This is my assignment assignment submission. --- Assignment Colab/lwasampijja-baker.ipynb | 1440 ++++++++++++++++++++++ 1 file changed, 1440 insertions(+) create mode 100644 Assignment Colab/lwasampijja-baker.ipynb diff --git a/Assignment Colab/lwasampijja-baker.ipynb b/Assignment Colab/lwasampijja-baker.ipynb new file mode 100644 index 0000000..df98d6b --- /dev/null +++ b/Assignment Colab/lwasampijja-baker.ipynb @@ -0,0 +1,1440 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**#STEP: 1 - IMPORTING LIBRARIES AND DATA**" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", + "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/kaggle/input/ace-class-assignment/Test.csv\n", + "/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\n", + "/kaggle/input/merged-data/merged_data.csv\n" + ] + } + ], + "source": [ + "#import libraries\n", + "\n", + "import numpy as np # linear algebra\n", + "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", + "import matplotlib.pyplot as plt \n", + "import seaborn as sns\n", + "\n", + "#let's remove the annoying warnings from our cells.\n", + "import warnings\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "\n", + "import os\n", + "for dirname, _, filenames in os.walk('/kaggle/input'):\n", + " for filename in filenames:\n", + " print(os.path.join(dirname, filename))" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "#Loading the training datasets \n", + "\n", + "df = pd.read_csv(\"../input/ace-class-assignment/AMP_TrainSet.csv\")\n", + "\n", + "#Loading the Testing datasets \n", + "\n", + "Test = pd.read_csv(\"../input/ace-class-assignment/Test.csv\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**#STEP: 2 -DATA VISUALISATION AND CLEANING**" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0", + "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a" + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n", + "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", + "mean 2.060237 8.521520 0.971410 73.668760 \n", + "std 3.819929 7.586652 0.107413 8.527489 \n", + "min -16.000000 0.000000 0.684000 42.750000 \n", + "25% 0.000000 2.516000 0.895000 68.294000 \n", + "50% 2.000000 7.143000 0.963000 74.059500 \n", + "75% 4.000000 13.158000 1.041000 79.343750 \n", + "max 30.000000 46.667000 1.451000 101.682000 \n", + "\n", + " FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n", + "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", + "mean 0.994007 -2.432927 0.088545 15.683233 \n", + "std 0.031333 1.707223 0.284133 11.575665 \n", + "min 0.866000 -10.432000 0.000000 0.041000 \n", + "25% 0.974000 -3.606000 0.000000 5.587500 \n", + "50% 0.994000 -2.296500 0.000000 14.988500 \n", + "75% 1.011000 -1.283250 0.000000 26.807750 \n", + "max 1.196000 3.576000 1.000000 51.280000 \n", + "\n", + " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 CLASS \n", + "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", + "mean 73.650828 5.911361 1.235255 0.500000 \n", + "std 9.166092 0.693689 0.210012 0.500082 \n", + "min 42.778000 3.533000 0.785000 0.000000 \n", + "25% 67.556000 5.459250 1.082000 0.000000 \n", + "50% 73.697000 5.925500 1.184000 0.500000 \n", + "75% 79.778000 6.382000 1.351000 1.000000 \n", + "max 103.167000 8.662000 2.192000 1.000000 " + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#for this we use the describe function on the dataset\n", + "df.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#Visualize this class\n", + "sns.countplot(df['CLASS'],label=\"Count\")" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "FULL_Charge 0\n", + "FULL_AcidicMolPerc 0\n", + "FULL_AURR980107 0\n", + "FULL_DAYM780201 0\n", + "FULL_GEOR030101 0\n", + "FULL_OOBM850104 0\n", + "NT_EFC195 0\n", + "AS_MeanAmphiMoment 0\n", + "AS_DAYM780201 0\n", + "AS_FUKS010112 0\n", + "CT_RACS820104 0\n", + "CLASS 0\n", + "dtype: int64" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Count the empty (NaN, NAN, na) values in each column\n", + "df.isna().sum()\n", + "\n", + "# None of my columns have any empty fields, which is good." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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FULL_AcidicMolPerc-0.6129961.0000000.7947960.5414810.1152010.513344-0.143168-0.4315900.4496210.002334-0.213543-0.598816
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FULL_DAYM780201-0.4346030.5414810.5482531.0000000.0101180.334778-0.090058-0.4087930.8941910.055915-0.326792-0.554838
FULL_GEOR030101-0.0587250.1152010.3461390.0101181.0000000.319157-0.230417-0.160269-0.0290850.040480-0.151935-0.260470
FULL_OOBM850104-0.2837580.5133440.4627120.3347780.3191571.000000-0.230561-0.3362970.275640-0.4527690.155304-0.453287
NT_EFC1950.088068-0.143168-0.169540-0.090058-0.230417-0.2305611.0000000.178683-0.0368440.1459240.0808980.260702
AS_MeanAmphiMoment0.355477-0.431590-0.426097-0.408793-0.160269-0.3362970.1786831.000000-0.3223780.0255800.1715240.693552
AS_DAYM780201-0.3653740.4496210.4562600.894191-0.0290850.275640-0.036844-0.3223781.0000000.045562-0.256060-0.437168
AS_FUKS010112-0.0905700.0023340.0329580.0559150.040480-0.4527690.1459240.0255800.0455621.000000-0.4452840.033432
CT_RACS8201040.232929-0.213543-0.403599-0.326792-0.1519350.1553040.0808980.171524-0.256060-0.4452841.0000000.267652
CLASS0.534602-0.598816-0.584111-0.554838-0.260470-0.4532870.2607020.693552-0.4371680.0334320.2676521.000000
\n", + "
" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 \\\n", + "FULL_Charge 1.000000 -0.612996 -0.490977 \n", + "FULL_AcidicMolPerc -0.612996 1.000000 0.794796 \n", + "FULL_AURR980107 -0.490977 0.794796 1.000000 \n", + "FULL_DAYM780201 -0.434603 0.541481 0.548253 \n", + "FULL_GEOR030101 -0.058725 0.115201 0.346139 \n", + "FULL_OOBM850104 -0.283758 0.513344 0.462712 \n", + "NT_EFC195 0.088068 -0.143168 -0.169540 \n", + "AS_MeanAmphiMoment 0.355477 -0.431590 -0.426097 \n", + "AS_DAYM780201 -0.365374 0.449621 0.456260 \n", + "AS_FUKS010112 -0.090570 0.002334 0.032958 \n", + "CT_RACS820104 0.232929 -0.213543 -0.403599 \n", + "CLASS 0.534602 -0.598816 -0.584111 \n", + "\n", + " FULL_DAYM780201 FULL_GEOR030101 FULL_OOBM850104 \\\n", + "FULL_Charge -0.434603 -0.058725 -0.283758 \n", + "FULL_AcidicMolPerc 0.541481 0.115201 0.513344 \n", + "FULL_AURR980107 0.548253 0.346139 0.462712 \n", + "FULL_DAYM780201 1.000000 0.010118 0.334778 \n", + "FULL_GEOR030101 0.010118 1.000000 0.319157 \n", + "FULL_OOBM850104 0.334778 0.319157 1.000000 \n", + "NT_EFC195 -0.090058 -0.230417 -0.230561 \n", + "AS_MeanAmphiMoment -0.408793 -0.160269 -0.336297 \n", + "AS_DAYM780201 0.894191 -0.029085 0.275640 \n", + "AS_FUKS010112 0.055915 0.040480 -0.452769 \n", + "CT_RACS820104 -0.326792 -0.151935 0.155304 \n", + "CLASS -0.554838 -0.260470 -0.453287 \n", + "\n", + " NT_EFC195 AS_MeanAmphiMoment AS_DAYM780201 \\\n", + "FULL_Charge 0.088068 0.355477 -0.365374 \n", + "FULL_AcidicMolPerc -0.143168 -0.431590 0.449621 \n", + "FULL_AURR980107 -0.169540 -0.426097 0.456260 \n", + "FULL_DAYM780201 -0.090058 -0.408793 0.894191 \n", + "FULL_GEOR030101 -0.230417 -0.160269 -0.029085 \n", + "FULL_OOBM850104 -0.230561 -0.336297 0.275640 \n", + "NT_EFC195 1.000000 0.178683 -0.036844 \n", + "AS_MeanAmphiMoment 0.178683 1.000000 -0.322378 \n", + "AS_DAYM780201 -0.036844 -0.322378 1.000000 \n", + "AS_FUKS010112 0.145924 0.025580 0.045562 \n", + "CT_RACS820104 0.080898 0.171524 -0.256060 \n", + "CLASS 0.260702 0.693552 -0.437168 \n", + "\n", + " AS_FUKS010112 CT_RACS820104 CLASS \n", + "FULL_Charge -0.090570 0.232929 0.534602 \n", + "FULL_AcidicMolPerc 0.002334 -0.213543 -0.598816 \n", + "FULL_AURR980107 0.032958 -0.403599 -0.584111 \n", + "FULL_DAYM780201 0.055915 -0.326792 -0.554838 \n", + "FULL_GEOR030101 0.040480 -0.151935 -0.260470 \n", + "FULL_OOBM850104 -0.452769 0.155304 -0.453287 \n", + "NT_EFC195 0.145924 0.080898 0.260702 \n", + "AS_MeanAmphiMoment 0.025580 0.171524 0.693552 \n", + "AS_DAYM780201 0.045562 -0.256060 -0.437168 \n", + "AS_FUKS010112 1.000000 -0.445284 0.033432 \n", + "CT_RACS820104 -0.445284 1.000000 0.267652 \n", + "CLASS 0.033432 0.267652 1.000000 " + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Correlations or influence between the attributes\n", + "df.corr()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#Visualize the correlation \n", + "#NOTE: To see the numbers within the cell ==> sns.heatmap(df.corr(), annot=True)\n", + "plt.figure(figsize=(20,20)) #This is used to change the size of the figure/ heatmap\n", + "sns.heatmap(df.corr(), annot=True, fmt='.0%')" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#Skew of Univariate Distributions\n", + "plt.figure(figsize=(20,20))\n", + "df.skew().plot(kind='bar')\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "text/plain": [ + "
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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#Scatter Plot Matrix: Scatter plots are useful for spotting structured relationships between variables, \n", + "#like whether you could summarize the relationship between two variables with a line\n", + "#AKA “pairs plot” in which one variable in the same data row is matched with another variable's value\n", + "\n", + "plt.figure(figsize=(20,20))\n", + "sns.pairplot(df)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**#STEP: 3 -MODELLING**" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "#Split the data into independent 'X' and dependent 'Y' variables\n", + "X = df.iloc[:, 0:11].values #Notice I started from index 0 to 11, essentially removing the id column & CLASS cloumn at the end\n", + "Y = df['CLASS'].values #Get the target variable 'CLASS' located at index=12\n" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "# Split the dataset into 75% Training set and 25% Testing set\n", + "from sklearn.model_selection import train_test_split\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size = 0.25, random_state = 0)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "# I Scaleed the data to bring all features to the same level of magnitude\n", + "# This means the data will be within a specific range for example 0 -100 or 0 - 1\n", + "\n", + "#Feature Scaling\n", + "from sklearn.preprocessing import StandardScaler\n", + "sc = StandardScaler()\n", + "X_train = sc.fit_transform(X_train)\n", + "X_test = sc.transform(X_test)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "#Create a function within many Machine Learning Models to the Training Set\n", + "def modelsT(X_train,Y_train):\n", + " \n", + " #1. Logistic Regression Algorithm to the Training Set\n", + " from sklearn.linear_model import LogisticRegression\n", + " log = LogisticRegression(random_state = 0)\n", + " log.fit(X_train, Y_train)\n", + " \n", + " #2. Using KNeighborsClassifier Method of neighbors class to use Nearest Neighbor algorithm\n", + " from sklearn.neighbors import KNeighborsClassifier\n", + " knn = KNeighborsClassifier(n_neighbors = 5, metric = 'minkowski', p = 2)\n", + " knn.fit(X_train, Y_train)\n", + " \n", + "\n", + " #3. Using SVC method of svm class to use Support Vector Machine Algorithm\n", + " from sklearn.svm import SVC\n", + " svc_lin = SVC(kernel = 'linear', random_state = 0)\n", + " svc_lin.fit(X_train, Y_train)\n", + " \n", + "\n", + " #4. Using SVC method of svm class to use Kernel SVM Algorithm\n", + " from sklearn.svm import SVC\n", + " svc_rbf = SVC(kernel = 'rbf', random_state = 0)\n", + " svc_rbf.fit(X_train, Y_train)\n", + " \n", + " #5. Using GaussianNB method of naïve_bayes class to use Naïve Bayes Algorithm\n", + " from sklearn.naive_bayes import GaussianNB\n", + " gauss = GaussianNB()\n", + " gauss.fit(X_train, Y_train)\n", + "\n", + "\n", + " #6. Using DecisionTreeClassifier of tree class to use Decision Tree Algorithm\n", + " from sklearn.tree import DecisionTreeClassifier\n", + " tree = DecisionTreeClassifier(criterion = 'entropy', random_state = 0)\n", + " tree.fit(X_train, Y_train)\n", + "\n", + "\n", + " #7. Using RandomForestClassifier method of ensemble class\n", + " from sklearn.ensemble import RandomForestClassifier\n", + " forest = RandomForestClassifier(n_estimators = 10, criterion = 'entropy', random_state = 0)\n", + " forest.fit(X_train, Y_train)\n", + " \n", + " #8. Using Perceptron\n", + " from sklearn.linear_model import Perceptron\n", + " perceptron = Perceptron()\n", + " perceptron.fit(X_train, Y_train)\n", + " \n", + "\n", + " #9. Stochastic Gradient Descent\n", + " from sklearn.linear_model import SGDClassifier\n", + " sgd = SGDClassifier()\n", + " sgd.fit(X_train, Y_train)\n", + " \n", + " \n", + " #10. Linear Discriminant Analysis \n", + " from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", + " lda = LinearDiscriminantAnalysis(n_components=2)\n", + " lda.fit(X_train, Y_train)\n", + " \n", + " \n", + " #print model accuracy on the Training data.\n", + " \n", + " print('[1]Logistic Regression Training Accuracy:',log.score(X_train, Y_train)) \n", + " print('[2]K Nearest Neighbor Training Accuracy:',knn.score(X_train, Y_train))\n", + " print('[3]Support Vector Machine (Linear Classifier) Training Accuracy:', svc_lin.score(X_train, Y_train)) \n", + " print('[4]Support Vector Machine (RBF Classifier) Training Accuracy:', svc_rbf.score(X_train, Y_train)) \n", + " print('[5]Gaussian Naive Bayes Training Accuracy:', gauss.score(X_train, Y_train)) \n", + " print('[6]Decision Tree Classifier Training Accuracy:', tree.score(X_train, Y_train)) \n", + " print('[7]Random Forest Classifier Training Accuracy:', forest.score(X_train, Y_train)) \n", + " print('[8]Perceptron Training Accuracy:', perceptron.score(X_train, Y_train)) \n", + " print('[9]Stochastic Gradient Descent Training Accuracy:', sgd.score(X_train, Y_train)) \n", + " print('[10]Linear Discriminant Analysis Training Accuracy:', lda.score(X_train, Y_train)) \n", + " \n", + " return log, knn, svc_lin, svc_rbf, gauss, tree, forest, perceptron, sgd, lda" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[1]Logistic Regression Training Accuracy: 0.9187884108867428\n", + "[2]K Nearest Neighbor Training Accuracy: 0.9433713784021072\n", + "[3]Support Vector Machine (Linear Classifier) Training Accuracy: 0.9183494293239683\n", + "[4]Support Vector Machine (RBF Classifier) Training Accuracy: 0.9477611940298507\n", + "[5]Gaussian Naive Bayes Training Accuracy: 0.9192273924495171\n", + "[6]Decision Tree Classifier Training Accuracy: 1.0\n", + "[7]Random Forest Classifier Training Accuracy: 0.9947322212467077\n", + "[8]Perceptron Training Accuracy: 0.8762071992976295\n", + "[9]Stochastic Gradient Descent Training Accuracy: 0.9100087796312555\n", + "[10]Linear Discriminant Analysis Training Accuracy: 0.9135206321334504\n" + ] + } + ], + "source": [ + "#Printing out accuracy of each Model\n", + "modelT = modelsT(X_train,Y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model 0\n", + " precision recall f1-score support\n", + "\n", + " 0 0.91 0.93 0.92 353\n", + " 1 0.94 0.92 0.93 407\n", + "\n", + " accuracy 0.93 760\n", + " macro avg 0.93 0.93 0.93 760\n", + "weighted avg 0.93 0.93 0.93 760\n", + "\n", + "0.9263157894736842\n", + "\n", + "Model 1\n", + " precision recall f1-score support\n", + "\n", + " 0 0.90 0.95 0.92 353\n", + " 1 0.95 0.91 0.93 407\n", + "\n", + " accuracy 0.93 760\n", + " macro avg 0.92 0.93 0.92 760\n", + "weighted avg 0.93 0.93 0.93 760\n", + "\n", + "0.925\n", + "\n", + "Model 2\n", + " precision recall f1-score support\n", + "\n", + " 0 0.90 0.95 0.92 353\n", + " 1 0.95 0.91 0.93 407\n", + "\n", + " accuracy 0.93 760\n", + " macro avg 0.92 0.93 0.92 760\n", + "weighted avg 0.93 0.93 0.93 760\n", + "\n", + "0.925\n", + "\n", + "Model 3\n", + " precision recall f1-score support\n", + "\n", + " 0 0.93 0.95 0.94 353\n", + " 1 0.95 0.93 0.94 407\n", + "\n", + " accuracy 0.94 760\n", + " macro avg 0.94 0.94 0.94 760\n", + "weighted avg 0.94 0.94 0.94 760\n", + "\n", + "0.9407894736842105\n", + "\n", + "Model 4\n", + " precision recall f1-score support\n", + "\n", + " 0 0.91 0.92 0.92 353\n", + " 1 0.93 0.92 0.93 407\n", + "\n", + " accuracy 0.92 760\n", + " macro avg 0.92 0.92 0.92 760\n", + "weighted avg 0.92 0.92 0.92 760\n", + "\n", + "0.9210526315789473\n", + "\n", + "Model 5\n", + " precision recall f1-score support\n", + "\n", + " 0 0.91 0.88 0.89 353\n", + " 1 0.90 0.92 0.91 407\n", + "\n", + " accuracy 0.90 760\n", + " macro avg 0.90 0.90 0.90 760\n", + "weighted avg 0.90 0.90 0.90 760\n", + "\n", + "0.9013157894736842\n", + "\n", + "Model 6\n", + " precision recall f1-score support\n", + "\n", + " 0 0.92 0.95 0.93 353\n", + " 1 0.96 0.92 0.94 407\n", + "\n", + " accuracy 0.94 760\n", + " macro avg 0.94 0.94 0.94 760\n", + "weighted avg 0.94 0.94 0.94 760\n", + "\n", + "0.9368421052631579\n", + "\n", + "Model 7\n", + " precision recall f1-score support\n", + "\n", + " 0 0.89 0.88 0.89 353\n", + " 1 0.90 0.91 0.90 407\n", + "\n", + " accuracy 0.89 760\n", + " macro avg 0.89 0.89 0.89 760\n", + "weighted avg 0.89 0.89 0.89 760\n", + "\n", + "0.8947368421052632\n", + "\n", + "Model 8\n", + " precision recall f1-score support\n", + "\n", + " 0 0.88 0.96 0.92 353\n", + " 1 0.96 0.89 0.92 407\n", + "\n", + " accuracy 0.92 760\n", + " macro avg 0.92 0.92 0.92 760\n", + "weighted avg 0.92 0.92 0.92 760\n", + "\n", + "0.9210526315789473\n", + "\n", + "Model 9\n", + " precision recall f1-score support\n", + "\n", + " 0 0.90 0.96 0.93 353\n", + " 1 0.96 0.90 0.93 407\n", + "\n", + " accuracy 0.93 760\n", + " macro avg 0.93 0.93 0.93 760\n", + "weighted avg 0.93 0.93 0.93 760\n", + "\n", + "0.9302631578947368\n", + "\n" + ] + } + ], + "source": [ + "#Showing the confusion matrix and accuracy for all of the models on the test data\n", + "#Classification accuracy is the ratio of correct predictions to total predictions made.\n", + "\n", + "from sklearn.metrics import classification_report\n", + "from sklearn.metrics import accuracy_score\n", + "\n", + "for i in range(len(modelT)):\n", + " print('Model ',i)\n", + " #Check precision, recall, f1-score\n", + " print( classification_report(Y_test, modelT[i].predict(X_test)) )\n", + " #Another way to get the models accuracy on the test data\n", + " print( accuracy_score(Y_test, modelT[i].predict(X_test)))\n", + " print()#Print a new line" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('LR', 0.835359128018065, 0.2708521320979506)\n", + "('LDA', 0.8535044293903076, 0.2571395669719574)\n", + "('KNN', 0.8027933385443807, 0.2521136100771112)\n", + "('TREE', 0.7368681605002605, 0.2833452298920867)\n", + "('NB', 0.880815746048289, 0.11642272449162755)\n", + "('SVM', 0.8350280093798853, 0.25836507020625044)\n", + "('FOREST', 0.8087067917318048, 0.2909686308113511)\n", + "('PERC', 0.8350964043772798, 0.2645271720286034)\n", + "('SGD', 0.7037432690637486, 0.3108465910214562)\n", + "('RVM', 0.8350280093798853, 0.25836507020625044)\n" + ] + }, + { + "data": { + "image/png": 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GYEVVXZ/kzCRH9t3+EHge8Lkka5KsnGJ3kqQ5NspUD1W1Clg1tO70gceHjbkuSdIM8Zu7ktQYg1+SGmPwS1JjDH5JaozBL0mNMfglqTEGvyQ1xuCXpMYY/JLUGINfkhpj8EtSYwx+SWqMwS9JjTH4JakxBr8kNcbgl6TGGPyS1BiDX5IaY/BLUmMMfklqjMEvSY0x+CWpMQa/JDXG4Jekxhj8ktQYg1+SGmPwS1JjDH5JaozBL0mNMfglqTEGvyQ1xuCXpMYY/JLUGINfkhozUvAnWZrkpiRrk5w6SfsuSS7u27+ZZL9xFypJGo9pgz/JTsDZwOHAYmB5ksVD3d4N3F9VLwPOAj487kIlSeMxyoj/EGBtVd1SVU8CFwFHDfU5Cvh0//gS4NAkGV+ZkqRxGSX49wFuH1ie6NdN2qeq1gMPAi8cR4GSpPGaN0KfyUbutQV9SHICcEK/+ESS60Y4fgv2Bu6Z6yK2EV6LjbwWG3ktNjpga3cwSvBPAAsHlhcAd0zRZyLJPGAP4L7hHVXVucC5AElWV9WSLSl6R+O12MhrsZHXYiOvxUZJVm/tPkaZ6rkaWJRk/yQ7A8uAlUN9VgLH9Y/fDnypqp414pckzb1pR/xVtT7JicDlwE7Ap6rq+iRnAquraiXwP4HPJFlLN9JfNpNFS5K23ChTPVTVKmDV0LrTBx4/DvzSZh773M3svyPzWmzktdjIa7GR12Kjrb4WcUZGktriTzZIUmNmJfiTPDLJujOS/FOSNUluSLJ8NmqZbSOc+/eS/NXwt6GTzE/yVJL3zl61M2fwOiQ5oj/vl/bX4tEkL5qibyX56MDyryc5Y9YKH5MkL+yf7zVJ7hp4/tf057gmyXVJvpBkz36b/ZI8NtBvTZJj+7Zbk/y/gfUfm9szHI9NPd9D/998J8mfJdmhBq9JPpDk+iTX9ud5WZIPDfU5KMmN/eNbk/ztUPua6T4qP9cX7ayqOojum79/nuS5c1zPbDqrqg6qqkXAxcCXkswfaP8l4Cpgh3pBTHIo8HFgaVV9v199D/D+KTZ5AvjFJHvPRn0zparu7Z/vg4BPsPH5Pwj4Qf/4x+k+HPG+gU1v3tCv/3f+QNtbB9afNIunM5Ome743ZMZi4JXAm2etshmW5CeBnwNeU1WvAg4D/gB4x1DXZcAFA8u7J1nY7+PAUY4118EPQFV9D3gUeMFc1zIXqupi4ArglwdWL6cLwwVJhr8pvV1K8ibgfwA/W1U3DzR9CnhHkr0m2Ww93c2sk2ehxG3BN3j2N+NbMurzvTOwK3D/jFc0e34MuKeqngCoqnuq6ivAA0leN9DvaLqfztlgBRtfHJYDF053oG0i+JO8BvheVd0917XMoX8AXgHQv3q/uKr+nmc+qduzXYC/Bn6+qr4z1PYIXfj/2hTbng0ck2SPGaxvzvU/iHgoz/yezL8Zmup500DblQPrd6QXxk093ycnWQPcCXy3qtbMbmkz6gpgYZLvJjknyYZ3MxfSf0Q+yeuBe/vB8gaXAL/YP/6PwBemO9BcB//JSW4CvgmcMce1zLXBn71YRhf40L2y7wjTPU8Bf0f3S66T+RhwXJLnDzdU1UPA+cCOMp0x7Ef6MLsX2Av44kDb8FTP4Hzu4FTPWbNa8Qya5vneMNXzImC3JDvMd4aq6hHgtXQ/a7MOuDjJ8XQZ8Pb+fsYynj2ivw+4v78WN9LNnmzSXAf/WVV1AN2I9vwku85xPXPpYLonDbqgPz7JrXSjv1cnWTRXhY3Jv9C9Rf2JJL813FhVD9DNW/7XKbb/Y7oXjd1mrMK581gfZvvSTWG8b5r+Ldjk811VTwH/F/jp2SxqplXVD6vqy1X1QeBE4G1VdTtwK939jLexcVA46GK6d0rTTvPA3Ac/AFX1V8BqNv7sQ1OSvA34GeDCJAcAu1XVPlW1X1XtB3yIHeDb0FX1KN3Nq2OSTDby/yPgvUzyxcKquo/uP/ip3jFs96rqQbpR7q839kGHZ5nu+U4S4A3AzZO1b4+SHDA0wDsIuK1/fCHd3zq5uaomJtn8UuAjdL+wMK3ZCv4fTTIx8O+USfqcCZyyo308i6nP/eQNH+cE3gn8u6paRzfav3RoH/+LHWO6Z8P/0EuB05IcNdR2D9257zLF5h+l+5XGHVZVfQv4Nhtf6Ifn+AenPwbn+M9/9t62e5M93xvm+K+jGyCcM+tVzZznAZ9O9/H2a+k+uXRG3/Y54N/yzJu6T6uqh6vqw/3fTJmW39yVpMbsaKNrSdI0DH5JaozBL0mNMfglqTEGvyQ1xuCXpMYY/JLUGINfkhrz/wG84fQ+zP6cYwAAAABJRU5ErkJggg==\n", 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LVfXSu18cY/zjGOOxMcZTY4ynquqbVfW5McbhQiYGAAAA4FxODEJjjB9V1Rer6htV9WpVfX2M8e3u/kp3f27RAwIAAAAwXxun2WiM8XJVvfzQfb//Adt++vxjAQAAALAop1kyBgAAAMAaEYQAAAAAwghCAAAAAGEEIQAAAIAwghAAAABAGEEIAAAAIIwgBAAAABBGEAIAAAAIIwgBAAAAhBGEAAAAAMIIQgAAAABhBCEAAACAMIIQAAAAQBhBCAAAACCMIAQAAAAQRhACAAAACCMIAQAAAIQRhAAAAADCCEIAAAAAYQQhAAAAgDCCEAAAAEAYQQgAAAAgjCAEAAAAEEYQAgAAAAgjCAEAAACEEYQAAAAAwghCAAAAAGEEIQAAAIAwghAAAABAGEEIAAAAIIwgBAAAABBGEAIAAAAIIwgBAAAAhBGEAAAAAMIIQgAAAABhBCEAAACAMIIQAAAAQBhBCAAAACCMIAQAAAAQRhACAAAACCMIAQAAAIQRhAAAAADCCEIAAAAAYQQhAAAAgDCCEAAAAEAYQQgAAAAgjCAEAAAAEEYQAgAAAAgjCAEAAACEEYQAAAAAwghCAAAAAGEEIQAAAIAwghAAAABAGEEIAAAAIIwgBAAAABBGEAIAAAAIIwgBAAAAhBGEAAAAAMIIQgAAAABhBCEAAACAMIIQAAAAQBhBCAAAACCMIAQAAAAQRhACAAAACCMIAQAAAIQRhAAAAADCCEIAAAAAYQQhAAAAgDCCEAAAAEAYQQgAAAAgjCAEAAAAEEYQAgAAAAgjCAEAAACEEYQAAAAAwghCAAAAAGEEIQAAAIAwghAAAABAGEEIAAAAIIwgBAAAABBGEAIAAAAIIwgBAAAAhBGEAAAAAMIIQgAAAABhBCEAAACAMIIQAAAAQBhBCAAAACCMIAQAAAAQRhACAAAACCMIAQAAAIQRhAAAAADCCEIAAAAAYQQhAAAAgDCCEAAAAEAYQQgAAAAgjCAEAAAAEEYQAgAAAAgjCAEAAACEEYQAAAAAwghCAAAAAGEEIQAAAIAwghAAAABAGEEIAAAAIIwgBAAAABBGEAIAAAAIIwgBAAAAhBGEAAAAAMIIQgAAAABhBCEAAACtVr0qAAAWOElEQVSAMIIQAAAAQBhBCAAAACCMIAQAAAAQRhACAAAACCMIAQAAAIQRhAAAAADCCEIAAPDP7d1/bOT5fdfx11uzDm5SoJBeq5JLmiCiMqcRTYJ1CsQKuAkogSoHiEpnqShCI8IfrUkBCQVGKqKSJQqIH1pViKgujaBMSK+tOKEjbZQOoPmjob4kpZu6UUNomyOhd6ilBSI3vuXDH/Yte3t72fGe976e/TwekuXx19/beUsfOeN55vv9GAA6IwgBAAAAdEYQAgAAAOiMIAQAAADQGUEIAAAAoDOCEAAAAEBnBCEAAACAzghCAAAAAJ0RhAAAAAA6IwgBAAAAdEYQAgAAAOiMIAQAAADQGUEIAAAAoDOCEAAAAEBnBCEAAACAzghCAAAAAJ0RhAAAAAA6IwgBAAAAdEYQAgAAAOiMIAQAAADQGUEIAAAAoDOCEAAAAEBnBCEAAACAzghCAAAAAJ0RhAAAAAA6IwgBAAAAdEYQAgAAAOiMIAQAAADQGUEIAAAAoDOCEAAAAEBnBCEAAACAzghCAAAAAJ0RhAAAAAA6IwgBAAAAdEYQAgAAAOiMIAQAAADQGUEIAAAAoDOCEAAAAEBnBCEAAACAzghCAAAAAJ0RhAAAAAA6IwgBAAAAdEYQAgAAAOiMIAQAAADQGUEIAAAAoDOCEAAAAEBnBCEAAACAzghCAAAAAJ0RhAAAAAA6IwgBAAAAdEYQAgAAAOiMIAQAAADQGUEIAAAAoDOCEAAAAEBnBCEAAACAzghCAAAAAJ0RhAAAAAA6IwgBAAAAdEYQAgAAAOiMIAQAAADQGUEIAAAAoDOCEAAAAEBnBCEAAACAzghCAAAAAJ0RhAAAAAA6IwgBAAAAdEYQAgAAAOiMIAQAAADQGUEIAAAAoDOCEAAAAEBnBCEAAACAzghCAAAAAJ0RhAAAAAA6IwgBAAAAdEYQAgAAAOiMIAQAAADQGUEIAAAAoDOCEAAAAEBnBCEAAACAzghCAAAAAJ1ZKQhV1buq6rNV9bmq+sBtvv/XquoXquo/V9XHq+qbL35UAAAAAC7CHYNQVY2S/ECSdyd5KMluVT10y2mfSrLVWvtDSR5L8vcuelAAAAAALsYqVwg9nORzrbXPt9a+kuTDSR65+YTW2qK19uWzL38myYMXOyYAAAAAF2WVIPSaJF+46eunzo69mGmSf/dShgIAAADg3rmywjl1m2PttidWfWeSrSR/7EW+/74k70uS173udSuOCAAAAMBFWuUKoaeSvPamrx9M8sVbT6qqdyaZJXlPa+23b/cPtdY+2Frbaq1tPfDAA3czLwAAAAAv0SpB6GeTvLGq3lBVr0jyaJLHbz6hqt6c5J/lNAY9ffFjAgAAAHBR7hiEWmvPJvnuJD+Z5CjJR1prn6mq76uq95yd9veTfG2SH62qT1fV4y/yzwEAAAAwsFX2EEpr7YkkT9xy7HtvevzOC54LAAAAgHtklVvGAAAAALiPCEIAAAAAnRGEAAAAADojCAEAAAB0RhACAAAA6IwgBAAAANAZQQgAAACgM4IQAAAAQGcEIQAAAIDOCEIAAAAAnRGEAAAAADojCAEAAAB0RhACAAAA6IwgBAAAANAZQQgAAACgM4IQAAAAQGcEIQAAAIDOCEIAAAAAnRGEAAAAADojCAEAAAB0RhACAAAA6IwgBAAAANAZQQgAAACgM4IQAAAAQGcEIQAAAIDOCEIAAAAAnRGEAAAAADojCAEAAAB0RhACAAAA6IwgBAAAANAZQQgAAACgM4IQAAAAQGcEIQAAAIDOCEIAAAAAnRGEAAAAADojCAEAAAB0RhACAAAA6IwgBAAAANAZQQgAAACgM4IQAAAAQGcEIQAAAIDOCEIAAAAAnRGEAAAAADojCAEAAAB0RhACAAAA6IwgBAAAANAZQQgAAACgM4IQAAAAQGcEIQAAAIDOCEIAAAAAnRGEAAAAADojCAEAAAB0RhACAAAA6IwgBAAAANAZQQgAAACgM4IQcF+Yz+eZTCYZjUaZTCaZz+dDjwQAAHBpXRl6AICXaj6fZzab5eDgINvb21kul5lOp0mS3d3dgacDAAC4fFwhBKy9/f39HBwcZGdnJxsbG9nZ2cnBwUH29/eHHg0AAOBSqtbaIE+8tbXVDg8PB3lu4P4yGo1yfHycjY2NG8dOTk6yubmZ69evDzgZAAD3q6rKUO+n4aupqidba1t3Os8VQsDaG4/HWS6Xzzu2XC4zHo8HmggAAOByE4SAtTebzTKdTrNYLHJycpLFYpHpdJrZbDb0aAAAAJeSTaWBtffcxtF7e3s5OjrKeDzO/v6+DaUBAABehD2EAAAA4JzsIcRlZQ8hAAAAAG5LEAIAAADojCAEAAAA0BlBCAAAAKAzghAAAABAZwQhAAAAgM4IQgAAAACdEYQAAAAAOiMIAQAAAHRGEAIA6NR8Ps9kMsloNMpkMsl8Ph96JAC4Z7zuPd+VoQcAAODlN5/PM5vNcnBwkO3t7SyXy0yn0yTJ7u7uwNMBwMXyuvdC1Vob5Im3trba4eHhIM8NANC7yWSSq1evZmdn58axxWKRvb29XLt2bcDJANZDVWWo99OcX0+ve1X1ZGtt647nCUIAAP0ZjUY5Pj7OxsbGjWMnJyfZ3NzM9evXB5wMYD0IQuulp9e9VYOQPYQAADo0Ho+zXC6fd2y5XGY8Hg80EQDcO173XkgQAgDo0Gw2y3Q6zWKxyMnJSRaLRabTaWaz2dCjAcCF87r3QjaVBgDo0HMbaO7t7eXo6Cjj8Tj7+/vdbqwJwP3N694L2UMIAAAAzskeQlxW9hACAAAA4LYEIQAAAIDOCEIAAAAAnRGEAAAAADojCAEAAAB0RhCCM/P5PJPJJKPRKJPJJPP5fOiRAAAA4J64MvQAcBnM5/PMZrMcHBxke3s7y+Uy0+k0SbK7uzvwdAAAAHCxXCEESfb393NwcJCdnZ1sbGxkZ2cnBwcH2d/fH3o0AAAAuHDVWhvkibe2ttrh4eEgzw23Go1GOT4+zsbGxo1jJycn2dzczPXr1wecDAAAuIyqKkO9n4avpqqebK1t3ek8VwhBkvF4nOVy+bxjy+Uy4/F4oIkAAADg3hGEIMlsNst0Os1iscjJyUkWi0Wm02lms9nQowEAAMCFs6k05P9vHL23t5ejo6OMx+Ps7+/bUBoAAID7kj2EAAAA4JzsIcRlZQ8hAAAAAG5LEAIAAADojCAEAAAA0BlBCAAAAKAzghAAAABAZwQhAAAAgM4IQgAAAACdEYQAAAAAOiMIAQAAAHRGEAIAAADojCAEAAAA0BlBCAAAAKAzghAAAABAZwQhAAAAgM4IQgAAAACdEYQAAAAAOiMIAQAAAHRGEAIAAADojCAEAAAA0BlB6ILN5/NMJpOMRqNMJpPM5/OhRwIAAAB4nitDD3A/mc/nmc1mOTg4yPb2dpbLZabTaZJkd3d34OkAAAAATrlC6ALt7+/n4OAgOzs72djYyM7OTg4ODrK/vz/0aAAAAAA3CEIX6OjoKNvb2887tr29naOjo4EmAgAALhvbTFwuVXVXHy/1v4WhCUIXaDweZ7lcPu/YcrnMeDweaCIAAOAyeW6biatXr+b4+DhXr17NbDYThQbUWnvZP+AyEIQu0Gw2y3Q6zWKxyMnJSRaLRabTaWaz2dCjAQAAl4BtJoDLooaqk1tbW+3w8HCQ576X5vN59vf3c3R0lPF4nNlsZkNpAAAgSTIajXJ8fJyNjY0bx05OTrK5uZnr168POBlwv6iqJ1trW3c6z18Zu2C7u7sCEAAAcFvPbTOxs7Nz45htJoAhuGUMAADgZWKbCeCycIUQAADAy+S5uwn29vZubDOxv7/vLgPgZWcPIQAAAID7xKp7CLl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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#Compare Machine Learning Algorithms Consistently\n", + "# Compare Algorithms\n", + "\n", + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", + "from sklearn.neighbors import KNeighborsClassifier\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "from sklearn.naive_bayes import GaussianNB\n", + "from sklearn.svm import SVC\n", + "from sklearn.ensemble import RandomForestClassifier\n", + "from sklearn.linear_model import Perceptron\n", + "from sklearn.linear_model import SGDClassifier\n", + "\n", + "array = df.values\n", + "\n", + "#split the dataset \n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "\n", + "# prepare models and add them to a list\n", + "models = []\n", + "models.append(('LR', LogisticRegression()))\n", + "models.append(('LDA', LinearDiscriminantAnalysis()))\n", + "models.append(('KNN', KNeighborsClassifier()))\n", + "models.append(('TREE', DecisionTreeClassifier()))\n", + "models.append(('NB', GaussianNB()))\n", + "models.append(('SVM', SVC()))\n", + "models.append(('FOREST', RandomForestClassifier()))\n", + "models.append(('PERC', Perceptron()))\n", + "models.append(('SGD', SGDClassifier()))\n", + "models.append(('RVM', SVC()))\n", + "\n", + "\n", + "\n", + "# evaluate each model in turn\n", + "results = []\n", + "names = []\n", + "scoring = 'accuracy'\n", + "\n", + "for name, model in models:\n", + " kfold = KFold(n_splits=10, random_state=7)\n", + " cv_results = cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\n", + " results.append(cv_results)\n", + " names.append(name)\n", + " msg = (name, cv_results.mean(), cv_results.std())\n", + " print(msg)\n", + "\n", + "# boxplot algorithm comparison\n", + "fig = plt.figure()\n", + "fig.suptitle('Algorithm Comparison')\n", + "ax = fig.add_subplot(111)\n", + "plt.figure(figsize=(20,20))\n", + "plt.boxplot(results)\n", + "ax.set_xticklabels(names)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> **##Exporting BEST Results to CSV**" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MCC: 0.8402064856722555\n", + "Accuracy: 90.0\n", + "370\n", + "388\n" + ] + } + ], + "source": [ + "from sklearn.metrics import matthews_corrcoef\n", + "\n", + "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = 10, random_state = 10)\n", + "modelG = GaussianNB()\n", + "modelG.fit(selected_features_train, Y_train)\n", + "result = modelG.score(selected_features_test, Y_test)\n", + "\n", + "Prediction = modelG.predict(selected_features_train)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (result*100.0))\n", + "\n", + "outputG = modelG.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut\n", + "\n", + "outputG = pd.DataFrame(outputG)\n", + "# Converting AssignmentOutPut to a dataframe since its output is an array\n", + "outputG.columns = ['Class'] # Naming the out\n", + "outputG.index.name = \"Index\" #Creating a column called index\n", + "outputG['Class'] = outputG['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "outputG.to_csv('outputG.csv') # Writing AssignmentOutPut1 to a csv file\n", + "#Printing the number of False and Trues\n", + "print(outputG.groupby('Class').size()[0].sum())\n", + "print(outputG.groupby('Class').size()[1].sum())" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.6" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} From 825b9bac9e2e9bac3dc958d60f1411e9b1acb599 Mon Sep 17 00:00:00 2001 From: Atwine Date: Thu, 12 Mar 2020 13:08:14 +0300 Subject: [PATCH 14/29] Make corrections --- .../nsangi-olga-tendo-checkpoint.ipynb | 2441 +++++++++++++++++ Assignment Colab/nsangi-olga-tendo.ipynb | 101 +- .../Pandas Cookbook/Pandas-Cookbook | 1 + 3 files changed, 2533 insertions(+), 10 deletions(-) create mode 100644 Assignment Colab/.ipynb_checkpoints/nsangi-olga-tendo-checkpoint.ipynb create mode 160000 Reading Material/Pandas Cookbook/Pandas-Cookbook diff --git a/Assignment Colab/.ipynb_checkpoints/nsangi-olga-tendo-checkpoint.ipynb b/Assignment Colab/.ipynb_checkpoints/nsangi-olga-tendo-checkpoint.ipynb new file mode 100644 index 0000000..2d52262 --- /dev/null +++ b/Assignment Colab/.ipynb_checkpoints/nsangi-olga-tendo-checkpoint.ipynb @@ -0,0 +1,2441 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + " Please look out for these cells for corrections." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", + "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/kaggle/input/ace-class-assignment/Test.csv\n", + "/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\n" + ] + } + ], + "source": [ + "# This Python 3 environment comes with many helpful analytics libraries installed\n", + "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", + "# For example, here's several helpful packages to load in \n", + "\n", + "import numpy as np # linear algebra\n", + "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "\n", + "\n", + "# Input data files are available in the \"../input/\" directory.\n", + "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", + "\n", + "import os\n", + "for dirname, _, filenames in os.walk('/kaggle/input'):\n", + " for filename in filenames:\n", + " print(os.path.join(dirname, filename))\n", + "# Any results you write to the current directory are saved as output.\n", + "import warnings\n", + "warnings.filterwarnings('ignore')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Naming the Training and test dataset using." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0", + "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a" + }, + "outputs": [], + "source": [ + "Train = pd.read_csv(\"../input/ace-class-assignment/AMP_TrainSet.csv\")\n", + "Test = pd.read_csv(\"../input/ace-class-assignment/Test.csv\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Confirming that the data has been read in and assigned to variables Train and Test" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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\n", + " \n", + " ## ??\n", + " \n", + " When you see these: \n", + " - I want to know if you understand the concept\n", + " - Why are you applying the concept\n", + " - What did you learn?\n", + " - I want to see that you know what you are doing." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(3038, 12)" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Train.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Establishing the attributes in the train data set" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", + " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", + " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", + " 'CLASS'],\n", + " dtype='object')" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Train.columns" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Establishing the data types for each attribute in the train data set. This helps in finding out which column has data types like strings that may need to be converted to foating points or integers to represent categorical or ordinal values. This can be done using df.dtype method or the df.info() method as shown in the two cells below, tho the df.info() is more informative.\n", + "\n", + "
\n", + " \n", + " Why is everything so big? \n", + "

like this?" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "FULL_Charge float64\n", + "FULL_AcidicMolPerc float64\n", + "FULL_AURR980107 float64\n", + "FULL_DAYM780201 float64\n", + "FULL_GEOR030101 float64\n", + "FULL_OOBM850104 float64\n", + "NT_EFC195 int64\n", + "AS_MeanAmphiMoment float64\n", + "AS_DAYM780201 float64\n", + "AS_FUKS010112 float64\n", + "CT_RACS820104 float64\n", + "CLASS int64\n", + "dtype: object" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Train.dtypes" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 3038 entries, 0 to 3037\n", + "Data columns (total 12 columns):\n", + "FULL_Charge 3038 non-null float64\n", + "FULL_AcidicMolPerc 3038 non-null float64\n", + "FULL_AURR980107 3038 non-null float64\n", + "FULL_DAYM780201 3038 non-null float64\n", + "FULL_GEOR030101 3038 non-null float64\n", + "FULL_OOBM850104 3038 non-null float64\n", + "NT_EFC195 3038 non-null int64\n", + "AS_MeanAmphiMoment 3038 non-null float64\n", + "AS_DAYM780201 3038 non-null float64\n", + "AS_FUKS010112 3038 non-null float64\n", + "CT_RACS820104 3038 non-null float64\n", + "CLASS 3038 non-null int64\n", + "dtypes: float64(10), int64(2)\n", + "memory usage: 284.9 KB\n" + ] + } + ], + "source": [ + "Train.info()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Statistical summary of the data in each column.\n", + "### This helps understand the distribution of each column as this method returns values like percentiles,standard deviation, minimum and maximum values of each attribute. This way you can also find out if you have negative values in any attribute. This also helps in understanding the scales at which each attribute is at." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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\n", + " \n", + " ## ??" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Since this is a classification problem, its important to check out the propotions of the values in the class to be predicted as its possible one class may have more values as compared to the others.\n", + "\n", + "
\n", + " \n", + " ## ??" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0, 0.5, 'Distirbution')" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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km4HDgT6SaoDLyK6i6gHMlATwSEScGxELJd0CPEM2hHVeRGxK6zkfuAfoCkyOiIXlitnMzJpWtsQREacUKb6+kfY/An5UpPxu4O5WDM3MzFrA3xw3M7NcnDjMzCwXJw4zM8vFicPMzHJx4jAzs1ycOMzMLBcnDjMzy8WJw8zMcnHiMDOzXJw4zMwsFycOMzPLxYnDzMxyceIwM7NcnDjMzCwXJw4zM8vFicPMzHJx4jAzs1ycOMzMLJeyJQ5JkyWtkfR0QdnukmZKWpz+7pbKJekaSUskLZA0smCZcan9YknjyhWvmZmVppw9jhuAo+uVXQL8LSKGAn9L8wDHAEPTYwLwa8gSDXAZcBBwIHBZXbIxM7PKKFviiIjZwLp6xWOAKWl6CjC2oHxqZB4BekkaABwFzIyIdRHxCjCTbZORmZm1obY+x9E/IlYBpL/9UvlAYHlBu5pU1lC5mZlVSHs5Oa4iZdFI+bYrkCZImiNpTm1tbasGZ2Zm7+tWSiNJfYGvANWFy0TEWTm3t1rSgIhYlYai1qTyGmBwQbtBwMpUfni98lnFVhwR1wLXAowaNapocjEzs5YrtcdxB7Ar8D/AXQWPvKYDdVdGjUvrrSs/I11ddTCwPg1l3QMcKWm3dFL8yFRmZmYVUlKPA9gxIi7Os2JJN5P1FvpIqiG7Oupy4BZJZwMvAiel5ncDxwJLgLeAMwEiYp2kHwCPp3bfj4j6J9zNzKwNlZo47pR0bETcXeqKI+KUBqpGF2kbwHkNrGcyMLnU7ZqZWXmVOlR1IVny2CDp9fR4rZyBmZlZ+1RSjyMiepY7EDMz6xhKHapC0ueBw9LsrIi4szwhmZlZe1bSUJWky8mGq55JjwtTmZmZdTKl9jiOBUZExGYASVOAJ3j/XlNmZtZJ5PnmeK+C6V1bOxAzM+sYSu1x/Bh4QtJ9ZLcBOQy4tGxRmZlZu1XqVVU3S5oFHECWOC6OiJfKGZiZmbVPjQ5VSfpo+jsSGEB276jlwJ6FP7ZkZmadR1M9jm+S/bDST4rUBfDZVo/IzMzatUYTR0RMSJPHRMSGwjpJVWWLyszM2q1Sr6p6qMQyMzPbzjXa45C0B9kv7n1A0v68/8NKuwA7ljk2MzNrh5o6x3EUMJ7sB5R+WlD+OvCdMsVkZmbtWFPnOKYAUySdGBF/bqOYzMysHSv1C4DDJe1bvzAivt/K8ZiZWTtXauJ4o2C6CjgeWNT64ZiZWXtX6jfHt/oeh6QryX4n3MzMOpk8NzkstCOwT2sGYmZmHUOpv8fxlKQF6bEQeA74WXM3KukbkhZKelrSzZKqJA2R9KikxZL+KGmH1LZHml+S6qubu10zM2u5Us9xHF8w/R6wOiLea84GJQ0ELgCGRcTbkm4BTib7zY+rImKapN8AZwO/Tn9fiYgPSToZ+E/gS83ZtpmZtVxJPY6IWAb0BsYA/wp8rIXb7Ub2pcJuZMNeq8jue3Vrqp8CjE3TY9I8qX60JGFmZhVR6lDV98jevHsDfYAbJP17czYYESuAK4EXyRLGemAu8GpBL6aG7BvrpL/L07Lvpfa9i8Q4QdIcSXNqa2ubE5qZmZWg1JPjpwAHRMRlEXEZcDBwWnM2KGk3sl7EEGBPYCfgmCJNo26RRureL4i4NiJGRcSovn37Nic0MzMrQamJ4wWy72/U6QH8vZnb/Bzwj4iojYiNwG3AIUCvNHQF2S1OVqbpGmAwQKrfFVjXzG2bmVkLNXWTw5+Tfbp/B1goaWaaPwJ4sJnbfBE4WNKOwNvAaGAOcB/wBWAaMA64I7WfnuYfTvX3RsQ2PQ4zM2sbTV1VNSf9nQvcXlA+q7kbjIhHJd0KzCO7QusJ4FrgLmCapB+msuvTItcDN0paQtbTOLm52zYzs5Zr8iaHkroCUyLiy6210XSe5LJ6xUuBA4u03QCc1FrbNjOzlmnyHEdEbAL61n0hz8zMOrdSvwD4AvC/kqYDb9YVRsRPG1zCzMy2S6UmjpXp0QXoWb5wzMysvSv17rj/t9yBmJlZx9DU5bhXR8RESX+l+JfuPl+2yMzMrF1qqsdxY/p7ZbkDMTOzjqGpy3HnpskREbHVbdQlXQjcX67AzMysfSr1liPjipSNb8U4zMysg2jqHMcpwKnAkHQpbp1dgLXlDMzMzNqnps5xPER26/M+QOHvjr8OLChXUGZm1n41dY5jGbBM0ueAtyNis6QPAx8FnmqLAM3MrH0p9RzHbKAq/ezr34AzgRvKFZSZmbVfpSYORcRbZD8b+/OIOAEYVr6wzMysvSo5cUj6JNmv/t2Vykq9XYmZmW1HSk0cE4FLgdsjYqGkfch+eMnMzDqZUu9VdT8FX/aLiKXABeUKyszM2i/fq8rMzHLxvarMzCyXku5VFRH3S+qbpmtbulFJvYDfAsPJejJnAc8BfwSqyX446osR8YokAT8DjgXeAsZHxLyWxmBmZs3T6MlxZSZJehl4FnheUq2k77Vwuz8D/jsiPgp8HFgEXAL8LSKGkn1X5JLU9hhgaHpMAH7dwm2bmVkLNHVV1UTgU8ABEdE7InYDDgI+JekbzdmgpF2Aw4DrASLi3Yh4FRgDTEnNpgBj0/QYYGpkHgF6SRrQnG2bmVnLNZU4zgBOiYh/1BWkK6q+nOqaYx+gFvidpCck/VbSTkD/iFiVtrEK6JfaDwSWFyxfk8rMzKwCmkoc3SPi5fqF6TxH92ZusxswEvh1ROwPvMn7w1LFqEjZNld4SZogaY6kObW1LT4NY2ZmDWgqcbzbzLrG1AA1EfFomr+VLJGsrhuCSn/XFLQfXLD8IGBl/ZVGxLURMSoiRvXt27eZoZmZWVOaShwfl/RakcfrwMeas8GIeAlYLukjqWg08Awwnfd/MGoccEeang6ckU7UHwysrxvSMjOzttfU5bhdy7TdrwM3SdoBWEp2t90uwC2SzgZeBE5Kbe8muxR3CdnluGeWKSYzMytBRW5UGBHzgVFFqkYXaRvAeWUPyszMSlLqTQ7NzMwAJw4zM8vJicPMzHJx4jAzs1ycOMzMLBcnDjMzy8WJw8zMcnHiMDOzXJw4zMwsFycOMzPLxYnDzMxyceIwM7NcnDjMzCwXJw4zM8vFicPMzHJx4jAzs1ycOMzMLBcnDjMzy6ViiUNSV0lPSLozzQ+R9KikxZL+mH6PHEk90vySVF9dqZjNzKyyPY4LgUUF8/8JXBURQ4FXgLNT+dnAKxHxIeCq1M7MzCqkIolD0iDgOOC3aV7AZ4FbU5MpwNg0PSbNk+pHp/ZmZlYBlepxXA18G9ic5nsDr0bEe2m+BhiYpgcCywFS/frU3szMKqDNE4ek44E1ETG3sLhI0yihrnC9EyTNkTSntra2FSI1M7NiKtHj+BTweUkvANPIhqiuBnpJ6pbaDAJWpukaYDBAqt8VWFd/pRFxbUSMiohRffv2Le8emJl1Ym2eOCLi0ogYFBHVwMnAvRFxGnAf8IXUbBxwR5qenuZJ9fdGxDY9DjMzaxvt6XscFwPflLSE7BzG9an8eqB3Kv8mcEmF4jMzM6Bb003KJyJmAbPS9FLgwCJtNgAntWlgZmbWoPbU4zAzsw7AicPMzHJx4jAzs1ycOMzMLBcnDjMzy8WJw8zMcnHiMDOzXJw4zMwsFycOMzPLxYnDzMxyceIwM7NcKnqvKrNK2bhxIzU1NWzYsKHSobSZqqoqBg0aRPfu3SsdinVwThzWKdXU1NCzZ0+qq6vpDL9EHBGsXbuWmpoahgwZUulwrIPzUJV1Shs2bKB3796dImkASKJ3796dqodl5ePEYZ1WZ0kadTrb/lr5OHGYmVkuThxmLfTSSy9x8skn88EPfpBhw4Zx7LHH8vzzzzN8+PBKh2ZWFj45btYCEcEJJ5zAuHHjmDZtGgDz589n9erVFY7MrHzavMchabCk+yQtkrRQ0oWpfHdJMyUtTn93S+WSdI2kJZIWSBrZ1jGbNeS+++6je/funHvuuVvKRowYweDBg7fMv/DCCxx66KGMHDmSkSNH8tBDDwGwatUqDjvsMEaMGMHw4cN54IEH2LRpE+PHj2f48OF87GMf46qrrmrzfTJrSiV6HO8BF0XEPEk9gbmSZgLjgb9FxOWSLgEuAS4GjgGGpsdBwK/TX7OKe/rpp/nEJz7RaJt+/foxc+ZMqqqqWLx4Maeccgpz5szhD3/4A0cddRTf/e532bRpE2+99Rbz589nxYoVPP300wC8+uqrbbEbZrm0eeKIiFXAqjT9uqRFwEBgDHB4ajYFmEWWOMYAUyMigEck9ZI0IK3HrN3buHEj559/PvPnz6dr1648//zzABxwwAGcddZZbNy4kbFjxzJixAj22Wcfli5dyte//nWOO+44jjzyyApHb7atip4cl1QN7A88CvSvSwbpb7/UbCCwvGCxmlRmVnH77rsvc+fObbTNVVddRf/+/XnyySeZM2cO7777LgCHHXYYs2fPZuDAgZx++ulMnTqV3XbbjSeffJLDDz+cX/7yl5xzzjltsRtmuVQscUjaGfgzMDEiXmusaZGyKLK+CZLmSJpTW1vbWmGaNeqzn/0s77zzDtddd92Wsscff5xly5ZtmV+/fj0DBgygS5cu3HjjjWzatAmAZcuW0a9fP77yla9w9tlnM2/ePF5++WU2b97MiSeeyA9+8APmzZvX5vtk1pSKXFUlqTtZ0rgpIm5LxavrhqAkDQDWpPIaYHDB4oOAlfXXGRHXAtcCjBo1apvEYlYOkrj99tuZOHEil19+OVVVVVRXV3P11VdvafO1r32NE088kT/96U985jOfYaeddgJg1qxZXHHFFXTv3p2dd96ZqVOnsmLFCs4880w2b94MwI9//OOK7JdZY9o8cSj7+ur1wKKI+GlB1XRgHHB5+ntHQfn5kqaRnRRf7/Mb1p7sueee3HLLLduU153gHjp0KAsWLNhSXpcMxo0bx7hx47ZZzr0Ma+8q0eP4FHA68JSk+ansO2QJ4xZJZwMvAieluruBY4ElwFvAmW0brpm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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Train.groupby('CLASS').size().plot(kind='bar', color='Purple',edgecolor = 'black')\n", + "# Plot formatting\n", + "plt.legend(title = 'Class')\n", + "plt.title('Bar Plot to show distribution of class variable')\n", + "plt.xlabel('Class')\n", + "plt.ylabel('Distirbution')" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "CLASS\n", + "0 1519\n", + "1 1519\n", + "dtype: int64" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Checking propotions of attribute class\n", + "Train.groupby('CLASS').size()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### From above, the entries in the class attribute are equal." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Establishing if there are any missing values in the attributes of the data set. This helps to give an insight on how to handle the missing values, whether to remove rows that have missing values or establishing a method like the mean,median ect to impute the NAs. \n", + "\n", + "
\n", + " \n", + " Good explanation." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "FULL_Charge 0\n", + "FULL_AcidicMolPerc 0\n", + "FULL_AURR980107 0\n", + "FULL_DAYM780201 0\n", + "FULL_GEOR030101 0\n", + "FULL_OOBM850104 0\n", + "NT_EFC195 0\n", + "AS_MeanAmphiMoment 0\n", + "AS_DAYM780201 0\n", + "AS_FUKS010112 0\n", + "CT_RACS820104 0\n", + "CLASS 0\n", + "dtype: int64" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Train.isna().sum()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Correlation between attributes.\n", + "## This is done to establish the relationship between variables and how they may change or may not change each other. The pearson's correlation method is going to be used since it assumes normal distribution on attributes involved. A value of 0 shows no correlation between the attributes, while a correlation of -1 or 1 shows full negative or positive correlation between variables." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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CLASS0.534602-0.598816-0.584111-0.554838-0.260470-0.4532870.2607020.693552-0.4371680.0334320.2676521.000000
\n", + "
" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 \\\n", + "FULL_Charge 1.000000 -0.612996 -0.490977 \n", + "FULL_AcidicMolPerc -0.612996 1.000000 0.794796 \n", + "FULL_AURR980107 -0.490977 0.794796 1.000000 \n", + "FULL_DAYM780201 -0.434603 0.541481 0.548253 \n", + "FULL_GEOR030101 -0.058725 0.115201 0.346139 \n", + "FULL_OOBM850104 -0.283758 0.513344 0.462712 \n", + "NT_EFC195 0.088068 -0.143168 -0.169540 \n", + "AS_MeanAmphiMoment 0.355477 -0.431590 -0.426097 \n", + "AS_DAYM780201 -0.365374 0.449621 0.456260 \n", + "AS_FUKS010112 -0.090570 0.002334 0.032958 \n", + "CT_RACS820104 0.232929 -0.213543 -0.403599 \n", + "CLASS 0.534602 -0.598816 -0.584111 \n", + "\n", + " FULL_DAYM780201 FULL_GEOR030101 FULL_OOBM850104 \\\n", + "FULL_Charge -0.434603 -0.058725 -0.283758 \n", + "FULL_AcidicMolPerc 0.541481 0.115201 0.513344 \n", + "FULL_AURR980107 0.548253 0.346139 0.462712 \n", + "FULL_DAYM780201 1.000000 0.010118 0.334778 \n", + "FULL_GEOR030101 0.010118 1.000000 0.319157 \n", + "FULL_OOBM850104 0.334778 0.319157 1.000000 \n", + "NT_EFC195 -0.090058 -0.230417 -0.230561 \n", + "AS_MeanAmphiMoment -0.408793 -0.160269 -0.336297 \n", + "AS_DAYM780201 0.894191 -0.029085 0.275640 \n", + "AS_FUKS010112 0.055915 0.040480 -0.452769 \n", + "CT_RACS820104 -0.326792 -0.151935 0.155304 \n", + "CLASS -0.554838 -0.260470 -0.453287 \n", + "\n", + " NT_EFC195 AS_MeanAmphiMoment AS_DAYM780201 \\\n", + "FULL_Charge 0.088068 0.355477 -0.365374 \n", + "FULL_AcidicMolPerc -0.143168 -0.431590 0.449621 \n", + "FULL_AURR980107 -0.169540 -0.426097 0.456260 \n", + "FULL_DAYM780201 -0.090058 -0.408793 0.894191 \n", + "FULL_GEOR030101 -0.230417 -0.160269 -0.029085 \n", + "FULL_OOBM850104 -0.230561 -0.336297 0.275640 \n", + "NT_EFC195 1.000000 0.178683 -0.036844 \n", + "AS_MeanAmphiMoment 0.178683 1.000000 -0.322378 \n", + "AS_DAYM780201 -0.036844 -0.322378 1.000000 \n", + "AS_FUKS010112 0.145924 0.025580 0.045562 \n", + "CT_RACS820104 0.080898 0.171524 -0.256060 \n", + "CLASS 0.260702 0.693552 -0.437168 \n", + "\n", + " AS_FUKS010112 CT_RACS820104 CLASS \n", + "FULL_Charge -0.090570 0.232929 0.534602 \n", + "FULL_AcidicMolPerc 0.002334 -0.213543 -0.598816 \n", + "FULL_AURR980107 0.032958 -0.403599 -0.584111 \n", + "FULL_DAYM780201 0.055915 -0.326792 -0.554838 \n", + "FULL_GEOR030101 0.040480 -0.151935 -0.260470 \n", + "FULL_OOBM850104 -0.452769 0.155304 -0.453287 \n", + "NT_EFC195 0.145924 0.080898 0.260702 \n", + "AS_MeanAmphiMoment 0.025580 0.171524 0.693552 \n", + "AS_DAYM780201 0.045562 -0.256060 -0.437168 \n", + "AS_FUKS010112 1.000000 -0.445284 0.033432 \n", + "CT_RACS820104 -0.445284 1.000000 0.267652 \n", + "CLASS 0.033432 0.267652 1.000000 " + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Train.corr(method='pearson')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## From the summary above, AS_DAYM780201 and FULL_DAYM780201 are the strongest positively correlated with a correlation of 0.894191 while FULL_AcidicMolPerc and FULL_Charge are the strongest negatively correlated attributes. This correlation can further be observed by plotting a heat map using seaborn to show the correlation of attributes with each other as shown below" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize= (10,10))\n", + "sns.heatmap(Train.corr(method = 'pearson'), cmap='Purples', robust=True, square=True, annot= True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Using visualisation to understand the data at hand. Histograms, Density plots and Box and whisker plots are some of the plots used to understand the attribute distribution.\n", + "## Histograms were used.\n", + "\n", + "
\n", + " \n", + " ## ??" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Using Histograms" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Train.hist(figsize=(10,10))\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## From the histograms above, we can observe that attributes AS_MeanAmphiMoment, AS_DAYM780201, AS_FUKS010112, FULL_DAYM780201, FULL_GEOR030101, FULL_AURR980107,FULL_CHARGE have a normal. We can also tell from these plots that attribute CT_RACS820104 and FULL_AcidicMolPerc are skewed to the right. We can also tell that attributes NT_EFC195 and CLASS are categorical attributes. This can also be observed using density plots as shown below.\n", + "\n", + "
\n", + " \n", + " ## ??" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Using Density plots\n", + "### With the density plot, we can easily make comparisons between variables in each column because the plot is less cluttered." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Train.plot(kind='density', figsize=(10,10), subplots=True, layout=(4,3), sharex=False)\n", + "plt.show" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Checking for the skewness of the data. Since many machine learning algorithms assume normal distribution,this allows one to know what attributes need to be corrected of skewness to improve the accuracy of the model. Skewness can be observed with bar plots of .skew().\n", + "\n", + "
\n", + " Good explanation.\n", + " \n", + " So what did you findout?" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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tDnxn5v3p3bYlj6mqc4CzgCv2EaAkSdJUpKpWPiB5APAnVfXo7v3DgJtU1RNmjjmxO+b07v03u2POXPS3DgQOBNhrr71ufNppp/X53yIBsPdT379V//6pB91tq/79KfIz13pszfNla54rnufbtiRHV9Wm1Y5bS4vV6cCeM+/3AL633DFJdgAuB/x48R+qqoOralNVbdp1113X8E9LkiRNx1oSqy8C+yS5epKLAQ8Gjlh0zBHAI7rX9wc+Xqs1hUmSJM2ZHVY7oKrOSfJ44MPA9sAbqurEJM8FNlfVEcAhwJuTnExrqXrw1gxakiRpjFZNrACq6gPABxZte9bM618DD+g3NEmSpGmx8rokSVJPTKwkSZJ6sqauQEmS+mJZAc0zW6wkSZJ6YmIlSZLUExMrSZKknjjGSpKkNXBsmNbCFitJkqSemFhJkiT1xMRKkiSpJyZWkiRJPTGxkiRJ6omJlSRJUk9MrCRJknpiYiVJktQTC4RKusgsnChJjYmV5o5f8pKkodgVKEmS1BMTK0mSpJ6YWEmSJPXExEqSJKknJlaSJEk9MbGSJEnqiYmVJElST0ysJEmSemJiJUmS1BMTK0mSpJ6YWEmSJPXExEqSJKknJlaSJEk9MbGSJEnqSapqmH84OQM4bSv9+V2AH22lv721TTX2qcYN0419qnHDdGOfatww3dinGjdMN/apxg1bN/arVdWuqx00WGK1NSXZXFWbho7jwphq7FONG6Yb+1TjhunGPtW4YbqxTzVumG7sU40bxhG7XYGSJEk9MbGSJEnqybwmVgcPHcBFMNXYpxo3TDf2qcYN0419qnHDdGOfatww3dinGjeMIPa5HGMlSZI0hHltsZIkSdpwJlaSJEk9MbGSJEnqyVwlVmkemuRZ3fu9ktxk6LhWk+QFSS4/8/4KSf5pyJhWMxvvvEhyx6FjuLAWzvmpSHLPoWNYiyS7LHr/0CQvT3JgkgwV11okefNatk3FlK/PqUny9aFjWK8kOybZL8mVho5lrhIr4NXAzYH9u/c/A141XDhrdpeq+unCm6r6CXDXAeNZix8l+WiSA+YoyTpk6AAugkcPHcByktx30c/9gIMX3g8d3yo+svAiyTOAhwFHA3cEXjJUUGu07+ybJNsDNx4olj6M9vpM8gdJjkrynSQHJ7nCzL4vDBnbapL8LMnZ3c/PkvwMuObC9qHjW06S1ybZt3t9OeA44E3Al5Lsv+Ivb2U7DPmPbwU3raobJfkStAQlycWGDmoNtk9y8ar6DUCSnYCLDxzTak4CXkpLYv8lyWeAtwLvqapfDRrZCpIcsdwu4IobGct6rXCTC7DTRsayTocBHwJ+SIsV4FLAPYAC3jVQXGsx2yp1X+DWVfWLJG8BjhkophUleRrwdGCnmXMmwG8ZwVT0lUz4+nwN8BzgKNpDzmeS3LOqvgnsOGRga/BG4HLA31bV/wNI8q2quvqgUa3u1lX1593rRwFfr6p7J7kK8EHa99Eg5i2x+l33VFYASXYFzh02pDX5T+BjSf6DFvufAYcOG9KqfldV7wPe1yWC9wAeDLwqyYer6iHDhresWwMPBX6+aHuAsXcb/xT4w4Wb36wk3xkgnrW6OXAQ8EXgtVVVSW5TVY8aOK612CnJfrTW/e2r6hcAVfW7JP83bGhLq6p/Bv45yT9X1dOGjmedpnp9XrqqPtS9flGSo4EPJXkY3ffRWFXVE5LcGHhrkncDr2TkMXd+O/P6jsB/A1TVD4bupZ+3xOrlwOHAlZI8H7g/8IxhQ1pdVf1LkuOBO9BuIM+rqg8PHNZqzjtzuxaqw4DDuibZew8W1eqOAn5ZVZ9cvCPJ1waIZz3eBFwNuEBiBbxlg2NZs6r6Yjc+5gnAx5P8PdO4cQN8ny1dfj9OsltVfT/JFYFzBoxrVVX1tCS7086ZHWa2f2q4qFY11eszSS5XVWcBVNWRXZf3O4Gdhw1tdVV1dJI7AI8HPglcYuCQ1uKnSe4OfBe4JXAAQJIdGLgFf+4KhCa5DnB72hf/x6rqpIFDWlHXwvbhqrrD0LGsR5K/qaoXDR2HpqX7ov83YFNVXWPoeC6s7rq9eFX9cuhYlpPkIFor8leAhda1qqpJTByYkiQPAU6pqqMWbd8LeGZVPWaYyNYvyW7AflX1gaFjWUmSa9MaU64CvLSq3tht/xPgTlX1lMFim6fEKslSTwY/q6rfbXgw69CNK3jYwtOOtr4kVwZ2p7WcfG+p7rUx6loE78xM7LTE/Kcr/qIukiSbgD1prVTfqKqvDhzSqroWnusvjN2ckqlen1PVNUjci/PfV44Ye8PEWM3brMBjgDOArwPf6F5/K8kxXR/yWP0a+HKSQ7qp3C9P8vKhg1pJksslOSjJV5Oc2f2c1G0b7SzBbjruUcAngH8B/hX4ZDej50aDBreKJA+nneO3AS5JGwB+W+Dobt8oTfVcAUjyx0k208aIvQF4LHBIkk8k2XPY6FZ1CuMfOH0+U74+l5Nk7BMG/h54G62X5wu0sZChjbl66pCxrSTJY5Ls071Okv/oZjYe342LHC62OWuxei1w+ML4pCR3oj3dHwa8rKpuOmR8y0nyiKW2V9VoB7An+TDwceDQqvpBt+0qwCOAO1TVKGvOJDkWeGxVfX7R9psB/15VNxgmstV1LRA3Xdw6lTa1+/NVde1hIlvZVM8VgG6G8Z2q6owkVwdeUlX36caM/W1V3WngEJeV5J3ADYCPAee1WlXVXw0W1Cqmen0u01sCLUE5rqr22Mh41iOtZtW+i3t20mbUn1hV+wwT2cqSnEDrsvxd1xX7FOBOwH7As6vq1oPFNmeJ1eaq2rTUtiTHVtUNh4ptNd3Mur2qaswDNM+T5GtV9Xvr3Te0JN9Y7kaR5OSqutZGx7RW3Q3wDxd3GXfdg5tHfAOc5LkCkOT4qrp+93p74ItVdaPu/YlVte+Kf2BAE31gm+T1mTZD9DTOX56juve7V9Voy/4k+SrwJ1V12qLtVwM+Mtbrc/Y7Pa38yeer6mXd+2MWrtMhzNuswB/PNGsCPAj4SXdDHG3ZhST3AF4EXAy4epIbAs8d+SDT05L8Ha0VYqH2yZWBRwJjnvr/wSTvp82wW4hzT+DhtFpLY/Z84JgkH2FL7HvRpho/b7CoVjfVcwVgc5JDaK0+96J1UZHkksD2A8a1qqo6dGoPbEz3+jwFuH1VfXvxjoy7FArAk2jlfr7B+e8r16LNEhyrc9MG2v+ENmHt+TP7nBXYl7TlJ54N3Krb9BngucBZtJvLyUPFtpK0mie3Az5RVft1275cVX8wbGTL67qfnkr7sllYQuD/AUcAL6yqHw8V22qS3IUtAzUDnE4bqDnqWTBw3uf+J5w/9g931fpHaeLnyo7AY4Dr0io7v6Gq/q9LWK60+Cl/TGYf2KpqKg9sk7w+kzwO+ExVHbfEvidU1SsGCGvNkmxHqxM2+5l/sapGWasNIK3Uwr/THnDeuzDzMskfA39XVXcbLLZ5Say6VqmDqupvh45lvZJ8vqpumuRLM4nVeV0QkrReU3xg07gkuXRVLS7WOhppNasuM/tgudCaXFU/GyquuZkV2GXWY575t5ITusF32yfZJ8krgM8NHdSFlWS0FbWTbJ/ksUmel+QWi/aNvpjscpJ8eegYLowxnyurSfLBoWNYxTlLlHAZ9ZP0PF6fmfbi0V8ZOoCVVNU5C0lVNzPwdrTaVoP2Ts1NixVAkhcD+9BK2/9iYXtVjXktsoUM+x9oMxoAPgz8U1X9erioLrwk366qvYaOYylJXk8rVfAF2oK6n6yqv+72DTrgcTVZfsHi0JaK2XUj4+nDmM8VgCw/xT/A+6pqt42MZz1mxoY9Fbgf8FfAjrVlfbXRmfL1uZwJnON/vdwu4B+qatSV45PcFHgIcB9alfvH0bqOBxseMW+J1X8ssbmq6s82PJg1SlvP8GrAyVMq8pi2BM+Su4BrV9UoF5FeNMtrB+DVwC60xaSPWugyGaMkvwP+i6VbHe5fVZfZ4JDWZKrnCpw32+uTnH+214KbVdVoF79e9MAW2gPb88b8wDbV6zMrLx59u6q61EbGsx5Jfk2rF7bUEk1PrqpR1ppLW7bugcC3aQsuH06bHT344tFzlVhNTZJHAy8AvglcHTiwqpa7QEclyf+jDaJe/FQQ4HNVddWNj2p1Sb5aVddZtO1ZtP+WK421ZAGcN2bmEVV1whL7vlNVoyxYOdVzBc6rlXOfqvrGEvtG+5lP1VSvzyQ/YfnFo99eVVfe+KjWJsnngCdU1dFL7BvtOZ7kDOBrwEtprce/TnJKjWCprLkqt5DkErSFGPdlZhHJEbdYPYlWmO2MJNegtUZMIrEC3kdb0f3YxTuSfGLjw1mzzUnuXFtWoqeqnpvke8BrBoxrLZ4EnL3MvvtsZCDrNNVzBeA5LD8W9QkbGMe6pS3D83Rgb86/CPOYJ8VM9fqc6uLRAI8ClpuZu2mZ7WNwFVpr7P7AS5McCeyUZIeqGnSB9LlqsUry38BXaf2tzwX+FDipqp44aGDLWDxmYKpjCCSNT/eF/rfAl5mp4zfmEhHShdE1qtydlmTdCvhYVT1ksHjmLLH6UlXtt9BP39Wg+XBV3W7o2JaS5IdsKWYKbSX6897XiJeegDYLgy21TxYW7vxCjfykykQXHO3GnBxAa526Kltifw9wSI14sfEJnyt/DZxVVYcs2v4E2pTulw4T2eqSfKaqbrX6keMy1esTzit8O6nFo9NWbngacG9gYQLMD2n3lYOmNPYXIMllgcdU1YsHi2Hk97V1SfKFqrpJkk8Bfwn8gHbzHrzPdSlZZsmJBTXupSfuRBtY+g3gu93mPWjVev+yqj4yVGwrSavMvz8tgT2927wHXVJbVQcNFdtqkrwV+ClwKOeP/RHAzlX1oKFiW8lUzxU4b4zVjarqt4u2X5xWQHG03WpJbk871xevFTjaWdJTvT7TFv19DXA5zn+O/5R2jh8zVGyryYTX8lzO0DMx5y2xejTwTuD6wH8AlwaeVVWvHTSwOZTkJOAuVXXqou1XBz5QVb8/SGCryEQXHIXWtVPLr7n39RrvIsyTPFdg5YKaK+0bgyT/CVwHOJEtXYFjnyU9yeszE108Gla9r4x6Lc/lDD3ofq4Gr1fV67uXnwRG2Uo1K8l7WaFgX4176Ykd2PJEOeu7wI4bHMt6nEvrRls8zmQ3RryeZOcnSR4AvLOqzgUWlqJ4ABeccTcmUz1XgNa9s7hLp+vyGbsbjDnxW8ZUr89LLU6qAKrqqCSjLbXQOS3TXctzOYO2GM1VYtU1z9+PC86Cee5QMa3iRUMHcBG8Afhikrdx/oU7HwQcsuxvDW+qC45C6w55IfDqbnp3gMvTmvEfPGRgq1jqXNmTFvOYzxVo9X3en+QpwEJ3zo2Bf2H81+9RSa5bVaOunr3IVK/PqS4eDe2e/VTgk0kWr+X5wMGiWkXaahNLJVABBn3wmbeuwA/RFlw+Gjhv8cghB7GtVdfUvdCV87UxD0RekOS6wD254GKpo76RZ4ILji6W5Iq06/dHQ8eyFkl+n6UX1h31uQKQtijwU4Hr0W7kJ9IG9Y56SZuuC/aawLdoY6xC6woc7bgwmO71mQkuHj1lSfahJVCLW9WuRps4MNiyNvOWWJ1QVdcbOo71SnIb2oDkU2kX5J60QpCfGjCsdUuyyxS+6JPsBZxdVT9NsjetVstJVXXioIGtQZKb0L4cv9gltnemxT7qL3ltvCRXW2r72MstTPn6nKpuJubutOr2v5jZfr6aYmOS5H3A06vq+EXbNwHPrqp7DBPZHC3C3PlckqmNKQB4MXCnqvrjqvojWpXhfxs4phUluUuSbyX5TJL9kpwIfD7J6d1spFFK8lTaGLyjuskOHwLuAhyW5dfMGoUkz6YtMPqaJP8MvJI2QeNpSf5h0OBWkOTOM68vl+T1SY5P8paxj1VK8pGZ108bMpb16hKoywP36H4uP4GkarLX53KSHDx0DCtJ8le00gpPAE5Mcq+Z3S8YJqo12XtxUgVQVZtpw4EGMxctVjN9rTvQFmE+hWk1fR+/OMalto1JNwtmf9qN+33A3bqBmr8P/NdYC512CeAm2kKvpwLX6CrfXwr4/JhbPLvz/IbAxWmlRPYZIaKrAAAeDElEQVSoqrOT7ESLfZTnS2YK36YtsvsD4HXAfYE/rqp7DxnfStLVxuteT6qAb5InAo8BFsor3Ac4uKpeMVxUK5vq9ZlkuYWKAxxXVXtsZDzr0d1Xbl5VP+9aCN8BvLmqXjZ7/o9NkpOr6lrr3bcR5mXw+t2HDuAi2py2Ev2bu/d/ShsnNmbnLhTsS/LLqjoKoKpO6sZIjNX/VdWvkvwW+BVwJkBV/SJZap3dUTmnG2fyyyTfrKqzAbr/njHPmJq1qapu2L3+t6xSy20EpvzkeQBw04WunSQvBP4XGG1ixXSvzzNoMxlng6zu/ZWW/I3x2L6qfg5QVad2Q1Pe0XUlj/lD/2KSx1TV62Y3JjmAgb8/5yWxuhKwy+JxJknuQavaO+rmb+AvgMcBf0U7kT9FK6g4Zj9N8ljgsrQyAE8GDgPuwAUXIh2TY5K8BbgUrXDiod2kh9sBYx9I/dskl6yqX9JmpgHnVU4ec2J1pa4bJ8Blk6S2NJWPOQkHuEaSI2ixL7w+z8hLooSZSTzd6zF/UcJ0r89TgNtX1bcX70gy9pIFP0hyw+rW8uxaru5Om8075qE1TwIOTzLbELEJuBgDr506L12BnwAeuUQBwmvRmr5HuaTNlCXZE3gG7ansObRuwQNoSezf1EiXn0hbFuYBtLjfQZt99BDg28CrZgdujk2Si1fVb5bYvguwW1V9eYCwVtWNDZv16q575yrAv1TVw4eIay2S/PFK+2uJRXfHoktmHwEc3m26N/DGGvcyPJO8PpM8DvhMVR23xL4njLz7dQ9aa/gPlth3y6r67ABhrVmS29Jm7EIrIvvxIeOB+UmsVqqOfNxYq94mucDAu1ljHTOj4STTXHNvqpJcdqHLdYl9ey3VQjEmSW5EW5Q2wKeq6ksDh6QRWmYm5ler6oRBA5uoeekK3GmFfWOuensu7cvxLcB7aWMKJqN7UrgfrTzEObS14F5XVd8cNLAVJDmGNpj3rWOOcylZYc29JKNdc68b2Pt4WhJ4CPB04ObAScALqmrMVeM/ASwMvP9YVc3OeH33wr4xWTSQ+tTu57x9VfXjjY5prSZ+fU5y8ehuJuZjgd8keRHwN8BngX9MckhVvWTQACdoXhKrjyZ5PvCM2Sf3JP9Iq0o9SlV1w+5i3J+WXH2l+9+PVNU5gwa3iiQH0YqzfQy4Cq0I4Tdpgx5fUFX/PWR8K7gCbSbjkUl+ALwVeHtVfW/YsNbkZbRFUU+d3ZhuzT1grGvu/SfwZdq4sId2r18I3BF4I+3LaKxmxyQtnvk11vFKP6IVp1y4hyweUD3m5b4meX3m/ItHf6HbvAfw1iSjXTy68zDguiwzExMwsVqneekKvBTweloXybHd5hsAm4FHL8x4GLskDwJeBbywqv516HhWMtv92o2L+GRV3TLJFYBPj3ha9OzU/1vTbob3pbWevLWqRltzJm2Zj99fnHSnVe3/ypDTi1eS5NjuISLA6VW1++J9A4a3okXny/nKLYy1/EKSlwG3obU6vJU29mcSN/qpXp+Z6OLRsKW0T5Ltge8DV6kta5FOsuj20Oaixaob0Lh/kmsA+3abT6yqU2aPS7Jvjax6b5LdaWum3Ye2kO6T2TLYdMzOnelWuCqwPUBV/SQjnxe9oKo+DXw6yRNorScPAkZ54+5Mdc297bqE+zLApZPs3U3rviJtBs+Yzc5oXHhN937X4cJaXlU9sbsGb0NrjXhFWqHT11TVtwYNbh0mdn1OdfFoWH4m5u0Z90zM0ZqLFqu1GtsTZpJP0r5sDqPNgDnf2IeRj4V4EG0h2q8B1wH+oqren2RX4GVV9ZBBA1xG1yw/5gWLV5QJrrmXZH9gYSbaX9LKixSt++Efx9oKAUvOaDyfqvrHjYrlwkhyeVri/Tza8h+vW+VXBjXV6zNtdYFX0sY/XmDx6BrpsjCw5EzMm9JaCkc9E3PMtrXEalRVZJOcypYChLP/RyxUjB/zWIiFQbLXAE6uqp8OHc+2bOzTortuhlTVOd2N/IbAd6vq+wOH1oskT6uqfx46DjhvaMS9aC08u9IGg7+9qsZeT2nSMtHFoxdLsiOtfMF3q+qHQ8czRdtaYjWqFqt5lOT3aHWsHjN0LEvJKuuNjXkGTJecPJB24/5QVZ3QFfJ7OrDTmB4aZnVT/pdVVcdsVCxby5juLUl+QWs5eStwMouqx1fVu5b6vTGY6vWZ5JLA7xbGWHX3wbsCp1bVqId2JHkt8IqqOjGt2PD/0orJ7ky7l7910AAnaC7GWE1dkvsAH6+qs7r3lwduU1XvHjay5SW5PvAi2riCd9OWyXg1rRn5xQOGtpoX0SY4fJAt60lOxSG0MVVfAF6e5DRa2YKnjvlcoU0iOZG27AdccJbaPBTwHdN59N+0z/U63c+sYsvagWM01evzQ7QCyd9IK0z9v8B/AXdPcpOqGvMC3reuqj/vXj8K+HpV3TutgO8HaQm61mHuE6skV52ZqvvbQYNZ3rNnn2q6Im3PpiUsY/U64DW0G8idgWNopSL+tKp+PWRgq7gRbczJ3WjLILwV+NhEZk1tAq5fVecmuQRtWv21lqqYPDJPodU7+xVtOvrhU5mpuw6jOX+q6pFDx3ARTPX6vEJVfaN7/QjaDMYndLMCjwbGnFjNfi/ekZaYU1U/mMg8pNGZ+67AJN+uqr2GjmMlC9NdF21btpr8GCyeJp+2HtbeUxpPkOQWtEGadwD+vqqOWOVXBjWV6f7L6ept7U8b/3MarTjosSv/1jSMafxmkodW1X8u16021u60xaZ0fc7ew5N8FvjXhVbkjHj1D4AkR9J6Gb4LHAlcp0uqdgBOqKrFrZ5axdy3WDGNpuTNSV5Cq2FVwBMYeHXuNbhEkv3Y8vn+HLj+QqmFsY+b6WYv7kdbZPR0YAqDNK+TLcsgBbhm935hssOol0Cqqm8leQ9tpYSHAddmS925UUry+Kp65RoOHVNB3IXVJi4zaBQXwQSvz+PTqpZ/lzYT8CNw3rCOsXss8HJaoecnzbSA3x54/2BRTZgtViPQzeJ5Ju3JLLSL8p/GPM21e8pZTtVIF75O8ijabKlL0KYWHzaVmS9JrrbS/qpaXENnFLr6cg+mtVR9h9Yd+L6RdxkD02sVnLqpXp9JdgKeSKtb9YbqFmPuWt2uWVVvHjI+bay5SKySvIKlxzgEeERVXXaDQ9JIJTmXtqTKwuK5i2dM3XPDg1qnrkttX1rsJy0uhDs23Wd+PPAe4Gwu+JmPtmtqyolV1+rzGGBvZnonqurPhoppNVO9PpPcsar+Z5l9L6yqv9/omNYqyb8Ap1TVaxdtfzKtCvtoYx+reekK3Hwh9w0qyUur6klJ3ssSieFYbyIrSXJH4O+q6o5Dx7KM2w4dwIWV5LK0pZs20brQAtwgydHAAVV19pDxreC5bDm/Lz1kIBfC9ZMs9bkudL+O+aHtPcCngY/Sps9PwVSvz1cleXJVndd11tW1egOti23M7k6rW7XYy2gPRCZW6zQXiVVVHbrcvq7fe6wWmofHHOOSktwOeC1byi28AHgT7Qvn+QOGtpqbAi+e0iD7GS+nLTHx4Nqylldo3civBB4+YGzLqqrnDB3DRfDlsQxKvxAuOcHWhqlen3cCPpTk4lX1rm7W7jtoLbT3GDa0VdXC/WTRxnOnsjzZ2Gw3dAAb4IFDB7Ccqjq6+99PLvUzdHyreDFwIHBF2g3kKODNVXXjMRcgBK4GHJ3klkMHciHcsqqeM3sTrOa5tHpWo5TkEkkekeSeaf4uyfuSvCzJLkPHN8fel+SuQwexTpO8PqvqVNoY2ecl+XPamntfr6qH1KKFmUfol0kusEh0t+1XA8QzeXMxxmolSb5TVXsOHcdSknyZFerfjHmW1xJT/79ZVdccMqa16iqBvwL4Kq0W12yiMtrZjElOrqprLbPvG1V1gZvjGCQ5DPgdbbbaFYATgPcCtwJuWFV3HzC8FSV5elW9YOg41iPJz2j3ldA+89/SPn8Yf/flJK/PmdUFdqO13P8PbS1VYLxxAyS5C+3z/ie2zEbfRKu99aSq+sBQsU3VXCRWaWvWLbkLOK6q9tjIeNZqZpbX47r/Xega/FPgl11LxCglOQX4m5lNL5p9P/JWK5LcBngnbaDsees1jnU2I0CSQ4FvAs+bLZiY5JnAtavqYYMFt4IkJ1TV9bq6OKdX1VVm9o29xs+zWf7hp6rqeRsZz7ZiatfnVGdJL0hyPeBv2TLW6kRaLa4vDxfVdM1LYvUttjyhLVY1/sWMP1tVt1xt25gk+Y8VdtdYZx4luRKtG/MawF8uTIuegm7w+iG06tTH0s75/YAvAY+ukS6EPdu6ObUip0messTmSwKPBq5YVaMejJ/kvrSWwQI+XeNe+mjS1+e86caJ3aOqxlSjbRLmIrGauiTHAo+vqs90728BvLpmKpurH11L20HA62qiJ3+SawLXpT1InFhV3xw4pBUl+SGtdlVoNYretrALeGBVXXmo2NYjyWVotYoOAA6jDbIebY2lJK+mFatcWOvtQcA3q+pxy//WsKZ6fXYJ7KyiLTl1bFX9bICQLpS0hd7vRKt4/ye0ZPz+w0Y1PXORWM30by8o4EdV9Z0h4lmvJDemTcu9XLfpp8CfjbxffvFyGQs3ks9U1bcGCGlNkuxaVWcssX1P2my7fx0grDVZWKqke33LqvrszL61VgjfcEkesdL+lWb1jkE31OCvaV30hwIvq6qfDBvV6pKcCFxvIUHppv9/uar2HTay5U31+lymBX9n4Pq0Uigf3+CQ1iXJHwEPoa3R+AXglsA1quqXgwY2UfOSWC3Vv70zcDFg/5rIemRdV0+q6qyhY1lNN/ZksZ1pTznPqaq3LbF/VLoZaQ+gPZ3tTlsc+G9W/q3hTLlLbUGSS9O6ike7qsCsJP8K3Bc4GHhVTWjx6CTvAp5cXUX+bkznQVW1/7CRrc3Urs+ldJ/5YVV106FjWU6S02kFWV8DvLuqfpbkW1V19YFDm6x5qWO1ZFG5JJtotX/+aGMjWpsss1jqQumQGnFF6qr6x6W2d0/3H2VLd8+odN0596E9nV0bOJz2ZDbKCQ6LZJnXS70flSR/QZtldKnu/c+BF1bVqwcNbHVPAX4DPAP4h5myPlMoEHpF4KQkX+je/yHwv0mOgHEWIJ749XkBVXVakh2HjmMV7wTuTesq/r+09Tyn3+IyoLlIrJZTVZu7J+SxmvxiqYtV1Y9HXlTuh7Sm7mfQui0ryX0GjmmtapnXS70fjSTPAG4B3Ka65XfS1g98WZKdq+qfBg1wBVU15Vp/zxo6gAthytfnBST5PVpiPlpV9cQkT6JVvd8f+FfgskkeCHxgSq20YzEXXYHLSXJl2olx46Fj2VakVWR/xlinF6etf/VgWlL7FuDtwP+MfeYoQJJfAifTWkuu2b2me3+NqrrUcr87pCRfA25QixZdTlu49riquvYwkW0buiEGs2sF/njAcFY01eszSy9LtjOtrtVDq+p/Nz6qC6drYbszLcm6U1VZxHed5iKxytKLMO9Me0p+YlW9d+OjWruuPtETF6bLJ7kCbcbRKEsWwLLFTXcGvkdb+PqkjY9q7boWk/1pN/F9gGfTxnB8fdDAVjBT92xJC2NpxibJ16rq95bZ99Wqus5Gx7QtSHIg8Dxa9exz2dJ9OeokBaZ3fSb540WbCjgT+EZV/XaAkHqR5I+q6lNDxzE185JYLZ51tHBSf3HM06EXJPlSLVqPbKltY7LEl3wBZ05lUPKsJH9AG9PxwJpI9fgpSfIx4AVV9bFF228HPHO5MZK6aJJ8A7h5Vf1o6Fguiilcn0luVlVHDR3HhdGVWHggbYLAh6rqhCR3B54O7DTm76GxmpfEaq+q+vbQcVxYSY6jjT/5Sfd+Z+CTVfUHw0a2PkkuRRsE+ZCqutvQ8awkyeVpT8LQ1vSawkzMA4CdF6acJ/kubXxegL+rqtcMGd9ykuwLvAf4DG3JjKINpL4lcK+qOnHA8OZWkg8B953ilPmpXZ+LZuz+b1WNdu3OxZK8EdiTNrbtpsBptLVHnzr2grJjNS+D199Nq0ZNkndW1f0Gjme9Xgx8Lsk7aF86DwQmsT5ZkosBd6U9Ud6ZNsPktYMGtYIu3oNpCeC3aEnJ1ZIcDvz5yJvt/5z2GS/4YVXt3lVI/ghtuvToVNWJaUtmPATYl/aZfwp47OJxV+rV02j3lc8zM4C6qv5quJBWNuHrc3bCziUGi+LC2QRcv6rO7e4lPwKuVVU/GDiuyZqXxGr2pB79+IHFqupNSTYDt6P9t9y3qr4ycFgrSnJHtlTnPZK2zuFNqupRgwa2umcAOwJ7LlRE7qZ4vwp4ZvczVttV1Zkz7/8boKp+3Q0EH60uxiNps74KOMmkaqv7d+DjtPX2zl3l2LGY6vW5XTc2druZ1+d9L415wgDw26o6F867Tr9uUnXRzEtX4LKFE6em6067D62w6Wi705KcC3waeGR1ldaTnDL2gbFJTqAlgL9ctP3SwFFVdb2lf3N4SU6uqmstsX074OSxfvbdrLTXAzemrXG4HXADWrfgAVV19oDhza0kn6uqWwwdx3pM9fpMcipbJggsNuoJAzOzjeH8M44XJjtcf6jYpmpeWqxukORs2omwU/caplHEb3LdaZ0b02bsfDRtfa+3AdsPG9KanLvUmJOq+nmSsT9lfCTJP1XVMxZtfy6tK3CsXg58hbYkybkAXa2zZwKvBB4+YGzz7MhuZuB7OX9X4JhbTyZ5fVbV3ms5Lsm+IxxT+PtDBzBv5qLFaqqW6E57O/CKtV6kY5HklrT/jvvRWiQOr6qDh41qaQsTBVj6yfLIqrrBxka0dl1r5utpA7+P6zbfANgMPHqshfySfKOq9lnvPl00SZZas3PsrSeTvT7XYso9KlMblD8kE6sBTbU7bTldl9QdaS0Tj+q2jeoJbcpN9gu6Gj8LC+l+paq+uWj/2D7zJbswu30mVhsoycVGPAB8Lq7PlYy9jM5Kphz7RpuXrsCpmmp32pK6bp4Pdz8L3kw3Y3MMJt5kD0C1ZWFOWeGQUX3mwGeTPAt4Xs08ySV5JjDJ2j9T0nW73pY21OAewJWHjWh583B9rmLKLRlTjn1DTXkdrMmrqi9V1d93Re+eA+wHXCzJB7uxEfNgzOsGruTNQwdwEYztM38C8AfAyUnemeQdSb5J68Z8/LChza8kN03yMlpdoiNorePzUuV+yten5pyJ1UhU1Wer6vG06rcvpRVoA84rsDhVU33KGVtysh6j+syr6uyqegBwJ+CNwJtoa5Ddf7bw48TP89FI8vyu6voLaKUW9gPOqKpDF4oQz4GpXp+j7YZdg6l+5hvOrsCRmUJ32jZiVMnJPOjGgn1zhUM8z/txIPA1WsHY93W1iebtfB7Vf0+3xNdPFx4UktyWVuT0NOCVC+Paqupmw0W5tCQfqao7reHQh231YOaELVbTMKknhSRXnXk75Se0yZiTz3xS5/mIXQV4PnBPWvfrm2llaHyQ3noOAy4FkOSGtOK936Z1d796wLjWYte1HFRVJ2ztQOaFF9o0jOrpbA2OAvaCcT6hLSfJVavqe93bqSUnk/zMF5naeT5KVfV/wAeBD3ZLlNwduCTw3SQfq6qHDBpgP8Z2fe40c+94KPCGqnpxN1P62AHjWovLJbnvcjur6l0bGcw8MLHS1jDVlocpJydT/cy1FXXLBr0DeEe3NMyyX6BjMOEutdnr73a0dRrp1t8b+7V5OVryvWSJC8DEap1MrEZq4q0nU215GPsNcCWT/Mwnfp6PWpKL04r27s107vWH0Zb0OmumS+2f2dKl9ugBY1vJx5McBnwfuAJtjUaS7AaMfU3M06rqz4YOYp5M5WLbFo269STJK1j6yzzA5Tc4nL6MOjmZ08981Of5xL0HOIu2JuNvVjl2LKbapfYk4EHAbsCtqup33fZ9gJ0Hi2ptfi/JLavqs7Mbk9wa+N7iAsRanYnVeI299WTzhdw3qIknJ5P8zFcx9vN8yvaoqjsPHcQ6TbJLrSt8+zZog9eTPBF4IPAtWvmcMfs88LMltv+KFvs9Njac6TOxGq9Rt55U1aHL7Uvyoo2MZZ0mm5xM+DNfyajP84n7XJI/qKovDx3IOkyySy3JtWmraOwPnElb9zVVddtBA1ubK1XV8Ys3VtXmJHtvfDjTZ2I1oIm3nqzkgcDfDB3EUuY0OYERf+ZzfJ6P3a2AR3aLMf+G9nlXVV1/2LBWNNUuta/SKtvfo6pOBkjy5GFDWrNLrLBvpw2LYo6YWA1rsq0nqxhtk/0qRpucrMGYP/N5Pc/H7i5DB7BeE+5Sux+txerIJB+i/TeM+Zqc9cUkj6mq181uTHIAbXye1snEakBTbj1JstzTY5jODWWxUcc91c98yuf5lFXVaQBJrsTKrRKjMdUutao6HDg8yaVo5SGeDFw5yWuAw6vqI4MGuLIn0WL/U7YkUpuAi9FmaGqdMrPYvEYkyberaq+h41hO171QLFP7pKquscEhrckqyclxVbXHRsazHlP9zFcy9vN8ypLcE3gxcFXgh8DVgJOqarRrMiY5l9aldsBMl9opEz23dwYeADyoqm43dDyr6WqGXa97e2JVfXzIeKbMxGqkknynqvYcOo55M4/JyZR5nm89SY6jzaz7aFXt131x7l9VBw4c2rKS3IfWYnULYKFL7fVVdfVBA5PWwa7AAU21awcgyeLFcgv4UVV9Z4h41mrKN+ipfuZTPs8n7ndVdWaS7ZJsV1VHJnnh0EGtZOJdahJgi9Wgptx6kuTIJTbvTOuX37+qRlnMb6rJCUz6M5/seT5lST5KS04OAq5I6w78w6q6xaCBrdPUutQkEyv1Kskm4CVV9UdDx7KUqSYnKxn7Z65hdK0+vwK2A/6Utibcf1XVmYMGJs05E6sBTbn1ZCVJjqmqxf9tozb15GTMn/m8nudT0C1qvE9VfTTJJYHtq2qpKtuSeuIYq2G9eIltOyeZcuvJlZlgNe2uyvClh47jwpjAZz535/kUJHkMcCCtRfaawO7Aa4HbDxmXNO9MrAa0XG2WrvXk5cBoW0+Wqaa9M202zxM3PqKLZgLJyWQ/8ymf5xP3OOAmtLXgqKpvdDWtJG1FJlYjNJHWk8UVs4tW0O+vq+qHA8SzJlNNTjqT/MyXM5HzfMp+U1W/XVi7OMkOjPzhQZoHJlYjNIXWE+DIqvr20EFcCFNOTqb6mS9pIuf5lH0yydOBnZLcEfhL4L0DxyTNPQevD2i11pOqGu1NcHawdJJ3VtX9ho5pLZLsNdXkZMKf+WTP8ylLsh1wAHAnWqmLD9OKbXrTl7YiW6yGNeXWk9maRFOqQ/RuYHLJSWeqn/mUz/PJqqpzgdd1P5I2iInVsKbctVPLvB67qSYnMN3PfMrn+eQkOX6l/VV1/Y2KRdoWmVgNa8qtJzdIcjYtUdmpe033vqrqssOFtqKpJicw3c98yuf5FJ1LO7ffQhtT9athw5G2LSZWw5ps60lVbT90DBfSVJOTKX/mkz3Pp6iqbpjkOsD+tOTqK93/fqSqzhk0OGkbsN3QAWzjptx6MklVtX1VXbaqLlNVO3SvF96PNqmaOM/zDVZVX62qZ3eTHd4LvIm2oLGkrcxZgQNK8n/AL+haT4BfLuxi5K0n0lp5nm+8JLsDDwbuA/wEOAw4vKp+Pmhg0jbAxEqS5kiSTwKXoSVT7wB+PLu/qn681O9J6oeJlSTNkSSnsqXLdfYGv9BC6Dg3aSsysZKkbVCSfavqxKHjkOaNg9cladv05qEDkOaRiZUkbZuy+iGS1svESpK2TY4DkbYCEytJkqSemFhJ0rbpt0MHIM0jZwVK0hxJcjXgp1V1Vvf+tsC9gdOAV1aVCZW0FdliJUnz5TDgUgBJbgj8N/Bt4AbAqweMS9omuAizJM2Xnarqe93rhwJvqKoXJ9kOOHbAuKRtgi1WkjRfZsso3A74GEBVnYslFqStzhYrSZovH09yGPB94ArAxwGS7Ab8esjApG2BiZUkzZcnAQ8CdgNuVVW/67bvA+w8WFTSNsJZgZI0p7rB6w8BHgh8C3hXVb1i2Kik+WaLlSTNkSTXBh4M7A+cCbyd9hB920EDk7YRtlhJ0hxJci7waeCAqjq523ZKVV1j2MikbYOzAiVpvtwP+AFwZJLXJbk9zgaUNowtVpI0h5JcilZxfX9a2YVDgcOr6iODBibNORMrSZpzSXYGHgA8qKpuN3Q80jwzsZIkSeqJY6wkSZJ6YmIlSZLUExMrSZKknphYSZIk9cTESpIkqSf/Hz7mtBsVh+qCAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Train.skew().plot(kind='bar', figsize=(10,6))" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "NT_EFC195\n", + "0 2769\n", + "1 269\n", + "dtype: int64" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# From above, attribute NT_EFC195 shows that its, skewed.\n", + "Train.groupby('NT_EFC195').size()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Separating the train data set into output and input components" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "A = Train.values\n", + "X = A[:, 0:11]\n", + "Y = A[:,11]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Spot checking classification algorithms since its a classification problem at hand.\n", + "### This is done to know which algorithm is best suited for the problem at hand. Two linear machine learning algorithms(Logistic regression and Linear discriminant analysis) and four non-linear machine learning algorithm were used(k-nearest neighbors, naive bayes, support vector machines and classific regression tress. \n", + "\n", + "
\n", + " \n", + " ## Less than 10 algorithms!!!" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('LR', 0.8342865299822478)\n", + "('LDA', 0.8377162908048379)\n", + "('KNN', 0.8690586462107053)\n", + "('CART', 1.0)\n", + "('NB', 0.8407203694376205)\n", + "('SVM', 0.8187103751493263)\n" + ] + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "from pandas import read_csv\n", + "from matplotlib import pyplot\n", + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "from sklearn.neighbors import KNeighborsClassifier\n", + "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", + "from sklearn.naive_bayes import GaussianNB\n", + "from sklearn.svm import SVC\n", + "from sklearn.metrics import matthews_corrcoef\n", + "\n", + "#split the dataset \n", + "#A = Train.values\n", + "# Separating A into output and input components\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "# prepare models and add them to a list\n", + "models = []\n", + "models.append(('LR', LogisticRegression()))\n", + "models.append(('LDA', LinearDiscriminantAnalysis()))\n", + "models.append(('KNN', KNeighborsClassifier()))\n", + "models.append(('CART', DecisionTreeClassifier()))\n", + "models.append(('NB', GaussianNB()))\n", + "models.append(('SVM', SVC()))\n", + "#print(models)\n", + "\n", + "# evaluate each model in turn\n", + "results = []\n", + "names = []\n", + "scoring = 'accuracy'\n", + "\n", + "for name, model in models:\n", + " kfold = KFold(n_splits=20, random_state=7)\n", + " cv_results = cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\n", + " results.append(cv_results)\n", + " names.append(name)\n", + " model.fit(X, Y)\n", + "\n", + " Prediction = model.predict(X)\n", + " msg = (name, matthews_corrcoef(Y, Prediction))\n", + " print(msg)\n", + "\n", + "# boxplot algorithm comparison\n", + "fig = pyplot.figure()\n", + "fig.suptitle('Algorithm Comparison')\n", + "ax = fig.add_subplot(111)\n", + "pyplot.boxplot(results)\n", + "ax.set_xticklabels(names)\n", + "pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### From these results, it would suggest that both DecisionTreeClassifier, KNeighborsClassifier and GaussianNB are worthy of further study on this problem." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Data Preparation.\n", + "### This is important because this finds a way to best expose the structure of the problem to machine learning algorithim intended to be used. Since the data has attributes of varying scales, its important to use one of the methods for data preparation like rescaling, standardization, normalization or binarization for better prediction. Here, rescaling is used to have all the attribute on the same scale." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[0.457 0. 0.348 0.545 0.33 0.483 0. 0.005 0.508 0.415 0.182]\n", + " [0.435 0.116 0.322 0.489 0.276 0.458 1. 0.011 0.421 0.586 0.475]\n", + " [0.467 0.116 0.246 0.523 0.288 0.565 0. 0.011 0.442 0.273 0.666]\n", + " [0.457 0.089 0.275 0.399 0.403 0.647 0. 0.011 0.405 0.153 0.424]\n", + " [0.511 0.183 0.323 0.373 0.342 0.595 0. 0.011 0.5 0.196 0.536]]\n" + ] + } + ], + "source": [ + "from numpy import set_printoptions\n", + "from sklearn.preprocessing import MinMaxScaler\n", + "\n", + "A = Train.values\n", + "# Separating A into output and input components\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "scaler = MinMaxScaler(feature_range= (0,1))\n", + "rescaledX = scaler.fit_transform(X)\n", + "\n", + "# Summary of the transformed data\n", + "set_printoptions(precision = 3) # This sets the number of floating point output after rescaling the data\n", + "print(rescaledX[0:5, :]) # This is used as check to confirm that the data has been rescaled" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Standardization\n", + "### It is a useful technique to transform attributes with a Gaussian distribution and differing means and standard deviations to a standard Gaussian distribution with a mean of 0 and a standard deviation of 1" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[ 7.697e-01 -1.123e+00 -1.900e-01 1.376e-01 -6.067e-01 -7.206e-01\n", + " -3.117e-01 -1.331e+00 -2.257e-02 -3.610e-01 -9.251e-01]\n", + " [ 5.079e-01 -4.109e-01 -3.763e-01 -2.432e-01 -1.181e+00 -9.245e-01\n", + " 3.208e+00 -1.303e+00 -5.924e-01 9.021e-01 1.037e+00]\n", + " [ 9.006e-01 -4.109e-01 -9.163e-01 -8.651e-03 -1.054e+00 -4.632e-02\n", + " -3.117e-01 -1.304e+00 -4.590e-01 -1.409e+00 2.318e+00]\n", + " [ 7.697e-01 -5.741e-01 -7.115e-01 -8.701e-01 1.594e-01 6.274e-01\n", + " -3.117e-01 -1.302e+00 -7.015e-01 -2.300e+00 6.989e-01]\n", + " [ 1.424e+00 2.041e-03 -3.670e-01 -1.050e+00 -4.790e-01 2.003e-01\n", + " -3.117e-01 -1.302e+00 -7.713e-02 -1.977e+00 1.447e+00]]\n" + ] + } + ], + "source": [ + "from numpy import set_printoptions\n", + "from sklearn.preprocessing import StandardScaler\n", + "B= Train.values\n", + "#Separating the array into intput and output components\n", + "X = B[:, 0:11]\n", + "Y = B[:, 11]\n", + "scaler2 = StandardScaler()\n", + "standardizedX = scaler2.fit_transform(X)\n", + "# A portion of the transformed data\n", + "set_printoptions(precision = 3) # This sets the number of floating point output after rescaling the data\n", + "print(standardizedX[0:5,:]) # This is used as check to confirm that the data has been rescaled" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Feature selection\n", + "### Statistical tests can be used to select those features that have the strongest relationship with the output variable. Feature selection is done on non transformed data using select k best using he univariate statistic F was used since it can work best with data containg negative values as opposed to chi2 that doesnt take in negative values." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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featuresscorespvalue
7AS_MeanAmphiMoment2813.8681780.000000e+00
1FULL_AcidicMolPerc1697.2495654.220004e-295
2FULL_AURR9801071572.2806771.887905e-277
3FULL_DAYM7802011350.3007436.997934e-245
0FULL_Charge1214.9028383.404241e-224
5FULL_OOBM850104785.1247987.441087e-154
8AS_DAYM780201717.3174084.911002e-142
10CT_RACS820104234.2741975.329249e-51
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" + ], + "text/plain": [ + " features scores pvalue\n", + "7 AS_MeanAmphiMoment 2813.868178 0.000000e+00\n", + "1 FULL_AcidicMolPerc 1697.249565 4.220004e-295\n", + "2 FULL_AURR980107 1572.280677 1.887905e-277\n", + "3 FULL_DAYM780201 1350.300743 6.997934e-245\n", + "0 FULL_Charge 1214.902838 3.404241e-224\n", + "5 FULL_OOBM850104 785.124798 7.441087e-154\n", + "8 AS_DAYM780201 717.317408 4.911002e-142\n", + "10 CT_RACS820104 234.274197 5.329249e-51" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sklearn.feature_selection import SelectKBest, f_classif\n", + "from numpy import set_printoptions\n", + "\n", + "#Feature Extraction\n", + "bestfeat = SelectKBest(score_func=f_classif, k=8)\n", + "fit = bestfeat.fit(X,Y)\n", + "\n", + "set_printoptions(precision=3) # This sets the number of floating point output after rescaling the data\n", + "selected_features = fit.transform(X)\n", + "\n", + "scores = pd.DataFrame(fit.scores_)\n", + "pvalues = pd.DataFrame(fit.pvalues_)\n", + "columns = pd.DataFrame(Train.columns[0:11])\n", + "\n", + "selected_features = pd.concat([columns,scores, pvalues,], axis=1)\n", + "selected_features.columns = ['features', 'scores', 'pvalue']\n", + "selected_features.nlargest(8, \"scores\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### SelectKBest using the f statistic, gives scores to each attribute and takes the specified number of attributes with the highest scores. Attributes AS_MeanAmphiMoment, FULL_AcidicMolPerc, FULL_AURR980107, FULL_DAYM780201, FULL_Charge, FULL_OOBM850104, AS_DAYM780201 and CT_RACS820104 were the selected features." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Chi2 statistical test was used to since there were no negative values in the attributes after rescaling with the minmax scaler." + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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featuresscorespvalue
7AS_MeanAmphiMoment244.2277284.708742e-55
6NT_EFC195188.1970267.868482e-43
1FULL_AcidicMolPerc157.6175133.751602e-36
2FULL_AURR98010754.2314481.782118e-13
3FULL_DAYM78020137.3117801.006747e-09
8AS_DAYM78020126.1562243.148806e-07
5FULL_OOBM85010416.2314335.605627e-05
0FULL_Charge15.2452499.441397e-05
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" + ], + "text/plain": [ + " features scores pvalue\n", + "7 AS_MeanAmphiMoment 244.227728 4.708742e-55\n", + "6 NT_EFC195 188.197026 7.868482e-43\n", + "1 FULL_AcidicMolPerc 157.617513 3.751602e-36\n", + "2 FULL_AURR980107 54.231448 1.782118e-13\n", + "3 FULL_DAYM780201 37.311780 1.006747e-09\n", + "8 AS_DAYM780201 26.156224 3.148806e-07\n", + "5 FULL_OOBM850104 16.231433 5.605627e-05\n", + "0 FULL_Charge 15.245249 9.441397e-05" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sklearn.feature_selection import SelectKBest\n", + "from sklearn.feature_selection import chi2\n", + "\n", + "#Feature Extraction\n", + "test = SelectKBest(score_func=chi2, k=8)\n", + "fit = test.fit(rescaledX,Y)\n", + "\n", + "# Summary of scores \n", + "set_printoptions(precision=3) # This sets the number of floating point output after rescaling the data\n", + "#print(fit.scores_)\n", + "selected_features1 = fit.transform(rescaledX)\n", + "\n", + "scores = pd.DataFrame(fit.scores_)\n", + "pvalues = pd.DataFrame(fit.pvalues_)\n", + "columns = pd.DataFrame(Train.columns[0:11])\n", + "\n", + "selected_features1 = pd.concat([columns,scores, pvalues,], axis=1)\n", + "selected_features1.columns = ['features', 'scores', 'pvalue']\n", + "selected_features1.nlargest(8, \"scores\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Feature selection using the recursive feature selection method with LG" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'rescaledX2' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mmodel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mLogisticRegression\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mrfe\u001b[0m\u001b[0;34m=\u001b[0m \u001b[0mRFE\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0mfit\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrfe\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrescaledX2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 6\u001b[0m \u001b[0mselectedfeaturesRFE\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrescaledX2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msupport_\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'rescaledX2' is not defined" + ] + } + ], + "source": [ + "from sklearn.feature_selection import RFE\n", + "from sklearn.linear_model import LogisticRegression\n", + "model = LogisticRegression()\n", + "rfe= RFE(model,5)\n", + "fit = rfe.fit(rescaledX2, Y)\n", + "selectedfeaturesRFE = rescaledX2[:, fit.support_]\n", + "\n", + "print(\"Num_Feature:\", fit.n_features_)\n", + "print(\"Selected Features:\", fit.support_)\n", + "print(\"Feature Ranking:\", fit.ranking_)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Evaluating Machine learning Alogorithms\n", + "## K-fold Cross Validation\n", + "### Cross validation is an approach that you can use to estimate the performance of a machine learning algorithm with less variance than a single train-test set split. It works by splitting the dataset into k-parts (e.g. k = 5 or k = 10). Each split of the data is called a fold. The algorithm is trained on k1 folds with one held back and tested on the held back fold. This is repeated so that each fold of the dataset is given a chance to be the held back test set. The choice of k must allow the size of each test partition to be large enough to be a reasonable sample of the problem, whilst allowing enough repetitions of the train-test evaluation of the algorithm to provide a fair estimate of the algorithms performance on unseen data. For modest sized datasets in the thousands or tens of thousands of records, k values of 3, 5 and 10 are common. In the example below we use 10-fold cross validation." + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'selected_features_train' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mkfold\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mKFold\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn_splits\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnum_folds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrandom_state\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mseed\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mmodel11\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mLogisticRegression\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mmodel11\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mselected_features_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcross_val_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel11\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mselected_features\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcv\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkfold\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'selected_features_train' is not defined" + ] + } + ], + "source": [ + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "num_folds = 10\n", + "seed = 11\n", + "kfold = KFold(n_splits=num_folds, random_state=seed)\n", + "model11 = LogisticRegression()\n", + "model11.fit(selected_features_train, Y_train)\n", + "\n", + "results = cross_val_score(model11, selected_features, Y, cv=kfold)\n", + "Prediction = model11.predict(selected_features_train)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (results.mean()*100.0))\n", + "#Assigning the preditions of the model to variable AssignmentOutPut\n", + "AssignmentOutPut11 = model11.predict(Test.values) \n", + "#Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut11 = pd.DataFrame(AssignmentOutPut11)\n", + "\n", + "AssignmentOutPut11.columns = ['Class'] # Naming the output column\n", + "AssignmentOutPut11.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut11['Class'] = AssignmentOutPut11['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut11.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut11.groupby('Class').size()[1].sum())\n", + "\n", + "AssignmentOutPut11.to_csv('AssignmentOutPut1.csv') # Writing AssignmentOutPut1 to a csv file" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'selected_features_train' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mkfold\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mKFold\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn_splits\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnum_folds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrandom_state\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mseed\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mmodel22\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mGaussianNB\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mmodel22\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mselected_features_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcross_val_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel22\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mselected_features\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcv\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkfold\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'selected_features_train' is not defined" + ] + } + ], + "source": [ + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.naive_bayes import GaussianNB\n", + "\n", + "num_folds = 10\n", + "seed = 22\n", + "kfold = KFold(n_splits=num_folds, random_state=seed)\n", + "model22 = GaussianNB()\n", + "model22.fit(selected_features_train, Y_train)\n", + "\n", + "results = cross_val_score(model22, selected_features, Y, cv=kfold)\n", + "Prediction = model22.predict(selected_features_train)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (results.mean()*100.0))\n", + "\n", + "#Assigning the preditions of the model to variable AssignmentOutPut\n", + "AssignmentOutPut22 = model22.predict(Test.values) \n", + "#Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut22 = pd.DataFrame(AssignmentOutPut22)\n", + "\n", + "AssignmentOutPut22.columns = ['Class'] # Naming the output column\n", + "AssignmentOutPut22.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut22['Class'] = AssignmentOutPut22['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut22.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut22.groupby('Class').size()[1].sum())\n", + "\n", + "AssignmentOutPut22.to_csv('AssignmentOutPut22.csv') # Writing AssignmentOutPut1 to a csv file" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'selected_features_train' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mkfold\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mKFold\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn_splits\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnum_folds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrandom_state\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mseed\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mmodel33\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mKNeighborsClassifier\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mmodel33\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mselected_features_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcross_val_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel33\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mselected_features\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcv\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkfold\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'selected_features_train' is not defined" + ] + } + ], + "source": [ + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.neighbors import KNeighborsClassifier\n", + "\n", + "num_folds = 10\n", + "seed = 33\n", + "kfold = KFold(n_splits=num_folds, random_state=seed)\n", + "model33 = KNeighborsClassifier()\n", + "model33.fit(selected_features_train, Y_train)\n", + "\n", + "results = cross_val_score(model33, selected_features, Y, cv=kfold)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (results.mean()*100.0))\n", + "\n", + "#Assigning the preditions of the model to variable AssignmentOutPut\n", + "AssignmentOutPut33 = model33.predict(Test.values) \n", + "#Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut33 = pd.DataFrame(AssignmentOutPut33)\n", + "\n", + "AssignmentOutPut33.columns = ['Class'] # Naming the output column\n", + "AssignmentOutPut33.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut33['Class'] = AssignmentOutPut33['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut33.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut33.groupby('Class').size()[1].sum())\n", + "\n", + "AssignmentOutPut33.to_csv('AssignmentOutPut33.csv') # Writing AssignmentOutPut1 to a csv file" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'selected_features_train' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mkfold\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mKFold\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn_splits\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnum_folds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrandom_state\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mseed\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mmodel44\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mDecisionTreeClassifier\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mmodel44\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mselected_features_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcross_val_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel44\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mselected_features\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcv\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkfold\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'selected_features_train' is not defined" + ] + } + ], + "source": [ + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "\n", + "num_folds = 10\n", + "seed = 44\n", + "kfold = KFold(n_splits=num_folds, random_state=seed)\n", + "model44 = DecisionTreeClassifier()\n", + "model44.fit(selected_features_train, Y_train)\n", + "\n", + "results = cross_val_score(model44, selected_features, Y, cv=kfold)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (results.mean()*100.0))\n", + "\n", + "#Assigning the preditions of the model to variable AssignmentOutPut\n", + "AssignmentOutPut44 = model44.predict(Test.values) \n", + "#Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut44 = pd.DataFrame(AssignmentOutPut44)\n", + "\n", + "AssignmentOutPut44.columns = ['Class'] # Naming the output column\n", + "AssignmentOutPut44.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut44['Class'] = AssignmentOutPut44['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut44.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut44.groupby('Class').size()[1].sum())\n", + "\n", + "AssignmentOutPut44.to_csv('AssignmentOutPut44.csv') # Writing AssignmentOutPut1 to a csv file" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'selected_features_train' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mkfold\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mKFold\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn_splits\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnum_folds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrandom_state\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mseed\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mmodel55\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mSVC\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mmodel55\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mselected_features_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcross_val_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel55\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mselected_features\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcv\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkfold\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'selected_features_train' is not defined" + ] + } + ], + "source": [ + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.svm import SVC\n", + "\n", + "num_folds = 55\n", + "seed = 6\n", + "kfold = KFold(n_splits=num_folds, random_state=seed)\n", + "model55 = SVC()\n", + "model55.fit(selected_features_train, Y_train)\n", + "\n", + "results = cross_val_score(model55, selected_features, Y, cv=kfold)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (results.mean()*100.0))\n", + "\n", + "#Assigning the preditions of the model to variable AssignmentOutPut\n", + "AssignmentOutPut55 = model55.predict(Test.values) \n", + "#Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut55 = pd.DataFrame(AssignmentOutPut55)\n", + "\n", + "AssignmentOutPut55.columns = ['Class'] # Naming the output column\n", + "AssignmentOutPut55.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut55['Class'] = AssignmentOutPut55['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut55.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut55.groupby('Class').size()[1].sum())\n", + "\n", + "AssignmentOutPut55.to_csv('AssignmentOutPut55.csv') # Writing AssignmentOutPut1 to a csv file" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Evaluating Machine learning Alogorithms\n", + "## Split into Train and Test set" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Non rescaled data" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MCC: 0.8283116428616907\n", + "Accuracy: 91.92422731804587\n", + "387\n", + "371\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import matthews_corrcoef\n", + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "A = Train.values\n", + "# Separating A into output and input components\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "test_size = 0.33\n", + "seed = 1\n", + "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", + "my_model1 = LogisticRegression()\n", + "my_model1.fit(selected_features_train, Y_train)\n", + "result = my_model1.score(selected_features_test, Y_test)\n", + "\n", + "Prediction = my_model1.predict(selected_features_train)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (result*100.0))\n", + "\n", + "#Assigning the preditions of the model to variable AssignmentOutPut\n", + "AssignmentOutPut1 = my_model1.predict(Test.values) \n", + "#Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut1 = pd.DataFrame(AssignmentOutPut1)\n", + "\n", + "AssignmentOutPut1.columns = ['Class'] # Naming the output column\n", + "AssignmentOutPut1.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut1['Class'] = AssignmentOutPut1['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut1.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut1.groupby('Class').size()[1].sum())\n", + "\n", + "AssignmentOutPut1.to_csv('AssignmentOutPut1.csv') # Writing AssignmentOutPut1 to a csv file" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MCC: 0.8566012373350099\n", + "Accuracy: 90.62811565304088\n", + "397\n", + "361\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import matthews_corrcoef\n", + "from sklearn.neighbors import KNeighborsClassifier\n", + "\n", + "A = Train.values\n", + "# Separating A into output and input components\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "test_size = 0.33\n", + "seed = 2\n", + "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", + "my_model2 = KNeighborsClassifier()\n", + "my_model2.fit(selected_features_train, Y_train)\n", + "result = my_model2.score(selected_features_test, Y_test)\n", + "\n", + "Prediction = my_model2.predict(selected_features_train)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (result*100.0))\n", + "\n", + "#Assigning the preditions of the model to variable AssignmentOutPut\n", + "AssignmentOutPut2 = my_model2.predict(Test.values) \n", + "#Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut2 = pd.DataFrame(AssignmentOutPut2)\n", + "# Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut2.columns = ['Class'] # Naming the out\n", + "AssignmentOutPut2.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut2['Class'] = AssignmentOutPut2['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut2.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut2.groupby('Class').size()[1].sum())\n", + "\n", + "AssignmentOutPut2.to_csv('AssignmentOutPut2.csv') # Writing AssignmentOutPut1 to a csv file" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MCC: 1.0\n", + "Accuracy: 90.72781655034895\n", + "387\n", + "371\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import matthews_corrcoef\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "\n", + "A = Train.values\n", + "# Separating A into output and input components\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "test_size = 0.33\n", + "seed = 3\n", + "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", + "my_model3 = DecisionTreeClassifier()\n", + "my_model3.fit(selected_features_train, Y_train)\n", + "result = my_model3.score(selected_features_test, Y_test)\n", + "\n", + "Prediction = my_model3.predict(selected_features_train)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (result*100.0))\n", + "AssignmentOutPut3 = my_model3.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut\n", + "\n", + "AssignmentOutPut3 = pd.DataFrame(AssignmentOutPut3)\n", + "# Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut3.columns = ['Class'] # Naming the out\n", + "AssignmentOutPut3.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut3['Class'] = AssignmentOutPut3['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut3.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut3.groupby('Class').size()[1].sum())\n", + "\n", + "AssignmentOutPut1.to_csv('AssignmentOutPut3.csv') # Writing AssignmentOutPut1 to a csv file\n" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MCC: 0.8417648773342619\n", + "Accuracy: 91.92422731804587\n", + "369\n", + "389\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import matthews_corrcoef\n", + "from sklearn.naive_bayes import GaussianNB\n", + "\n", + "A = Train.values\n", + "# Separating A into output and input components\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "test_size = 0.33\n", + "seed = 4\n", + "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", + "my_model4 = GaussianNB()\n", + "my_model4.fit(selected_features_train, Y_train)\n", + "result = my_model4.score(selected_features_test, Y_test)\n", + "\n", + "Prediction = my_model4.predict(selected_features_train)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (result*100.0))\n", + "\n", + "AssignmentOutPut4 = my_model4.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut\n", + "\n", + "AssignmentOutPut4 = pd.DataFrame(AssignmentOutPut4)\n", + "# Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut4.columns = ['Class'] # Naming the out\n", + "AssignmentOutPut4.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut4['Class'] = AssignmentOutPut4['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "AssignmentOutPut4.to_csv('AssignmentOutPut4.csv') # Writing AssignmentOutPut1 to a csv file\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut4.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut4.groupby('Class').size()[1].sum())" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MCC: 0.8164151115601915\n", + "Accuracy: 91.12662013958126\n", + "405\n", + "353\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import matthews_corrcoef\n", + "from sklearn.svm import SVC\n", + "\n", + "A = Train.values\n", + "# Separating A into output and input components\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "test_size = 0.33\n", + "seed = 5\n", + "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", + "my_model5 = SVC()\n", + "my_model5.fit(selected_features_train, Y_train)\n", + "result = my_model5.score(selected_features_test, Y_test)\n", + "\n", + "Prediction = my_model5.predict(selected_features_train)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (result*100.0))\n", + "AssignmentOutPut5 = my_model5.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut\n", + "\n", + "AssignmentOutPut5 = pd.DataFrame(AssignmentOutPut5)\n", + "# Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut5.columns = ['Class'] # Naming the out\n", + "AssignmentOutPut5.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut5['Class'] = AssignmentOutPut5['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "AssignmentOutPut1.to_csv('AssignmentOutPut5.csv') # Writing AssignmentOutPut1 to a csv file\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut5.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut5.groupby('Class').size()[1].sum())" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MCC: 0.8376165100283083\n", + "Accuracy: 91.72482552342971\n", + "403\n", + "355\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", + "from sklearn.metrics import matthews_corrcoef\n", + "\n", + "A = Train.values\n", + "# Separating A into output and input components\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "test_size = 0.33\n", + "seed = 6\n", + "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", + "my_model6 = LinearDiscriminantAnalysis()\n", + "my_model6.fit(selected_features_train, Y_train)\n", + "result = my_model6.score(selected_features_test, Y_test)\n", + "\n", + "Prediction = my_model6.predict(selected_features_train)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (result*100.0))\n", + "AssignmentOutPut6 = my_model6.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut\n", + "\n", + "AssignmentOutPut6 = pd.DataFrame(AssignmentOutPut6)\n", + "# Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut6.columns = ['Class'] # Naming the out\n", + "AssignmentOutPut6.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut6['Class'] = AssignmentOutPut6['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "AssignmentOutPut6.to_csv('AssignmentOutPut6.csv') # Writing AssignmentOutPut1 to a csv file\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut6.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut6.groupby('Class').size()[1].sum())" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.4" + }, + "varInspector": { + "cols": { + "lenName": 16, + "lenType": 16, + "lenVar": 40 + }, + "kernels_config": { + "python": { + "delete_cmd_postfix": "", + "delete_cmd_prefix": "del ", + "library": "var_list.py", + "varRefreshCmd": "print(var_dic_list())" + }, + "r": { + "delete_cmd_postfix": ") ", + "delete_cmd_prefix": "rm(", + "library": "var_list.r", + "varRefreshCmd": "cat(var_dic_list()) " + } + }, + "types_to_exclude": [ + "module", + "function", + "builtin_function_or_method", + "instance", + "_Feature" + ], + "window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/Assignment Colab/nsangi-olga-tendo.ipynb b/Assignment Colab/nsangi-olga-tendo.ipynb index 2fa692c..2d52262 100644 --- a/Assignment Colab/nsangi-olga-tendo.ipynb +++ b/Assignment Colab/nsangi-olga-tendo.ipynb @@ -1,5 +1,13 @@ { "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + " Please look out for these cells for corrections." + ] + }, { "cell_type": "code", "execution_count": 1, @@ -314,7 +322,17 @@ "metadata": {}, "source": [ "## Dimensions of the data train set\n", - "### Checking for the number of rows and columns in the data sets" + "### Checking for the number of rows and columns in the data sets\n", + "\n", + "
\n", + " \n", + " ## ??\n", + " \n", + " When you see these: \n", + " - I want to know if you understand the concept\n", + " - Why are you applying the concept\n", + " - What did you learn?\n", + " - I want to see that you know what you are doing." ] }, { @@ -372,7 +390,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Establishing the data types for each attribute in the train data set. This helps in finding out which column has data types like strings that may need to be converted to foating points or integers to represent categorical or ordinal values. This can be done using df.dtype method or the df.info() method as shown in the two cells below, tho the df.info() is more informative." + "## Establishing the data types for each attribute in the train data set. This helps in finding out which column has data types like strings that may need to be converted to foating points or integers to represent categorical or ordinal values. This can be done using df.dtype method or the df.info() method as shown in the two cells below, tho the df.info() is more informative.\n", + "\n", + "
\n", + " \n", + " Why is everything so big? \n", + "

like this?" ] }, { @@ -658,14 +681,22 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### From the values above, there are no missing values since all counts in each column is equal. We can also observe that there are negative values in some attributes have a minimum values in negatives." + "### From the values above, there are no missing values since all counts in each column is equal. We can also observe that there are negative values in some attributes have a minimum values in negatives.\n", + "\n", + "
\n", + " \n", + " ## ??" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Since this is a classification problem, its important to check out the propotions of the values in the class to be predicted as its possible one class may have more values as compared to the others." + "## Since this is a classification problem, its important to check out the propotions of the values in the class to be predicted as its possible one class may have more values as compared to the others.\n", + "\n", + "
\n", + " \n", + " ## ??" ] }, { @@ -740,7 +771,11 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Establishing if there are any missing values in the attributes of the data set. This helps to give an insight on how to handle the missing values, whether to remove rows that have missing values or establishing a method like the mean,median ect to impute the NAs. " + "## Establishing if there are any missing values in the attributes of the data set. This helps to give an insight on how to handle the missing values, whether to remove rows that have missing values or establishing a method like the mean,median ect to impute the NAs. \n", + "\n", + "
\n", + " \n", + " Good explanation." ] }, { @@ -1120,7 +1155,11 @@ "metadata": {}, "source": [ "## Using visualisation to understand the data at hand. Histograms, Density plots and Box and whisker plots are some of the plots used to understand the attribute distribution.\n", - "## Histograms were used." + "## Histograms were used.\n", + "\n", + "
\n", + " \n", + " ## ??" ] }, { @@ -1157,7 +1196,11 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## From the histograms above, we can observe that attributes AS_MeanAmphiMoment, AS_DAYM780201, AS_FUKS010112, FULL_DAYM780201, FULL_GEOR030101, FULL_AURR980107,FULL_CHARGE have a normal. We can also tell from these plots that attribute CT_RACS820104 and FULL_AcidicMolPerc are skewed to the right. We can also tell that attributes NT_EFC195 and CLASS are categorical attributes. This can also be observed using density plots as shown below." + "## From the histograms above, we can observe that attributes AS_MeanAmphiMoment, AS_DAYM780201, AS_FUKS010112, FULL_DAYM780201, FULL_GEOR030101, FULL_AURR980107,FULL_CHARGE have a normal. We can also tell from these plots that attribute CT_RACS820104 and FULL_AcidicMolPerc are skewed to the right. We can also tell that attributes NT_EFC195 and CLASS are categorical attributes. This can also be observed using density plots as shown below.\n", + "\n", + "
\n", + " \n", + " ## ??" ] }, { @@ -1205,7 +1248,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Checking for the skewness of the data. Since many machine learning algorithms assume normal distribution,this allows one to know what attributes need to be corrected of skewness to improve the accuracy of the model. Skewness can be observed with bar plots of .skew()." + "## Checking for the skewness of the data. Since many machine learning algorithms assume normal distribution,this allows one to know what attributes need to be corrected of skewness to improve the accuracy of the model. Skewness can be observed with bar plots of .skew().\n", + "\n", + "
\n", + " Good explanation.\n", + " \n", + " So what did you findout?" ] }, { @@ -1287,7 +1335,11 @@ "metadata": {}, "source": [ "## Spot checking classification algorithms since its a classification problem at hand.\n", - "### This is done to know which algorithm is best suited for the problem at hand. Two linear machine learning algorithms(Logistic regression and Linear discriminant analysis) and four non-linear machine learning algorithm were used(k-nearest neighbors, naive bayes, support vector machines and classific regression tress. " + "### This is done to know which algorithm is best suited for the problem at hand. Two linear machine learning algorithms(Logistic regression and Linear discriminant analysis) and four non-linear machine learning algorithm were used(k-nearest neighbors, naive bayes, support vector machines and classific regression tress. \n", + "\n", + "
\n", + " \n", + " ## Less than 10 algorithms!!!" ] }, { @@ -2352,7 +2404,36 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.6" + "version": "3.7.4" + }, + "varInspector": { + "cols": { + "lenName": 16, + "lenType": 16, + "lenVar": 40 + }, + "kernels_config": { + "python": { + "delete_cmd_postfix": "", + "delete_cmd_prefix": "del ", + "library": "var_list.py", + "varRefreshCmd": "print(var_dic_list())" + }, + "r": { + "delete_cmd_postfix": ") ", + "delete_cmd_prefix": "rm(", + "library": "var_list.r", + "varRefreshCmd": "cat(var_dic_list()) " + } + }, + "types_to_exclude": [ + "module", + "function", + "builtin_function_or_method", + "instance", + "_Feature" + ], + "window_display": false } }, "nbformat": 4, diff --git a/Reading Material/Pandas Cookbook/Pandas-Cookbook b/Reading Material/Pandas Cookbook/Pandas-Cookbook new file mode 160000 index 0000000..b45d95c --- /dev/null +++ b/Reading Material/Pandas Cookbook/Pandas-Cookbook @@ -0,0 +1 @@ +Subproject commit b45d95ccef24b020fdf28ecb5a07e3348bee62f1 From 9f9a44656a8ac61fb1e35a6a4ee195c609bdc372 Mon Sep 17 00:00:00 2001 From: Atwine Date: Thu, 12 Mar 2020 16:10:50 +0300 Subject: [PATCH 15/29] updated --- .../Talent Paul-checkpoint.ipynb | 1903 ----------------- .../Screenshot 2020-02-14 at 14.59.00.png | Bin 102933 -> 0 bytes Assignment Colab/Talent Paul.ipynb | 1903 ----------------- Assignment Colab/talz_csv10 | 759 ------- Assignment Colab/talz_csv3 | 759 ------- Assignment Colab/talz_csv8 | 759 ------- Assignment Colab/talz_csv9 | 759 ------- 7 files changed, 6842 deletions(-) delete mode 100644 Assignment Colab/.ipynb_checkpoints/Talent Paul-checkpoint.ipynb delete mode 100644 Assignment Colab/Screenshot 2020-02-14 at 14.59.00.png delete mode 100644 Assignment Colab/Talent Paul.ipynb delete mode 100644 Assignment Colab/talz_csv10 delete mode 100644 Assignment Colab/talz_csv3 delete mode 100644 Assignment Colab/talz_csv8 delete mode 100644 Assignment Colab/talz_csv9 diff --git a/Assignment Colab/.ipynb_checkpoints/Talent Paul-checkpoint.ipynb b/Assignment Colab/.ipynb_checkpoints/Talent Paul-checkpoint.ipynb deleted file mode 100644 index 648ba8b..0000000 --- a/Assignment Colab/.ipynb_checkpoints/Talent Paul-checkpoint.ipynb +++ /dev/null @@ -1,1903 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Talent Paul" - ] - }, - { - "cell_type": "raw", - "metadata": { - "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", - "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" - }, - "source": [ - "# This Python 3 environment comes with many helpful analytics libraries installed\n", - "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", - "# For example, here's several helpful packages to load in \n", - "\n", - "import numpy as np # linear algebra\n", - "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", - "import matplotlib.pyplot as plt # Plotting\n", - "\n", - "# Input data files are available in the \"../input/\" directory.\n", - "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", - "\n", - "import os\n", - "for dirname, _, filenames in os.walk('/kaggle/input'):\n", - " for filename in filenames:\n", - " print(os.path.join(dirname, filename))\n", - "\n", - "# Any results you write to the current directory are saved as output." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "
\n", - " Please look out for colored cells for my notes.\n", - "
" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np # linear algebra\n", - "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", - "import matplotlib.pyplot as plt # Plotting" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": { - "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0", - "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a" - }, - "outputs": [], - "source": [ - "#Dealing with errors\n", - "import warnings\n", - "warnings.filterwarnings('ignore')" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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" - ], - "text/plain": [ - " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n", - "0 5.0 0.000 0.951 74.842 \n", - "1 4.0 5.405 0.931 71.595 \n", - "2 5.5 5.405 0.873 73.595 \n", - "3 5.0 4.167 0.895 66.250 \n", - "4 7.5 8.537 0.932 64.720 \n", - "\n", - " FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n", - "0 0.975 -3.663 0 0.282 \n", - "1 0.957 -4.011 1 0.600 \n", - "2 0.961 -2.512 0 0.593 \n", - "3 0.999 -1.362 0 0.614 \n", - "4 0.979 -2.091 0 0.616 \n", - "\n", - " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 CLASS \n", - "0 73.444 5.661 1.041 1 \n", - "1 68.222 6.537 1.453 1 \n", - "2 69.444 4.934 1.722 1 \n", - "3 67.222 4.316 1.382 1 \n", - "4 72.944 4.540 1.539 1 " - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "### Loading the data\n", - "Train = pd.read_csv(\"../AMP Data Sets/AMP_TrainSet.csv\")\n", - "Test = pd.read_csv(\"../AMP Data Sets/Test.csv\")\n", - "Train.head(5)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(3038, 12)" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# checking the dimensions of your data\n", - "#This returns the number of rows and columns\n", - "\n", - "Train.shape\n" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "FULL_Charge 0\n", - "FULL_AcidicMolPerc 0\n", - "FULL_AURR980107 0\n", - "FULL_DAYM780201 0\n", - "FULL_GEOR030101 0\n", - "FULL_OOBM850104 0\n", - "NT_EFC195 0\n", - "AS_MeanAmphiMoment 0\n", - "AS_DAYM780201 0\n", - "AS_FUKS010112 0\n", - "CT_RACS820104 0\n", - "CLASS 0\n", - "dtype: int64" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#Looking for null values in each colum\n", - "Train.isnull().sum()" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "FULL_Charge float64\n", - "FULL_AcidicMolPerc float64\n", - "FULL_AURR980107 float64\n", - "FULL_DAYM780201 float64\n", - "FULL_GEOR030101 float64\n", - "FULL_OOBM850104 float64\n", - "NT_EFC195 int64\n", - "AS_MeanAmphiMoment float64\n", - "AS_DAYM780201 float64\n", - "AS_FUKS010112 float64\n", - "CT_RACS820104 float64\n", - "CLASS int64\n", - "dtype: object" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "##Exploring the data and it's data types\n", - "Train.dtypes" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201FULL_GEOR030101FULL_OOBM850104NT_EFC195AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CT_RACS820104CLASS
count3038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.000000
mean2.0602378.5215200.97141073.6687600.994007-2.4329270.08854515.68323373.6508285.9113611.2352550.500000
std3.8199297.5866520.1074138.5274890.0313331.7072230.28413311.5756659.1660920.6936890.2100120.500082
min-16.0000000.0000000.68400042.7500000.866000-10.4320000.0000000.04100042.7780003.5330000.7850000.000000
25%0.0000002.5160000.89500068.2940000.974000-3.6060000.0000005.58750067.5560005.4592501.0820000.000000
50%2.0000007.1430000.96300074.0595000.994000-2.2965000.00000014.98850073.6970005.9255001.1840000.500000
75%4.00000013.1580001.04100079.3437501.011000-1.2832500.00000026.80775079.7780006.3820001.3510001.000000
max30.00000046.6670001.451000101.6820001.1960003.5760001.00000051.280000103.1670008.6620002.1920001.000000
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FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201FULL_GEOR030101FULL_OOBM850104NT_EFC195AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CT_RACS820104CLASS
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FULL_AcidicMolPerc-0.6129961.0000000.7947960.5414810.1152010.513344-0.143168-0.4315900.4496210.002334-0.213543-0.598816
FULL_AURR980107-0.4909770.7947961.0000000.5482530.3461390.462712-0.169540-0.4260970.4562600.032958-0.403599-0.584111
FULL_DAYM780201-0.4346030.5414810.5482531.0000000.0101180.334778-0.090058-0.4087930.8941910.055915-0.326792-0.554838
FULL_GEOR030101-0.0587250.1152010.3461390.0101181.0000000.319157-0.230417-0.160269-0.0290850.040480-0.151935-0.260470
FULL_OOBM850104-0.2837580.5133440.4627120.3347780.3191571.000000-0.230561-0.3362970.275640-0.4527690.155304-0.453287
NT_EFC1950.088068-0.143168-0.169540-0.090058-0.230417-0.2305611.0000000.178683-0.0368440.1459240.0808980.260702
AS_MeanAmphiMoment0.355477-0.431590-0.426097-0.408793-0.160269-0.3362970.1786831.000000-0.3223780.0255800.1715240.693552
AS_DAYM780201-0.3653740.4496210.4562600.894191-0.0290850.275640-0.036844-0.3223781.0000000.045562-0.256060-0.437168
AS_FUKS010112-0.0905700.0023340.0329580.0559150.040480-0.4527690.1459240.0255800.0455621.000000-0.4452840.033432
CT_RACS8201040.232929-0.213543-0.403599-0.326792-0.1519350.1553040.0808980.171524-0.256060-0.4452841.0000000.267652
CLASS0.534602-0.598816-0.584111-0.554838-0.260470-0.4532870.2607020.693552-0.4371680.0334320.2676521.000000
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" - ], - "text/plain": [ - " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 \\\n", - "FULL_Charge 1.000000 -0.612996 -0.490977 \n", - "FULL_AcidicMolPerc -0.612996 1.000000 0.794796 \n", - "FULL_AURR980107 -0.490977 0.794796 1.000000 \n", - "FULL_DAYM780201 -0.434603 0.541481 0.548253 \n", - "FULL_GEOR030101 -0.058725 0.115201 0.346139 \n", - "FULL_OOBM850104 -0.283758 0.513344 0.462712 \n", - "NT_EFC195 0.088068 -0.143168 -0.169540 \n", - "AS_MeanAmphiMoment 0.355477 -0.431590 -0.426097 \n", - "AS_DAYM780201 -0.365374 0.449621 0.456260 \n", - "AS_FUKS010112 -0.090570 0.002334 0.032958 \n", - "CT_RACS820104 0.232929 -0.213543 -0.403599 \n", - "CLASS 0.534602 -0.598816 -0.584111 \n", - "\n", - " FULL_DAYM780201 FULL_GEOR030101 FULL_OOBM850104 \\\n", - "FULL_Charge -0.434603 -0.058725 -0.283758 \n", - "FULL_AcidicMolPerc 0.541481 0.115201 0.513344 \n", - "FULL_AURR980107 0.548253 0.346139 0.462712 \n", - "FULL_DAYM780201 1.000000 0.010118 0.334778 \n", - "FULL_GEOR030101 0.010118 1.000000 0.319157 \n", - "FULL_OOBM850104 0.334778 0.319157 1.000000 \n", - "NT_EFC195 -0.090058 -0.230417 -0.230561 \n", - "AS_MeanAmphiMoment -0.408793 -0.160269 -0.336297 \n", - "AS_DAYM780201 0.894191 -0.029085 0.275640 \n", - "AS_FUKS010112 0.055915 0.040480 -0.452769 \n", - "CT_RACS820104 -0.326792 -0.151935 0.155304 \n", - "CLASS -0.554838 -0.260470 -0.453287 \n", - "\n", - " NT_EFC195 AS_MeanAmphiMoment AS_DAYM780201 \\\n", - "FULL_Charge 0.088068 0.355477 -0.365374 \n", - "FULL_AcidicMolPerc -0.143168 -0.431590 0.449621 \n", - "FULL_AURR980107 -0.169540 -0.426097 0.456260 \n", - "FULL_DAYM780201 -0.090058 -0.408793 0.894191 \n", - "FULL_GEOR030101 -0.230417 -0.160269 -0.029085 \n", - "FULL_OOBM850104 -0.230561 -0.336297 0.275640 \n", - "NT_EFC195 1.000000 0.178683 -0.036844 \n", - "AS_MeanAmphiMoment 0.178683 1.000000 -0.322378 \n", - "AS_DAYM780201 -0.036844 -0.322378 1.000000 \n", - "AS_FUKS010112 0.145924 0.025580 0.045562 \n", - "CT_RACS820104 0.080898 0.171524 -0.256060 \n", - "CLASS 0.260702 0.693552 -0.437168 \n", - "\n", - " AS_FUKS010112 CT_RACS820104 CLASS \n", - "FULL_Charge -0.090570 0.232929 0.534602 \n", - "FULL_AcidicMolPerc 0.002334 -0.213543 -0.598816 \n", - "FULL_AURR980107 0.032958 -0.403599 -0.584111 \n", - "FULL_DAYM780201 0.055915 -0.326792 -0.554838 \n", - "FULL_GEOR030101 0.040480 -0.151935 -0.260470 \n", - "FULL_OOBM850104 -0.452769 0.155304 -0.453287 \n", - "NT_EFC195 0.145924 0.080898 0.260702 \n", - "AS_MeanAmphiMoment 0.025580 0.171524 0.693552 \n", - "AS_DAYM780201 0.045562 -0.256060 -0.437168 \n", - "AS_FUKS010112 1.000000 -0.445284 0.033432 \n", - "CT_RACS820104 -0.445284 1.000000 0.267652 \n", - "CLASS 0.033432 0.267652 1.000000 " - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#Correlation\n", - "Train.corr(method='pearson')" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "#Classification\n", - "Train.groupby('CLASS').size().plot(kind='bar')\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "
\n", - " I asked specifically for each of us to write their thoughts down specifically on what they are doing at each stage.\n", - " \n", - " You are not doing a good job documenting your work with mark down.\n", - " " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#The distribution of 0 and 1 is the same" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "FULL_Charge 0.534602\n", - "FULL_AcidicMolPerc -0.598816\n", - "FULL_AURR980107 -0.584111\n", - "FULL_DAYM780201 -0.554838\n", - "FULL_GEOR030101 -0.260470\n", - "FULL_OOBM850104 -0.453287\n", - "NT_EFC195 0.260702\n", - "AS_MeanAmphiMoment 0.693552\n", - "AS_DAYM780201 -0.437168\n", - "AS_FUKS010112 0.033432\n", - "CT_RACS820104 0.267652\n", - "CLASS 1.000000\n", - "Name: CLASS, dtype: float64" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#Looking at the correlation of \"CLASS\" with other attributes\n", - "Train.corr()['CLASS']" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Data With Visualization" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "#Univariate Plot\n", - "plt.figure(figsize=(50,50))\n", - "Train.hist()\n", - "plt.subplots_adjust(bottom=1,right=2,top=3)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Density Plots\n", - "\n", - "### Density plots are another way of getting a quick idea of the distribution of each attribute. The plots look like an abstracted histogram with a smooth curve drawn through the top of each bin\n", - "\n", - "
\n", - "\n", - "## ??\n", - "\n", - "What did you learn from the plots?" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 20, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "Train.plot(kind='box', subplots=True, layout=(3,4), sharex=False, sharey=False)\n", - "plt.subplots_adjust(bottom=1,right=2,top=3)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "
\n", - "Please your visual, is compact, the labels on the upper axis are overlapping, can you try a different library to plot this if you are having a hard time with matplotlib?" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "#Multivariate Plot\n", - "correlations = Train.corr()\n", - "# plot correlation matrix\n", - "fig = plt.figure()\n", - "ax = fig.add_subplot(111)\n", - "cax = ax.matshow(correlations, vmin=-1, vmax=1)\n", - "fig.colorbar(cax)\n", - "ticks = np.arange(0,9,1)\n", - "ax.set_xticks(ticks)\n", - "ax.set_yticks(ticks)\n", - "ax.set_xticklabels(Train.columns)\n", - "ax.set_yticklabels(Train.columns)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Scatter plot\n", - "\n", - "
\n", - "\n", - "## ??\n", - "\n", - "What are you trying to learn with the plots below? \n", - "Its not compulsory to do a pair plot if you are not trying to inform specific decisions.\n", - "\n", - "Please plot only those that you are interested in they could be 2 or 3 that have caught your eye." - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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RUhn/4E2v0olOTW//6AOVdczePYtqhka3/OGBsWUoihJ945kXB499905ZI73z3uprec/bdg3VWxeaqqSGlr0AACAASURBVOvi7/OHCnFfvD7j6sJbXnuFWvVAd33pMf3Sda/Q8ZNtbZ5r6cC3n9WuK7bqXYV6eVRdvqEZ6HQv0eluNFCnFu/NR9++Sy+0o7z8VZWLqvjbOlfX/gOH9Pof+B6991OD256pB5qpB5ptBHr6hc7Atnyc/9ZnvlHZ9hx9sTd0Tne/dVFJ4gbagHKZ8tv5uddckbclB79zTIsv25KvV3VuVbFZdS8v5vaknGP8+FXb9cvXvWLg+hSvY1VO4uusU91Iv/gnX9Xh4+08x7jzC9+szCuq6smqWMzr2d07dWcpf7mzouzt3b1Tn3noaf3I979k4PUPvPka/bv//IRuee0V+t75lk62I72zsO9RZdbHvJN015ce0y9f9wptaIX62+Pts86HvvLoM3rjNZdV5j3FtuWOG69RLbR6T3ZNF+Zb+vBbrlU/dkNt6ks2NvWyLbMXdD0sVefEo9ogv+yfP3ioMt/19cnPveYKfeXRZ/RT11w2lGduaAb62+c7evS7L2jxiq268wvf1M//o5frvZ96qLKO9jG7bUNd//x//H4dO9kbeH/fnkV9qFC3DcT4nkVtmavpX/2Hrw3kJd85ekIv27phIF7u2r1Tl7RCnexEQ23zoWOn9AOXbRo43+IxrKTNPpPrjHNXdb0/9j+9Wt0oOeN74Ld1x398dGRs7929U7XQ6Bf+aKkO/P23XKs4cQM57x03XqNNs3Xd8tEH9JqXb9GtP3KFnj/dH8o5tm1oSHI6+mJvKPf8ztETetm2jUP9h2IbX+zXVuVTo/LtvXsWtbEZ6Hc++/W8PP/8P3q5/t1/fkK//hOv1JGTyeB+K/qcvj+w/4GndPf/852B6yxJ3zl2Ss+c6AyWobfuUqNm9bY/+P+mqnyM68tNywf3OHfTHAedTqQT/b4kqVkzOt136UThbPLYbM0oclJoBuZy6dnTseZbgYykU32n2ZrRs6djNUOj4ydjbWgEkoyiZGnymKT0gw8jPXOir20bapLSiSHfOdbV8ZNtveryTTKSYkmdfvqBTKfv9EI7UqtmdeR4NHSdv/708/rQlx7X3XsW1aiZynozSZI8n/b1cz9KhureqjxzGuoinF/LjTXf87ZdunLbnL519KTu+I+P6ld+9BU60e5XjjH4tvSW116hS2ZqmmuEevp4e2DZP7n1h/RCOxqZZ5bH3LbM1fV/fv7RvO3+yNsWlSQaOd5x+w1X69JNTZ3sxEPjhF959Jk8px/V/y+OP9z7X57UXz9xTHft3qlv/O0LetXl82r3Yp0u9Ut9P7G4zoduulYbWmGeA+357y8fyqXKY2Q+nymW3z+85Qf1rHpD43f79izqS19/Rn928PAF15erismqfvPAmOJbd6kWGv3e576Rjx2U1/nxq7brl657xUC9+v7rr9a3/m6pn1bVNy+OL3z4LdcqsDaPv//lJ185VLdunasrcU4n2oPjbMW8eFROW97f3j2L2jZX07efPT30Gcu/vv8beTnZ2Az1L//8azp6spvH8Pve8Eo9f6o3dAx+veJjv9+q8TbahfGKYwY37NqhZ0/2Bj4bq4rdj97ygzrZifRLf7pU1v/snT+k505ElXF4956dSpz0mYeeHhoH8v363/ns1wfGCLbM1dWqBTp6Mhr6bKEeSB/4y6VxiWK9dGdpPK04lpWPp173Cn3mbw4PjZnt27MoI6cHvn1Mi1dsHfosotOLh/pR87M1vVgqK748v71QVu7avVPzM5Eu3djSt46eZJwBWCfW66cgr5b0mHPuCedcT9InJL2ptMybJP1R9ni/pOuMMWddixw71csrpne97vvyhlSSDh9v69fve1jXL+7QrR87oGOneiPX9cu/91MP6blTfV2/uCMfwJek1191qQ4/1x65/Xd//EFdv7hDknTDrpfmFbE/pusXd+j4qf7Q+r/2yYd064+8PF/GV+7+/Xd//EHdsOulet/+h/Plqvb/7MmlxMO/9+zJXl75l5e/7d6D6vQSvf6qS/NE2S/zrnsPZrNysRaOtXt5vEjpPbjt3oPpX+3E0m33HhyIjWJMFWP0cNb5e/p4R9deviVPQvx7/t77mDtSGNDwyzx9vJMPLhe3efi5dh7fPt7Ly7zrdd9Xubw/n+LzwxX78cdX3FZ5vUPPtYfO67Z7D+r1V11aWf6L5dIf26Hn2jrZSYau+eHn0u2Xt/Ern/gbHXquPbKOSbfTWbYMHTnZHT72jz+oIy/2Rl7LqnrrQlN1Xfx9rqoTl6sL37f/YR3P6vDb7j2o79ueTmJ6/VWX5vsZ11a8++MPKrSBjpzoDtWpxXtz+HhnoPxVlYuq+Dt8vKMbdr007wgU33vuVF+Hj3eUODO0LR/nVcd7/eKOynM6cqI71AaUy5TfTt42fPxBvf6qSwfWqzq3qtisupcXc3tSzjGuX9wxdH2K17EqJ/F1Vhob6es+xxiVV1TVk1WxmNezFflLVdm7LctHyq+/91MP5WWvH7l84kZxX1Vl1se8L6/vuveg+pE7p3zohl0vHZn3FM/51z75kI4Xrunh4+k1rmpTnzx2+oKvh6Xq+BvVBvllR+W7xXrlhl0vrcwz+7H0vv0Pp/VNFnO+Xqyqz/z9u35xh54+3hl6/12luq2cS8SxhvKSay/fMhQv7/74g+rHqmybX3PltqHzXcn1OtvrjHNXdb2fPHb6rO6B39a42L4tyyGKrx0/1R/KeX/tkw/pcJZb3vojL9fh453KnOPQc21JtjL3vPbyLZX9h2KcF/u1VfnUqHz7tnsPyho7UJ59Xe+cGd7vxx/UsyeHy8zh59q6YddLh67zsVM9PXns9HAZ+uMDevLY6akrH+P6crh4THMcHGv31IucepHTi+1EvcjpRPZ/L3J6vp3oZCfR8+1EL7TT/59vJ+pHTi9mr/vl+pFTP5YOP9dWnEgnO4lOdxN1ekvb6/TS7fl++fPtRCfaSd53ezHbvj+W0930/8PPtSVV1EH3HtRrrtymw8fbeue9BzWq3nyulPsdP9WvrHur8sxpqItwfi031nzrxw7oyMlunhscOdGt7J8U29L37X9Yz7zQVS/r8xSX7UVubJ5ZHnN7+nhnoO1+5oXu2PGO9+1/WFGsynHCYk4vVff/i+MPae6S5s2vuXKbnj7e0XMV/VKfOxTX+eVPfHUgB6rKpcp5uM9nyn3eqvG7d917UG/auXBB9uWqYnK5HO/WPz6gQ9n4rB87KK/jx87K97vYT6vqmxfj77lT/YH4q6pbDx/vKLDB0HvFvNi/Vs5Ny/u77d6DihNVfsZSLCdHXuzlz30MH36uXXkMxbEC/3jceBvtwnjFMYPDWf99XBwePp6Oy/uJG/61JDEj4/DIi718nGpUv748RvD08Y4kU/nZQmCDgXGJ/L2K8bTiWFbxs7aqMbN33XtQR17s5WWqfM7lY3/f/ocVVpQVX57L59mNXN4eEaPA+rBep+5fJulQ4flhST80ahnnXGSMeUHSFknPljdmjHmHpHdI0ktf+tLKHfaiOK+YNrVq+eP8AI6389d7UTxy3eLyM/VAMwoG3kuc00w9GLv9Ta30rwYCa4aOyb9Xtb5fftTx+/eL2y3vv2rbyx2v/1q7qmWiOBHOzUriV0q/RqvyHhTuTzE2ijE1Kn7jEdv066Q/STIcH6NixpeJ4v6rtl21fPn9cfupKi8rWc85t+xxFY+t6prP1IN8marzH3fu/v3ia+Uy1I+TFa9bPP9yvbWWVhrD56Lquvj7vFydWH7dL1+sw/29TtzSPV+urViuvi8eo3cm8Tfq+H0sjCq/zrmB58u1L8udQ9V2/H5Wcm7l2BwV45NqT9Yifscp5xjLXcdxOUlRMWfwyxSdyX0vP15pPlK17cPH27JmfJ4z6tx8efXrn20+tNzxlduplVy3mXowsXp4LWN4VPxVnbtfdlS+W843qrbr77Wvm6vynPI65Rhe7v3i/U6yPKH4/qi61hpVts3F5VdaL466dme63rRab/WwNLqsr/TerSS2V7I/H2OjcnK/zKh6dVyuX95GuV9bXrZqvaSQWxf/H3U8VWXG5zzF1/x1Xu66VK2z1s5HXw4Xj/UYB2cSw2fDmuF1rUn7Mr7PPU55meWu17hxDv+tHuPy0ZXmfqPq9wu1rV6v1lMOMSrvi7L+77jx3nJbOqptL752NmNuxXgetf5K+2rLjZf4tt2XvXFjaVXrFHOgM8kpisbt04+bXGh9uaqYPNNYqVpn1Daq+mlV+5BWFn/j8tpx46Kjno9qd5c7d/943HqjHpfXudDbhXOJ4eKYQXGMVxo95lPVLsdj4tAvP65fVtU3it3ocYAzGduVlsaylusjztSDgXHpced8JrmMX3bUeOyFHqPjTDqPwMVtvX7zxnnlnPuIc26Xc27Xtm3bKpeph4EW5luSpOfb/fyxtzDfyl+vh8HIdYvLn+7FQ9uyxuh0Lx67/efb6VdNxokbOqbn2/2R6/vlRx2/f7+43fL+q7a93PH631usWib9HXuci5XEr5T+7mXlPbDpb+2VY6MYU6PiNxixTb9OnLgzihlfJor7r9p21fLl98ftp1yWVrqeMWbZ4yoeW9U1P519zeOo8x937v794mvlMlQL7IrXLZ5/ud5aSyuN4XNRdV38fViuTiy/7pcv1uH+XhfruuXaiuXq++IxemcSf6OO38fgqPJb/JKqcnmp2v9y51C1Hb+flZxbOTZHxfik2pO1iN9xyjnGctdxXE5SrCeKOcOZtv1Vz6vyl7Mte4nTGa3nz628/tnmQ8sdX7mdWsl1O92LJ1YPr2UMj4q/qnP3y47Kd8v5RtV2/b22Y/Kc8jq+rjubGLdZnlB8f1RdmzhVts3F5VdaL466dme63rRab/WwNLqsr/TerSS2V7I/H2OjcnK/zKh6dVyuX97GSnL38nq2kFsX/x91PFVlxuc8xdfqYaB6GCx7XcrrTML56Mvh4rEe4+BMYjjI/oWl//3jqn+JU/44KLwWWJP3uYv/ytsrL+OvV3kd//+4fpL/YHhcPrrS3G9U/X6httXr1XrKIUa1o2HW/10uPy3+P6ptL752NmNuxf2PWn+lfbXlxkt82+7L3rixtKp1ijnQmeQUReP26cdNLrS+XFVMnkmsjBpnG7WNqn5a1T6klcXfuLx23LjoqOej2t1R5WQlZXXU47Pt+027c4nh4phBMfbGjfdW3Zuqz0XKy4/rl1X1jYIRn4X55Vfaxyr2s5brI57uxZWfwY2KxzMpK4kbPR57ocfoOJPOI3BxW6+frD8taUfh+UL2WuUyxphQ0iWSjp3tDrfM1nXP23ZpYb6lfV9+XLffcHVeWS3Mp7/Tdt/BQ7rnbbu0ZbY+cl2//AfefI02z9Z038FD+jc/+6r8vS8+8l0tbG6N3P5du3fqvoPpl47sP/CU9u5ZHDim+w4e0vxsbWj9O268Rvd85Yl8mfdfP/j+Xbt3av+Bp3T7DVfny1Xtf+tcXXfceM3Ae1vn6tq7e2fl8nv3LKpZt/riI9/VXaVl9u1Z1Pa5xtneEpyhLa16Hi9Seg/27lnUllZdYSDt3bM4EBvFmCrG6MJ8Gp+XzTf11SePaV9pm/7e+5jbvqE+FE+XzTf1wZuGt7mwuZXHt4/38jL7vvx45fL+fIrPFyr244+vuK3yejs2t4bOa++eRX3xke9Wlv9iufTHtmNzS3NNO3TNFzan2y9v44M3vUo7NrdG1jHpdprLlqHtc43hY9+9U9s31Edey6p660JTdV38fa6qE5erC/1vA/p67vEjJ7TPx0ipXh5Vl0dJrO0bG0N1avHeLMw3B8pfVbmoir+F+ab2H3hKH3jz8LY3z9a0MN+UNW5oWz7Oq473voOHKs9p+8bGUBtQLlN+O3nbsHunvvjIdwfWqzq3qtisupcXc3tSzjHuO3ho6PoUr2NVTuLrrDQ20td9jjEqr6iqJ6tiMa9nK/KXqrK3N8tHyq9/4M3X5GWvFhrdXdr3qDLrY96X1317FlULzTnlQ/sPPDUy7yme8x03XqP5wjVdmE+vcVWbevmWmQu+Hpaq429UG+SXHZXvFuuV/Qeeqswza4F0+w1Xp/VNFnO+Xqyqz/z9u+/gIV023xx6f1+pbivnEkGgobzkq08eG4qXu3bvVC1QZdv81986OnS+K7leZ3udce6qrvflW2bO6h74bY2L7b1ZDlF8bX62NpTz3nHjNVrIcst7vvKEFuablTnHjs0tSUll7vnVJ49V9h+KcV7s11blU6Py7b17FpW4ZKA8+7reGDe83907tXVuuMwsbG5p/4Gnhq7zltm6Lt8yM1yG3rpLl2+ZmbryMa4vh4vHNMfBllZd9dCoHhptaFnVQ6ON2f/10GhTy2quabWpZXVJK/1/U8uqFhptyF73y9VCo1ogLWxuKbDSXNNqpmHVrC9tr1lPt+f75ZtaVhtbNu+7bci2749lppH+v7C5JamiDtqzqL/+1lEtzLd0955Fjao3N5dyv/nZWmXdW5VnTkNdhPNrubHme962S9vnGnlusH1jY+QYQ7E/8pJLGqpnfZ7isvXQjM0zy2Nul803B9rul1zSGDvecfsNVysMVDlOWMzpper+f3H8Ic1d0rz5r791VJfNN7W5ol/qc4fiOh+66dqBHKgqlyrn4T6fKfd5q8bv9u1Z1F88ePiC7MtVxeRyOd49b92lHdn4rB87KK/jx87K97vYT6vqmxfjb/NsbSD+qurWhfmm4iQeeq+YF/vXyrlpeX979ywqsKr8jKVYTrZvqOfPfQwvbG5VHkNxrMA/HjfeRrswXnHMYCHrv4+Lw4X5dFz+zpuvHXjNWjcyDrdvqOfjVKP69eUxgsvmm5Jc5WcLcRIPjEvk71WMpxXHsoqftVWNme3bs6jtG+p5mSqfc/nYb7/hakUVZcWX5/J5NkKTt0fEKLA+mOLXp68X2WSMb0q6TukkjQckvcU597XCMr8o6R86595ljLlJ0j91zt243LZ37drlDhw4UPlekjgdO9VTL4rVyr56sR8lMsYoMJK1Vltm67IVf/VQXFdKv6ousDb7ukYnI6N+nMhaow0Nq07fqZ84JYlTaI2MkWInNcN0nV6ULjtbtzrdSxQlTs3QKnaSMU5WJl+/FlhZI3WiZGCZJElnIAfWqBYY9eN0X904UT2wSpwUJ4msMbLGH6WTMWbwPSvVA6tOP8m3Z006o3tjK1ArrOl4uy8jp26ULhMGVtvnGgrD9To/6Lxbkz+FGRe/ktTpRDrW7inK4mpLq65mM1SSOL3Y6epkN5ExknPpT/jUgzTe0pBeitFaFpP92GmuYXWq5xTFSX7vjTEyWoo5Y4x6caLEOQUmjTfn0q8/jRMna43q1igIjLr9RP3s+BqhVSdKlCRO9dDKSmpH6X4aoVVgpXYW/6E1amXlIU6catYoDIzkpMg5RUm6b39+PtYDYzRTt2r3lva7qWXVi5WXrdAazTWsTnbTbTdDq3527MXyk59LkA1GNevq92M9e3rpmm+dqSsIrJ473UuvSb4Nq/lWTcc7fXX6iRqBUeyUX9dGaBUGJj2mOBlbhqIo0ZGT3YF1rTV5nVULrUJr1M7+OmBUvVWwZn/KtVwMn4vidfHXz7n0N/uKcR8YI2uNelGiZi1QFKdx4OM7dlLNGsXOyTlpJou7WmCymchpHEdZ3CaJU+S3m9WNzZpVnEixSxRk9bWPp9AadbM4b9asulGSH5s1S/FWfl4sS8rKp7WSS9KyZrNtG6Xx38vq+k60FOcbmlYvdgp1uZXiJG17fP3dyNqhuNA+hYFVr7CdZi1rE0rn7f9vhFaJpHpgdLob58fXyq5LP07GxmbVvVymPVkXdfBqKeYY9TBI65J2P39evo5J4vTsqa46/USBkVr1QBsbNZ3o9tXO/oK5Flq1akansnYhMGYgLwmD9Fu1elFadwbWDMRJmOUevSyW66FVP4uRWmA1UzdDbY6P5/QXcFyWa6TbMnJ52WvW02V8/Z/W91bdKFY9sIqdUxQPxnziXF4+a4FRL0rzrCCLyWJ9HsXp+ad1pJVzaUwW85tGaNWLE0XxUt3glF6XTj9WaK0Co7yecJLqWd3bjxIlTuonaRvUqgfa1BpbD18QdbBXjtdxbZCPVckpyu5ZM7TpX9VlsWOtlCRSLTTqR24gJ4iTdBv9xKmV1Us2Wy+vowttra8bjTFqZTlzL87yisCqWTPq9l1ef/r82u9PGozLmYbVqW6S19P+2BqhVZLFRpLFf7FtnmsGOtmJ8/zeGLNsvXgu13kNXFAxXKXqeks6q3vgt5UkiWKXtpXFunWmbtXN+l3F/CIMbBpnhXw9rZPSmJxrBIqyOPQ5Q80aNbK4lpTnI7XAaraetgGNrOzkOXHT6mRnqY33bUScOJlCnRoGRqEx6mT5drNu1Snk1jP1dLs+P3BOaZugdHvNWtpOFMtNL17KiYxJj78Wpvlx4pyatUBbZxv5dU4Sp+fbvbRty/KvrbONs7k36yKPGNWXw8XlLOJg3dTBnU6kThJJksKsnxFaqZ/9+mHNSomG/4qs3ZeatfREomyddl8KA6nbd2rWfS6W1iXyw5gmrV/aPan4ucLz7URzjXQ8wWSLR8lSTtHtOzWyPNhf59mG1Yl2rFqQrpe49Dh7WX7s+92J0vw3KdWReXsfWDnnBsZKzrSNvwitizp4tYwaay7GRDE3MNlYhY+7Yl87zsa6rDEKAymKC7lslq86pflquW9fC60CLY251YP022ja/aV9hVm72+6leUCj1Peq2XQsxer/b+/e4y0f6/6Pv957ZsyMIefIIYQSyVRCxU0R0l24o8wt0YNON5VKSUdUd0Vu3RVKDqNut0MO3YpCDj/KIWIMQxihSJGJThpz+Pz+uK7v3t9Zs9baa++91l7ru/b7+XjMY/b+Hta6vt/9ua7vdV3f63t9YeGSGOw3Ltp8q04f4Olnh+rK03JfSu2xTJ08MDgLTvHzjHxuUn4dapcWbYKpkwd4dtGSwT7sqVMGBuvlM1aYxMJSf0XRd7N0abAkt0OLfvpFS5atc620whSe+edzPLtoqE0wY6p45tmhtnS/teWWi8kl6TwV52uylOudQ3G6dGnuWyOdz6IvebBeWO6zjWX7Z4t+qKIMLuqp0ycPsHBJDLbFV8h9EEW9uNxWL/piJynVZyF9TvFZkwfSwL5yH/K0KQODfXdFf1S5T3rV6QP8beGyMTclf8dQPklletGHN9QvkPriij6UFSYPIGDh4qVMnpRmwC76pGdMncRzS1K+b1QGdFlPx3ARryL9vYt+noHchzWpFFeTBsQq0wf4+8JYpuyaPnmAgYF0H6C2f3jSwNA9kNp2/bQpKQaLmCzKwUkDGmwPldtR06YMsHjJUBoDDbbdpk0e4LlSW26wL4t0D69I1/QVBlLbrebe3ox8P3Hx0mB6TbtrlemTWLgkWPjcULxPGdDgMS4p7gPV5OdFS5bmOtAknjdt2etRj/QztKqn6hEbffKyEX/2w19582iSZOOkw3/ThvHbkz0BEbFY0uHAFcAk4MyImCfpOOC2iLgUOAP4vqT5wAJg/7F+78CAWGvl0T3ZO9J9VxnBZ682Y+TpGW+jPW/WXtOmTWa9Oh07AwNilRWnscqKo/vc0e7XFjXxv/oo80NtPppRZ9lojnPq1MmsN3X5c/78502ru/3zpzSfamzVFtIwefIA6646ffgNK1B2tFOj87LeamMP4CqUw616Xguh006txHStlmN8gqhXx2h23R0YEM9fefkyaPXJU5crF0bz92nVmK8dfZTvJpKR1IkbxWpPG2seyvuvMsYibiztFhu5Rud7NH+DXvrbNSqnRx2fIyy3W71ONKr/DwyI1Wcsf22DarZPG7XlbGKpchxMmzaZaaPoZpxRpypQb1kjtVWJVvetvYZ3sl5sE1cr1/221w3G2o4aw/61+W+0fXitfVl7PmaNlZYvNMZaV+9lo4m3gQG11EfTqO9s3PqhRhgTI7nWWHeMJl7rZGmgv/p2a2N9pTrLGmmWn3uprWo20fVsizAiLgcur1n2udLP/wT2G+90mZmZmZmZmZmZmZmZmZmZmbXThHmnhZmZmZmZmZmZmZmZmZmZmVkv8uANMzMzMzMzMzMzMzMzMzMzsy7y4A0zMzMzMzMzMzMzMzMzMzOzLvLgDTMzMzMzMzMzMzMzMzMzM7MuUkR0Ow3jStKTwCPdTkeHrAn8qduJ6KBePr4/RcQenf6SEcRvL5+rdvDxtde4xC90rAyuSjxUJZ1QnbQW6exWGVyV81SoWnqhemkeTXqrXgYXev1v1cvp6+W0wfDp6/UY7vXz24zTPj7clus9Pgetn4NeLIP75e/XL8cBvX0sbssNr0pphWqld6xp7cUyeKSq9PcaTr8cy3geRz/EcDNVjomqpr0v72tMwHrwWPgctKEtN+EGb/QzSbdFxDbdTken9PvxtVO/nysfn5VV5XxVJZ1QnbR2O53d/v6Rqlp6oXpprlp626nXj72X09fLaYPeT99wqpx+p31i8rnzOYBqn4Mqp72sX44D+utY2qVK56RKaYVqpbdKae2UfjoH/XIs/XIcvaDK57Kqaa9quttloh8/+BxAe86BX5tiZmZmZmZmZmZmZmZmZmZm1kUevGFmZmZmZmZmZmZmZmZmZmbWRR680V9O63YCOqzfj6+d+v1c+fisrCrnqyrphOqktdvp7Pb3j1TV0gvVS3PV0ttOvX7svZy+Xk4b9H76hlPl9DvtE5PPnc8BVPscVDntZf1yHNBfx9IuVTonVUorVCu9VUprp/TTOeiXY+mX4+gFVT6XVU17VdPdLhP9+MHnANpwDhQR7UiImZmZmZmZmZmZmZmZmZmZmY2CZ94wMzMzMzMzMzMzMzMzMzMz6yIP3jAzMzMzMzMzMzMzMzMzMzPrIg/e6AOS9pB0n6T5kj7Z7fS0g6QNJF0r6R5J8yR9OC9fXdJVkh7I/6/W7bT2mn6KCbBwqQAAIABJREFUh4kSB5ImSbpD0o/z7xtLuiX/Dc+XtEK309gNw8WypJMkzcn/7pf0dGndktK6SzuczjMlPSHp7gbrJekb+TjmSnplad1BOY4fkHRQJ9PZYloPyGm8S9KNkrYurXs4L58j6bYup3NnSc+U/safK63rWBlYtbwqaVVJF0r6taR7Jb2ml8tPSR/JZf3dks6VNK3XznG92Gx0Tpvl/SproWzeUNLV+Zivk7T+OKZt1OVxD6Rtc0k3SVoo6cjxStcI0tfw+tCrJO2Xy5SlkrapWXd0joP7JO3erTS2QtIxkh4rXfP27HaamunkdbjftFCeTs3Xvvn5WrjR+Keys1o4BwdLerIU/4d2I52d1MvXrpGqcv5XH/Y9qGJtl06r0vlQhdpx6uE2XL3ytdF5rFJZ2061+aKq6uWZbqdptOrlqW6nqQqqWp9qId0N+z+7qVG9qWabnjzn7TJcvVduy7ktx9jygQdvVJykScDJwJuALYBZkrbobqraYjHwsYjYAtgeOCwf1yeBqyNiM+Dq/LtlfRgPEyUOPgzcW/r9q8BJEbEp8GfgkK6kqotaieWI+EhEzIyImcA3gYtLq58t1kXEWzuc3NnAHk3WvwnYLP97L3AqpE4D4PPAdsC2wOfHoQNmNs3T+hCwU0RsBXwBOK1m/evzOd1m+V3bajbN0wlwQ+lvfByMSxlYtbz638BPI2JzYGtS2nuy/JS0HvAhYJuIeBkwCdif3jvHs1k+Nhud07p5v8pazGNfA74XES8HjgO+PI5JnM0oyuNxMpvmaVtAygNfG5fULG82Y7s+9KK7gX8Dri8vzDG7P7Al6ZhPybHdy04qXfMu73ZiGunDtkjHtHiuDgH+nK+BJ5GuiX1jBPFyfin+Tx/XRI6P2fTutatlfZD/+7HvoWptl06r0vmoRDuuAm242UzgtluLavNFVdXLM5XTJE/Z8GZTzfrUbEbR/9kDGtWbynr1nI+Z23Juy5XMpkNljwdvVN+2wPyI+E1EPAecB+zV5TSNWUQ8HhG355//Sqp0rUc6trPzZmcDe3cnhT2rr+JhIsSB0hPJbwZOz78LeANwYd6k0sc3BiON5VnAueOSshoRcT3pplsje5FuZEZE3AysKukFwO7AVRGxICL+DFzF8BX2jqY1Im7MaQG4GRi3J+Zr0jHcOW2kY2Vg1fKqpFWAfwHOAIiI5yLiaXq7/JwMTJc0GVgReJweO8cNYrPROW2U96uslTy2BXBN/vnaOus7ZgzlcdfTFhFPRMStwKLxSE+d76/E9WEkIuLeiLivzqq9gPMiYmFEPATMJ8W2jV1ftUU6rJVzVb6+XAjskusf/cLxQm9fu0ao0n/Pfut7qFrbpdOqdD4q2I7r2Tac227N1eaLqmqSZ6qqNk/9vsvpqYSq1qfG0P/ZVU3qTWU9ec7bxG25itf926WTZY8Hb1TfesDvSr8/yvIFZaXlKYVeAdwCrB0Rj+dVfwDW7lKyelXfxkMfx8HXgU8AS/PvawBPR8Ti/Hvf/A1HqOVYlrQhsDFDNwsBpkm6TdLNkrrdqdHoWHo9vx4C/KT0ewBXSvqVpPd2KU1lr5F0p6SfSNoyL+vkOa1aXt0YeBI4S2ka1NMlzaBHy8+IeIw048BvSR1+zwC/orfPcaHROe31PD4arRzTnaTZDgD2AVaWtMY4pK0V/fg36Yba60PVVDEODs9TbJ45DrN0jUUVz223tHKuBrfJ18JnSPWPftFqvLwtx/+FkjYYn6T1lKrkq6qkc1h90vdQtbZLp1XpfFSmHVfRNtxEarsNpzZfVFWjPFM59fJURFzZ3VT1jSrn8Xr9nz2jpt5UVuVzPhy35dyWa9Wo84EHb1hPk7QScBFwRET8pbwuIoJ0M9H6XL/GgaR/BZ6IiF91Oy0Vtz9wYUQsKS3bMNKrPf4d+LqkTbqTtGqS9HrSzbmjSot3iIhXkqb7OkzSv3QlccntpL/x1qRX5vywk19W0bw6GXglcGpEvAL4OzVT6/ZS+ZlvRu5F6nhZF5hBh2ei6YReOqdddCSwk6Q7gJ2Ax4AlzXexqmhwfegaST9Teh907b9KPfExzHGcCmwCzCR14p7Y1cSaja8fARtFehXXVQw9vWbWEf3Q91DRtkvHVPB8VKYdV/U2XK+cx26oYL5oZtg8UxX18pSkd3Y3VdZl49r/OVLN6k1muC03JpO7nQAbs8eA8oil9fOyypM0hVT4nxMRF+fFf5T0goh4PE8v80T3UtiT+i4e+jwOXge8VdKewDTgeaT3NK4qaXIelVn5v+EojSSW9wcOKy/Io9WJiN9Iuo40AvjB9iezJY2O5TFg55rl141bqhqQ9HLStJlvioiniuWlc/qEpEtI06Nd3400lhsEEXG5pFMkrUnnysAq5tVHgUcjohj5fiGpA6NXy89dgYci4kkASReTznsvn+NCo3Pad9dkWjimiPg9eeaN3JB/Ww9NW9uPf5Nx0+j60E0Rsesoduu5OGj1OCR9F/hxh5MzFj13bntYK+eq2ObRPHX2KkBP5L02aeWaUj7e04HjxyFdvaYq+aoq6Wyoj/oeqth26aSqnY8qteOq2IabSG23ZpbLF5L+JyKqOFCgUZ6ponp56rXA/3Q1Vf2hknm8Uf9nRPypm+mChvWmskqe8xa5Lee2XKtGnQ8880b13QpsJmljSSuQbmJe2uU0jVl+/9MZwL0R8V+lVZcCB+WfDwL+b7zT1uP6Kh76PQ4i4uiIWD8iNiL9ra6JiAOAa4F982aVPb4xaimWJW0OrAbcVFq2mqSp+ec1SY3Se8Yl1fVdCrxLyfakaQ8fB64AdsvpXQ3YLS/rGkkvBC4GDoyI+0vLZ0haufiZlNa7u5NKkLROLh+QtC2pPvMUHSoDq5hXI+IPwO8kvSQv2oWUD3q1/PwtsL2kFfPftkhvz57jkkbntFHer7Jh85ikNSUVbYyjgTPHOY3N9OPfZFw0uj5U1KXA/pKmStoY2Az4ZZfT1JCWfR/qPnTx+tuCvmqLdFgr56p8fdmXVP/opyeEW7mmlOP/raT3aU80Vbl2VTr/91PfQxXbLp1UtfNRsXZcFdtwE6nt1lCDfFHFgRvN8kwV1ctTE7Hu0wmVzONN+j+7qkm9qayS57xFbsu5LdeqUecDz7xRcRGxWNLhpBt+k4AzI2Jel5PVDq8DDgTukjQnL/sU8BXgAkmHAI8Ab+9S+npSH8bDRI2Do4DzJH0RuINUGZpQGsWypOOA2yKiqAzsD5xXU/l5KfAdSUtJldqvRETHGm6SziXNoLGmpEeBzwNT8nF8G7gc2BOYD/wDeHdet0DSF0iVHYDjImJBp9LZYlo/R3r/3im5bbA4v35mbeCSvGwy8L8R8dMupnNf4AOSFgPPAvvnGBjvMrDX8+oHgXNyJfo3pNgboAfLz4i4RdKFpCkhF5PO52nAZfTQOW4Qm42uSXXzfpW1WDbvDHxZUpBm5zms4Qe22WjL415Im6R1gNtIT4MulXQEsMV4TT06hutDz5K0D2lq2bWAyyTNiYjdc8xeQOrUXQwcFsu+eq3XHC9pJmla74eB93U3OY31YVukY1osT88Avi9pPrCAVO/tGy2egw9Jeispry4ADu5agjukl69dI9EH+X8i9D30ettlvPXy+ahEO67X23ATve02wdTLM5XTJE/ZMKpanxpD/2e3Nao3vRB6+5y3g9tybssVOln2qDfyupmZmZmZmZmZmZmZmZmZmdnE5NemmJmZmZmZmZmZmZmZmZmZmXWRB2+YmZmZmZmZmZmZmZmZmZmZdZEHb5iZmZmZmZmZmZmZmZmZmZl1kQdvmJmZmZmZmZmZmZmZmZmZmXWRB2+YmZmZmZmZmZmZmZmZmZmZdZEHb5iZmZmZmZmZmZmZmZmZmU1wktaRdJ6kByX9StLlkl4s6e4G20+W9KSkr9Qs/1dJd0i6U9I9kt6Xl79E0nWS5ki6V9Jp43FcVeHBGz1M0pIcuMW/jSQdLOlbNdtdJ2mb/PPDktasWb/cPk2+cyVJ3yllyOskbZe/u26mtP7UjfjL28+UFJL2aGHb90t6V53lg/EqaRtJ3xjmcx6WdEPNsjnDxbyknSX9OP98cL44zckXofcMl37rvF6K43rlqKRjJB2Zf54t6aGczjsl7VKTvvvy8lslzSyte4ekuZLmSfpqafkLJV2bK0dzJe1ZWne0pPn5M3cvLT9T0hN10rm6pKskPZD/Xy0v/3jp3N6dz/fqrZ4na65L9YCHJd2V/90j6YuSptVsc4Skf0paJf/+/LzfOqVtTs5xtnPOC4eW1hX5o4j980vH+LCkOXn5FEln57TcK+no0mfskeN3vqRPlpafk5ffneN5Sl4uSd/I28+V9MrSPj+V9HRRnlv7dCmGV5J0qlJd9nal+ux78rqNJD1bk6Z35XWrSPpejpEH88+r1NnvnrxuSuk7lytTJU2T9EulcnuepGNL228s6Za8z/mSVsjL/yWnebGkfWuO6yClMvgBSQeVln9J0u8k/a2V82Ot61L8NozDvH5LSdfkWHtA0mclqfQ9RV10nqQLJa2Y1x2jVO5uWvqsI/KyIu2zcnk7N5eLa5b2fax0Htpenyitf3W9+LfekOPlxNLvR+b4+HQpPsr55kMNPqc2puZIWlWpzvBMadnPSvu8S+nafpdS3baoQ+yX431pEct5+QqSzsrb3ylp59K6ol5dfM/zO3LCrCFJe+d42jz/PqBUTyv+xrdK2rjJ/qNqv48hvXU7otvwuXWv3Sr1cyi1Ef8haeXS+q/n87dmvf07TdKnuvG9/aRNecBtNuuqNsZxEVevVamftbTdbOW6oZatd2+sVKfcXdKKOa7uyt//c0kr5e0axeHhedky5elo4rDJZx2QP+MuSTdK2nq059vaS8vflL5W6Xo7R9ICDfXP/qzB/k37CPI2X1eq8w7ULH+TpNvyfnco16/V4EZ2o3JW0gY53fco1Yc/XPqORv24m0u6SdJC5fK9tE/dvFJa/w2532HCkCTgEuC6iNgkIl4FHA2s3WS3NwL3A/vl/cn54jTgLRGxNfAK4Lq8/TeAkyJiZkS8FPhmRw6mojx4o7c9mwO3+PfwOHzn6cACYLOcId8NjLlBKGnyWD/Dxl034g9gFvDz/H9TEfHtiPjeMNvcFhF1Ow5rrCxpAwBJL20ppcs7PyJmAjsD/ymp2cVskPNHR/V8HNf4eI6hI4Bv16w7IFdyTgFOAJC0Rv55l4jYElhHQ4M+PgNcEBGvAPbP+yFpi/z7lsAewCmSJuV9ZudltT4JXB0RmwFX59+JiBOKc0uqwP2/iFgwwmO2xroVv6+PiK2AbYEXAd+pWT8LuBX4N4CIeAL4CvA1gNy5sWPxO3A38Paa/e8sfomId5Ti6CLg4rxqP2BqTsurgPflBvIk4GTgTcAWwKwc1wDnAJsDWwHTgaID8k3AZvnfe4FTS+k5ATiw1ZNjI9KtuuyfSXXZV5LKtPKgsgdr0lTUI84AfhMRm0bEJsBD+bOW2Y8UW+uTY7pJmboQeEMut2cCe0jaPn/WV0kN1E1zWg/Jy38LHAz8b/mAlAbFfR7YjpQvP6+hm94/ysus/boRvw3jUNJ04FLgKxHxEmBr4LXAf5T2Pz+ndUvgOeAdpXV3kWK1sB8wL3/2ZOC/SeX/y4G5wOGlbU8qnYfL8z5tq0/kz5tEyhtXDnuWrFsWAv+mmhvGEfGl0nW8nG+aDaA/qSZ/PZ2X31BatiukDm5S3Xi3XCfYHngmb383qT5yfc3nvyenbStSJ+KJNR3nB5S+54kRnwkbq9q20juAdYGX57/ZPsDTDfYttKP93qrlOqI7qU4/x3xgL0g3R4E3AI91Oh1NePDG2LUjD7jNZt3Wrjgursc3tvrFktYHfgp8LCKuAD4M/DEitoqIl5HaV4uGicNfALsCj9R8/GjisNFnPQTslM/HF0g3MK3LGtyUPgLYPZdxl5L7Z4v6aAN1+wjydwyQ8sDvgJ1Ky18GfAt4Z0RsAWxDus5D4xvZdctZYDEpD2xBqh8fVorvRu2uBcCHGCr7i3Q1yysoDZpaZuC99b3XA4siYvD+RETcSYrpRmaR+hV+C7wmL1sZmAw8lT9jYUTcl9e9AHi09Pl3tS31fcCDN2yQpE1IncKfiYilABHxUERcljeZJOm7eSTflbkDEUnvURpNe6ekizT0hNdsSd+WdAtwvKS18ki/eZJOl/SIhp7oeqfS04lzlGb+mLR8Cq3f5crTfqQbF29U6ckBpaet5uY4+35edoyGngJ4VV53J3BYab/BUdtKT+MWT2DNlfS20tdfwFAH9yzg3NJnTCvtd4ek1zc7jtwofhDYUNIMpScJfpn3LTpdDpZ0qaRrSJUoJB2loafD2vpUj42fZnE8AjcB67Ww7kXAAxHxZP79Z0AR1wE8L/+8CvD7/PNewHm5svQQqZGwLUBEXE+qyNfaCzg7/3w2sHedbZbJN1Z9EfE34P3A3vnmcVFXWIk0OKg8OOk0YJNcPp4MHB4Ri/K6R4BpktbO+WMP4Ce135fXvZ2hOApgRr6pOJ10I/IvpHidHxG/iYjngPPIHdoRcXlkwC9JDWjy+u/lVTcDq0p6Qd7nauCvYzlX1htyfG7LsnXZJyPiq8PstympE+QLpcXHAdvkzxwUEUtIsVWUw3XL1BxrxVMpU/K/yHH+BuDCvG6wTI2IhyNiLrC0Jom7A1dFxIKI+DNwFfnGeETcHBGPD3durPe1EIf/DvwiIq4EiIh/kAZY1HsqajIwgzQ4qPBDhm7+bUK6+f2nYpf8b0aO0ecxVG9opN31iQ+Sbgb5RnrvWky63n9knL/3aODIiPg9DHb4fTf/fG+p869sC+CavM0TpJtH29TZzsaZ0pPQO5BurBUDyl4APF66dj+ar3fNNGu/T5J0Qu6nmquhqZlXknS10ixXd5Xa5hspPcm6XH9X6fNrO6KLp8a/nPuxbpP0SklXKD3F+/68zc6Srpd0mdLTrN9WaSCR0gxad0q6Wfnhj3I/R3Ze6Vh3Jt0kXFz6jI8qPWl+t6QjSsf069wvd7/SE+m7SvqF0lO42+btmvVXXKz0lPkDko7Py78CTM/HfM4wfyOro415gLyt22w27todxyP0AtJg309HxKWlZYOD2iLivohYSPM4vCPqD84ecRw2+qyIuLF0Dm5mKNatu+relI6IG5rs01CdPgJI1+t5pME/5XL4E8CXIuLXxb4RUQwQanQju245GxGPR8Ttedu/AveybD/Fcu2uiHgiIm4FirK/0DCvKN2nOyGn3SaOlwG/anXjfP9jV9IDRueS4z7SQ56XAo9IOldpRqKiLnwScI2kn0j6iKRV23oEFefBG72taBDNkXTJOHzflsCcfMGpZzPg5EhPcj3N0A3CiyPi1ZGeLLyXoacHIVVKXhsRHyU9MXhN3v9C4IUw+JTEO4DXRRqtuAQ4oL2HZqMw3vEH6enBhyLiQdL0SW8GkLQlqdFZPMH64Tr7ngV8MK9v5LPAM5FGYr+c3KGXXUR+IgF4C+lCUzgMiEgjXGcBZze7IS/pRaSb6vOBT5PifltS5fAESTPypq8E9o2InZSeKNsL2C4fw/FNjsNa1zNxPEJ7kG6yDLduPvCS3Dk3mVQZ3yCvOwZ4p6RHgctJN0UgVeTLo2QfpfFAkcLapZuDf6BmijSlQXt7kPKRtU834ncZEfEX0tMim+VF+5MacTeQYm/tvN1S4AOkGLgv37gru5A0qOm1wO2kp3dr7Uh6WuaB0j5/Bx4ndZZ/LVf6h41hpWn5DiQ9jUMr+1hHdKMue2fRYdjAJlp2qv4dSTf5lqkD55/n5M8clK//29FCbOWbR3NIN6OviohbgDWApyNice32TTh+u2O843e4ONySms6TXNdYSVIxWPMdOeYeI804U67P/gX4ndLTXvsD55c+ZxGpDL+LNGhjC9IsIIXD8w3QMzU060vb6hOS1iM9mXZqox2tZ5wMHKDS63xG6SOl/HVtafmOpeWfzstG1HGY3Qm8Vel1FxuTBkZtUFp/Vv6OwVcP2bjZC/hpRNwPPCXpVaSBGG/Jf5MTJb2ihc9p1n4/hNTufzXwauA9OQ7+CewTaWau15NmZCn+/nX7uxp1RJf8Nvdj3UCadWhf0tOvx5a22ZbUFtsC2KSU7hnAzbn9fz15xpg67gfWyuXvLFJdnJy+Ysbc7fL3vqd0/jYFTiTNcLA5aRDgDsCRDM2e0ay/Yiapr24r0vVlg4j4JEMz7LjfbnTalQcGuc1mXdCuOL42b3/LCL77bOBbEXFhadmZwFFKr4P4oqQiL4wmpjoVh4dQZ0CUdcVo6pYN1ekjgKGBpZcAb9bQK1WafXejG9mNytlyGjYivY6iyEtN+3HraBb3hwOX+qERG8a/AtdGxLOkesbeeeAPEXEosAtpkNORpDKbiDgLeCnwA9KAp5slTR3/pPcmD97obeUpR/fJy6LBto2Wt9NDETEn//wrYKP888sk3SDpLtKgi3In9w9KHZA7kBuZEfFThp4E24XUmXJr7mzchXTj27qrG/FX7og4j6GOkTeQYulPMDhib1CuzKxaanh+v8Hn70rqcCR/TnkE+FPAnyXtTxqE9I/Suh2A/8n7/Jr0RMKL63x+0WF+LvC+nM7dgE/m5dcB08gDl8hP0ZbSdlakpyiXO0YbtV6K41a+9wRJ95OmzK99UvwcSQ+ROthOhsEY/gDpBswNwMOkAXBFOmZHxPrAnsD3VfOexdGIiKhzLG8hPQ3suG2vXqkHlG9qzCI9ab2UVBnfbzABqY5wN/kVPTUuyNs2m6Gldt22pHheF9gY+FgeHNeKU4DrR/vkhLVNV2NY0qdzZ2B5BoHa16a0GiOb5Gv5H0lPlM0dbof8FM1M0mDmbfNNc6uOXimDR6J4hd86pIEYH69Zfx7phs7epI5EYPDmyQdIHX7rkl6bUryz/lTSzcaZpA7DE9uR0Jr6xNeBo4YZeGU9IN8g/B5puuWxKL82pTyrYfm1KV8aw+efSep0vo0UXzcyVEc+IA/K3zH/8zT842u5tlJEPAq8hFTuLAWu1tCrIBtp1n7fDXhXvm4XAyc3I9Vp/1PSXNKMhesxdDOjUX9Xw47orHjq+y7gloj4a6RZEReWbrr8MtKTrEtIdd0d8vLngB/X+c56LiaV39uR2n2FHYBLIuLvkWZguJgU18Ux3ZXL1nmk6dMjp7X4rmb9FVdHxDMR8U/gHmDDJumz1rUrD9Rym83GU7viuHhtynb591bq2j8jPai04uDKFNcvIs0OsDrpHkOnX6nVMqXZbg4Bjup2Wqyt6vYRSFqB1A/7w1x3voU0m2ZTTW5kNy1nlWbCuQg4In9f7efW68dtiaR1SdeFbw63rfWdeaR7tq2aBewq6WFSvXYN0j09IM0kExEnkV5H+LbS8t9HxJkRsRdpZjn3m2WTu50AG7GnWP79UqszNOXtWMwDtpY0KerPvlEecb2ENE0TpKcL9o6IOyUdTLq4FP7ewvcKODsijh52S+u2jsVf7gB5G7BXfspKwBqSVh7rZ4/A+aSb4gePdv+IOLxmmYC3Rc10vpK2o7X8Ye3XrThu9L0PlX7/eERcKOmDpE7nciXpAFLl5wRSpbl4d+2PyE+aSXovQx3ThzA0rf5NeST4mqSncctPHq7P8O9M/qOkF0TE40rTRdZOab4/fmXKeOlkPWA5OXY3Au6XtBWp4/uq/JDiCqT4/VZpl6Us/8oHIuIPkhaRKukfJj3NVf6eyaSYLsf8v5Oe5lkEPCHpF6Qpz39HkxiW9HlgLeB9pW1GE/fWGZ2M4XtIddmBiFiab/x9SdLfWthvZrEfDL6jdmZeB3nQh9Ir/34h6a2RpukdNrYi4un8ZPkepBvfq0qaHGn2jVZi8TGWrV+vT7rBYuOv0/HbLA6fD/xLeYfcafe3iPhLefKAiAhJPyI96V1+Fd+PSfWI22r2mZn3ezB/7gXk17FExB9L3/ddhm40trM+sQ1wXk7PmsCekhZHRKNZyKy7vk56Ivuscfq+ouPwmuE2LOTydfD1LpJuJM1eQEQ8lv//q6T/JXWIf6+dCbb6lF7p8AZgK0kBTCK9Uuzjkaa3/wnwE0l/JA0yu3qYj2zUfhdpVs4rar7/YFId8VURsSh3Lhczajbq75oF7JC3haGO6Ktq9lta8xlLGepzrb1hUvy+KN9QKb6zWR/t+aS24NkRsbTFCWNq01NOa/Fdzforas+J+5DHqAN5oPhct9ls3HQqjrNW6trHkwZe/kDSXvmaX7xC6GLgYklLSTfPb2TkMdXWOJT0cuB04E0R8dRoP8faah5ppqyxatRHsDuwKnBXLodXBJ4ltaOKeu2d9T4w0msCzwTOlHQ36UZ2o3L2N3kQ/kXAORFxcemjhuvHrdUo7l9BmslrfnEskuZHxKatnCCrtGtIg57fGxGnwWB5ttwMjEozge4IbJCvA0h6NzBL0k3ANhFxXd58JunBaCTtQRosvEjSOqR6tq/7mWfeqJ5bgdflYEbSNsBUlp3WaFRyZ91twLHKpbHSVPzDTfm/MvB4vlg0mzbxF6T3IiJpN4YqY1cD+0p6fl63uiSP6O9NHYs/0owrcyNig4jYKCI2JFU+9iFdLPaTtEb+3tXLO0bE08DTkoonWBrF4VWkV6CQP6e2QXAJqRFwRc3yG4rPlPRi0pMo9d6tXM8VwAdLearRtIFXAe8uRo7XHqO1VVfiODckH5f0hvy9q5Nu5P28zud8CxiQtMzI7Ny591lge0mb588pys7VgP8gNQohTaW3S173UlLH5JOkp8P2lzRVafrgzUjTljVzKXBQ/vkg4P+KFUrTZu9UXmYd1cn4XYbS6P1TSE8L/JnUeX1Mju2NImJdYN0RXLM/R3qyut4A0V2BX+endQq/JY/SVpq+eXvg16RzsJmkjZWeaNif/NSjpENJDeVZNU9wX0p6AlOStidNpe0pH7ujk3W9JECyAAAG7klEQVTZ+aS67BeVn4pVGrjW9A5H3u8O0ivaCp8Bbs/rytv+iXRTuxh0XLdMlbSW8hO3kqaTOsF/ncvxaxnqLFqmTG3gCmA3Savlsn43lq+r2PjodPw2i8NzSDcQd83fPR34Bo1ftbcD8GDNd/yD9MRf7YwGjwFbSFor//5G0pPs5M6+wj6kp3WhjfWJiNi4uLaQpgX+Dw/c6F2RZlq7gGVfl9pJXybNTlfkuxXy9b4hSSvmugOS3ggsjoh7lF6jsmZePoU0q8LdTT7K2mtf4PsRsWHO8xuQbirvqPRkZzFo7eXkTt1hNGq/XwF8IP+NkfTiHA+rAE/kDuLXM8xMEqWO6BeWyqjDWP7VKcPZNtdbB0ivIanX/msqIh4hzcBYO1vCDaTZQIqY34dlZ+YYTqv9FWWLNDT9u41Mu/OA22zWDW2P45IHSPH60vw5GwJbk14jWHYE6ZWAZ+R4eV3Rx5vjbYv83Q3jsIm2xaGkF5IGlBwY6RUz1huuAaYqPQAHpJvSSq9UHbE6fQSzgENLdYeNgTfmPv8TgE/l+wtIGpD0/vzzHqW6S/lGdt1yNl+7zwDujYj/qklWw37cBurmlYi4LCLWKR3LPzxwY2LIfVf7kGbTeFDSPFK77A+kV7I9WvzL211TDNzI/o80U/ck4BOS7lOaqeZYhgZe7wbcLelOUp304xHxh/E4virwqOmKiYg/SvowcHmuCP2N5Su7c5VGmELqVJkLHCxp79I229dUtguHkp4InC/pWdLI1trpdmt9ljT905P5/0YzJRwLnCvpQOAmUkb/a0T8SdJngCvzMS0iNYhHWsGzDutw/M2iNH1zdhHwgYj4nqQvAf9P0hJSx/bBNdu+mzQqNYArGxzCF4GTlUauLiHF5OCo1Ij4K/lVFVr2SZZTgFOVXg20GDg4IhaqtaddvkB6Om1uPmcPkToJlxERP5U0E7hN0nPA5Qy9h9baqFtxTHqi712kGCwq1ccWT7nWpDEkfRH4BDWdkRHxrKQTSWXzIcB/S9o6rz6u1CD8GPBdSR8hPd11cK54zVN6ovYeUjwfVnTMSDqX9HT3mrny9fmIOIP01O4Fkg4hlc1vLyVpH+DKiPBMMuNgHOoBkN47K9Ig30tI5RikxtueNdtekpfXvuanXtpvbLK63uwtJ5PeST+PdPP9rBiahvJwUt6YBJwZEfPyPt8mxehNuYy+OCKOI5WpewLzSdNqv7v4Ekk3kN4DvlKO+0Oi5klNa59xqsueQKrLPkV6wuUTpfXF1KaFMyPiG6Ty9JuSijL5JhrfmPwhcIykHSPihnplqtIN77OVBpEMABdERDFjwVGkWQa+SKrTnAEg6dWkPLUa6X3Rx0bElhGxQNIXSB0qkMr6BXmf40lP4qyY4/f0iDimQbptjMYhfhvGYb7+75XXn0wq/77Psk/SvkNpMPMA6ZURB9c5hvPqLPu9pGOB65WeuH2ktO/xuY4apNezvS/v0+76hFXLiaT3X4/WRyS9s/T73o02jIjLJa0N/CzXT4L8nmRJ+5BmpFsLuEzSnIjYnTRTzRU5Lz7G0KtRpublU0h56GfAd8dwHDYys1i+zngRcDawQEPvuP4ly5ZtdTVpv59OmoXg9hwzT5Ji7BzgR7ldfxvpBnMzjTqij9fI3sd9K+l4NiUN4KxtL7YkIr5TZ9ntkmYzNHju9Ii4Q9JGLX5sS/0VNU7L298eEc0e4LLltTMPuM3mNlu3tLUsL8t9re8kxdQ00j2CQyPimZrtQtJBpJkMjie9DurUUp64DLgob1c3DiV9iNROXIdUpl0eEYcyijhs8lmfI92APyXH+uKI2GYk58TaL8fFPsDXJR0F/JPUzjliDB9b9BHsRHpQ7/2l7/u7pJ8Db4mI8yUdQbpHtiKpXlv0E+xG6uP9Z/7945FmRKpbzuZ234GkGT6KPo5PRcTlNGh3KQ0KuQ14HrA0p2WLSLMyNiqzbYKKNBNMvTZ7vUG8Z9fsu4DURoPl6yXFNh8FPjqWNPYzxeAMfWadlStvSyJisaTXAKdGeiezmZmZmZmZmZlZ35C0M3BkRAw3IMLMzMzMzAzwzBs2vl5IGvE3ADwHvKfL6TEzMzMzMzMzMzMzMzMzM+s6z7wxQUm6hTRlaNmBEXFXN9JjE4vjz/qB49iqzPFrVecYtipz/NpEIOnTwH41i38QEV/qRnqselxW2kTnPGD9wHFsVSZpK9KrKssWRsR23UiPmU0cHrxhZmZmZmZmZmZmZmZmZmZm1kUD3U6AmZmZmZmZmZmZmZmZmZmZ2UTmwRtmZmZmZmZmZmZmZmZmZmZmXeTBG2ZmZmZmZmZmZmZmZmZmZmZd5MEbZmZmZmZmZmZmZmZmZmZmZl30/wE+NQYmDiICFgAAAABJRU5ErkJggg==\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "#Scatter Plot Matrix\n", - "#A scatter plot shows the relationship between two variables as dots in two dimensions, one axis for each attribute\n", - "import seaborn as sns\n", - "#sns.set(style=\"ticks\")\n", - "sns.pairplot(Train)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Preparing data for machine learning\n", - "\n", - "
\n", - "\n", - "## ??" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Feature selection" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[0.457 0. 0.348 0.545 0.33 0.483 0. 0.005 0.508 0.415 0.182]\n", - " [0.435 0.116 0.322 0.489 0.276 0.458 1. 0.011 0.421 0.586 0.475]\n", - " [0.467 0.116 0.246 0.523 0.288 0.565 0. 0.011 0.442 0.273 0.666]\n", - " [0.457 0.089 0.275 0.399 0.403 0.647 0. 0.011 0.405 0.153 0.424]\n", - " [0.511 0.183 0.323 0.373 0.342 0.595 0. 0.011 0.5 0.196 0.536]\n", - " [0.457 0.165 0.451 0.614 0.333 0.524 1. 0.009 0.596 0.479 0.217]\n", - " [0.413 0.148 0.321 0.608 0.276 0.492 1. 0.007 0.587 0.536 0.485]\n", - " [0.391 0.126 0.24 0.574 0.252 0.328 0. 0.002 0.56 0.574 0.214]\n", - " [0.5 0.056 0.226 0.3 0.442 0.724 0. 0.003 0.357 0.062 0.81 ]\n", - " [0.543 0. 0.296 0.391 0.555 0.467 0. 0.006 0.339 0.545 0.306]\n", - " [0.391 0.074 0.4 0.482 0.376 0.48 0. 0.009 0.557 0.364 0.355]]\n" - ] - } - ], - "source": [ - "##Rescaling \n", - "from numpy import set_printoptions\n", - "from sklearn.preprocessing import MinMaxScaler\n", - "\n", - "###rescaling the data\n", - "array = Train.values\n", - "# separate array into input and output components\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "\n", - "##Scaling the data so that it's within the range of 0 and 1\n", - "scaler = MinMaxScaler(feature_range=(0, 1))\n", - "rescaledX = scaler.fit_transform(X)\n", - "# summarize transformed data\n", - "set_printoptions(precision=3) #number of decimal points\n", - "print(rescaledX[0:11,:])" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Num Features: 4\n", - "Selected Features: [ True True False True False False False True False False False]\n", - "Feature Ranking: [1 1 4 1 2 3 5 1 7 8 6]\n" - ] - } - ], - "source": [ - "#feature selection using recursive feature elimination\n", - "\n", - "from sklearn.feature_selection import RFE\n", - "from sklearn.linear_model import LogisticRegression\n", - "\n", - "# feature extraction\n", - "model = LogisticRegression()\n", - "rfe = RFE(model, 4)\n", - "\n", - "#I tried to test for the performance of the model with more features and the results hardly changed.\n", - "#I used 11 then 7,and finally 4 features. I selected the features ranndomly.\n", - "#As a trade off for faster performance , I decided to go with 4 features.\n", - "\n", - "#Accuracy at 11 =91.72482552342971\n", - "#Accuracy at 7 =91.72482552342971\n", - "#Accuracy at 4 =91.72482552342971\n", - "\n", - "#I chose RFE because it eliminates worst performing features\n", - "fit = rfe.fit(rescaledX, Y)\n", - "print(\"Num Features: \", fit.n_features_)\n", - "print(\"Selected Features:\", fit.support_)\n", - "print(\"Feature Ranking: \", fit.ranking_)" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[0.457, 0. , 0.545, 0.005],\n", - " [0.435, 0.116, 0.489, 0.011],\n", - " [0.467, 0.116, 0.523, 0.011],\n", - " ...,\n", - " [0.315, 0.268, 0.573, 0.329],\n", - " [0.391, 0.107, 0.526, 0.334],\n", - " [0.326, 0.338, 0.397, 0.334]])" - ] - }, - "execution_count": 26, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "rescaledX[:,fit.support_] #extracting features of interest\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Algorithms" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Accuracy: 91.72482552342971\n" - ] - } - ], - "source": [ - "###### Used on rescaled data\n", - "#Using Logistic Regression\n", - "#Splitting data into Train and Test Sets\n", - "\n", - "from sklearn.model_selection import train_test_split\n", - "from sklearn.linear_model import LogisticRegression \n", - "\n", - "test_size = 0.33 #Size of the test data\n", - "seed = 7\n", - "rescaledX_train, rescaledX_test, Y_train, Y_test = train_test_split(rescaledX, Y, test_size=test_size,\n", - "random_state=seed)\n", - "model = LogisticRegression() #Using Logistic Regression\n", - "model.fit(rescaledX_train, Y_train)\n", - "result = model.score(rescaledX_test, Y_test)\n", - "print(\"Accuracy: \", (result*100.0))" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Accuracy: 91.92422731804587\n" - ] - } - ], - "source": [ - "###Algorithm used on unscaled data\n", - "#Using Logistic Regression\n", - "#Splitting data into Train and Test Sets\n", - "\n", - "from sklearn.model_selection import train_test_split\n", - "from sklearn.linear_model import LogisticRegression \n", - "\n", - "array = Train.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "test_size = 0.33 #Size of the test data\n", - "seed = 7\n", - "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", - "random_state=seed)\n", - "model = LogisticRegression() #Using Logistic Regression\n", - "model.fit(X_train, Y_train)\n", - "result = model.score(X_test, Y_test)\n", - "print(\"Accuracy: \", (result*100.0))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Rescaled data gives accuracy of 91.72482552342971 and un scaled data with all the features gives 91.92422731804587. I have used unscaled data for the rest of the algorithms down" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[False True]\n", - "2\n", - "383\n", - "375\n" - ] - } - ], - "source": [ - "##Use the test dataset to see how the aligorithm is performing\n", - "out = model.predict(Test.values)\n", - "\n", - "out1 = pd.DataFrame(out) #Converting to data frame\n", - "out1.columns=[\"CLASS\"] #Naming the column\n", - "out1.index.name=\"Index\" #Creating a column index\n", - "out1[\"CLASS\"]=out1[\"CLASS\"].map({0.0:False,1.0:True}) # Chaninging 0 to \"False\" 1 to \"True\"\n", - "\n", - "out1.to_csv(\"talz_csv3\") ## Writing a csv file\n", - "print(out1['CLASS'].unique())\n", - "print(out1['CLASS'].nunique())\n", - "\n", - "#printing the numbers of False and True\n", - "print(out1.groupby('CLASS').size()[0].sum()) #\n", - "print(out1.groupby('CLASS').size()[1].sum()) " - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.880815746048289\n" - ] - } - ], - "source": [ - "###Naive Bayes\n", - "\n", - "from sklearn.naive_bayes import GaussianNB\n", - "from sklearn.model_selection import KFold\n", - "from sklearn.model_selection import cross_val_score\n", - "array = Train.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "kfold = KFold(n_splits=10, random_state=7)\n", - "model = GaussianNB()\n", - "model.fit(X, Y)\n", - "results = cross_val_score(model, X, Y, cv=kfold)\n", - "print(results.mean())" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[ True False]\n", - "2\n", - "370\n", - "388\n" - ] - } - ], - "source": [ - "##Use the test dataset to see how the aligorithm is performing\n", - "f = model.predict(Test.values)\n", - "\n", - "f1 = pd.DataFrame(f) #Converting to data frame\n", - "f1.columns=[\"CLASS\"] #Naming the column\n", - "f1.index.name=\"Index\" #Creating a column index\n", - "f1[\"CLASS\"]=f1[\"CLASS\"].map({0.0:False,1.0:True}) # Chaninging 0 to \"False\" 1 to \"True\"\n", - "\n", - "f1.to_csv(\"talz_csv8\") ## Writing a csv file\n", - "print(f1['CLASS'].unique())\n", - "print(f1['CLASS'].nunique())\n", - "\n", - "#printing the numbers of False and True\n", - "print(f1.groupby('CLASS').size()[0].sum()) #\n", - "print(f1.groupby('CLASS').size()[1].sum()) " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Classiffication and Regression Trees" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.7299407243355915\n" - ] - } - ], - "source": [ - "#Classiffication and Regression Trees\n", - "from sklearn.tree import DecisionTreeClassifier\n", - "array = Train.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "kfold = KFold(n_splits=10, random_state=7)\n", - "model = DecisionTreeClassifier()\n", - "model.fit(X, Y)\n", - "results = cross_val_score(model, X, Y, cv=kfold)\n", - "print(results.mean())" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[ True False]\n", - "2\n", - "385\n", - "373\n" - ] - } - ], - "source": [ - "fd = model.predict(Test.values)\n", - "\n", - "fd1 = pd.DataFrame(fd) #Converting to data frame\n", - "fd1.columns=[\"CLASS\"] #Naming the column\n", - "fd1.index.name=\"Index\" #Creating a column index\n", - "fd1[\"CLASS\"]=fd1[\"CLASS\"].map({0.0:False,1.0:True}) # Chaninging 0 to \"False\" 1 to \"True\"\n", - "\n", - "fd1.to_csv(\"talz_csv9\") ## Writing a csv file\n", - "print(fd1['CLASS'].unique())\n", - "print(fd1['CLASS'].nunique())\n", - "\n", - "#printing the numbers of False and True\n", - "print(fd1.groupby('CLASS').size()[0].sum()) #\n", - "print(fd1.groupby('CLASS').size()[1].sum()) " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Support Vector Machines (SVM)" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.8350280093798853\n", - "[False True]\n", - "2\n", - "397\n", - "361\n" - ] - } - ], - "source": [ - "from sklearn.svm import SVC\n", - "\n", - "array = Train.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "kfold = KFold(n_splits=10, random_state=7)\n", - "model = SVC()\n", - "model.fit(X, Y)\n", - "results = cross_val_score(model, X, Y, cv=kfold)\n", - "print(results.mean())\n", - "\n", - "svm = model.predict(Test.values)\n", - "\n", - "svm1 = pd.DataFrame(svm) #Converting to data frame\n", - "svm1.columns=[\"CLASS\"] #Naming the column\n", - "svm1.index.name=\"Index\" #Creating a column index\n", - "svm1[\"CLASS\"]=svm1[\"CLASS\"].map({0.0:False,1.0:True}) # Chaninging 0 to \"False\" 1 to \"True\"\n", - "\n", - "svm1.to_csv(\"talz_csv10\") ## Writing a csv file\n", - "print(svm1['CLASS'].unique())\n", - "print(svm1['CLASS'].nunique())\n", - "\n", - "#printing the numbers of False and True\n", - "print(svm1.groupby('CLASS').size()[0].sum()) #\n", - "print(svm1.groupby('CLASS').size()[1].sum()) " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Linear Discriminant Analysis" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.8535044293903076\n" - ] - } - ], - "source": [ - "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", - "\n", - "array = Train.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "num_folds = 10\n", - "kfold = KFold(n_splits=10, random_state=7)\n", - "model = LinearDiscriminantAnalysis()\n", - "results = cross_val_score(model, X, Y, cv=kfold)\n", - "print(results.mean())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## K-Nearest Neighbors" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "-0.16489729894042035\n" - ] - } - ], - "source": [ - "from sklearn.neighbors import KNeighborsRegressor\n", - "\n", - "array = Train.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "kfold = KFold(n_splits=10, random_state=7)\n", - "model = KNeighborsRegressor()\n", - "scoring = 'neg_mean_squared_error'\n", - "results = cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\n", - "print(results.mean())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Ridge Regression" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "-0.11583526542366822\n" - ] - } - ], - "source": [ - "from sklearn.linear_model import Ridge\n", - "\n", - "array = Train.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "num_folds = 10\n", - "kfold = KFold(n_splits=10, random_state=7)\n", - "model = Ridge()\n", - "scoring = 'neg_mean_squared_error'\n", - "results = cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\n", - "print(results.mean())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Random Forest" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.8087013635574085\n" - ] - } - ], - "source": [ - "# Random Forest Classification\n", - "from pandas import read_csv\n", - "from sklearn.model_selection import KFold\n", - "from sklearn.model_selection import cross_val_score\n", - "from sklearn.ensemble import RandomForestClassifier\n", - "array = Train.values\n", - "\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "\n", - "num_trees = 1000\n", - "\n", - "max_features = 3\n", - "\n", - "kfold = KFold(n_splits=10, random_state=7)\n", - "model = RandomForestClassifier(n_estimators=num_trees, max_features=max_features)\n", - "results = cross_val_score(model, X, Y, cv=kfold)\n", - "print(results.mean())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Stochastic Gradient Descent - SGD" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.7882935990967518\n" - ] - } - ], - "source": [ - "\n", - "# Stochastic Gradient Boosting Classification\n", - "from pandas import read_csv\n", - "from sklearn.model_selection import KFold\n", - "from sklearn.model_selection import cross_val_score\n", - "from sklearn.ensemble import GradientBoostingClassifier\n", - "\n", - "array = Train.values\n", - "\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "\n", - "seed = 7\n", - "num_trees = 100\n", - "\n", - "kfold = KFold(n_splits=10, random_state=seed)\n", - "model = GradientBoostingClassifier(n_estimators=num_trees, random_state=seed)\n", - "results = cross_val_score(model, X, Y, cv=kfold)\n", - "print(results.mean())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## XGB" - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.787307842626368\n" - ] - } - ], - "source": [ - "# Stochastic X Gradient Boosting Classification\n", - "from pandas import read_csv\n", - "from sklearn.model_selection import KFold\n", - "from sklearn.model_selection import cross_val_score\n", - "from xgboost import XGBClassifier\n", - "\n", - "array = Train.values\n", - "\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "\n", - "seed = 7\n", - "num_trees = 100\n", - "\n", - "kfold = KFold(n_splits=10, random_state=seed)\n", - "model = XGBClassifier(n_estimators=num_trees, random_state=seed)\n", - "results = cross_val_score(model, X, Y, cv=kfold)\n", - "print(results.mean())" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Comparinr the Algorithms used\n", - "from matplotlib import pyplot\n", - "from sklearn.model_selection import KFold\n", - "from sklearn.model_selection import cross_val_score\n", - "from sklearn.linear_model import LogisticRegression\n", - "from sklearn.tree import DecisionTreeClassifier\n", - "from sklearn.neighbors import KNeighborsClassifier\n", - "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", - "from sklearn.naive_bayes import GaussianNB\n", - "from sklearn.svm import SVC\n", - "from sklearn.ensemble import RandomForestClassifier\n", - "from sklearn.ensemble import GradientBoostingClassifier\n", - "from xgboost import XGBClassifier\n", - "# load dataset\n", - "\n", - "array = Train.values\n", - "\n", - "#split the dataset \n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "\n", - "# prepare models and add them to a list\n", - "models = []\n", - "models.append(('LR', LogisticRegression()))\n", - "models.append(('CART', DecisionTreeClassifier()))\n", - "models.append(('NB', GaussianNB()))\n", - "models.append(('SVM', SVC()))\n", - "models.append(('LDA', LinearDiscriminantAnalysis()))\n", - "models.append(('DTC', DecisionTreeClassifier()))\n", - "models.append(('KNN', KNeighborsClassifier()))\n", - "models.append(('RFC', RandomForestClassifier()))\n", - "models.append(('GBC', GradientBoostingClassifier()))\n", - "models.append(('XGB', XGBClassifier()))\n", - "# evaluate each model in turn\n", - "results = []\n", - "names = []\n", - "scoring = 'accuracy'\n", - "\n", - "for name, model in models:\n", - " kfold = KFold(n_splits=10, random_state=7)\n", - " cv_results = cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\n", - " results.append(cv_results)\n", - " names.append(name)\n", - " msg = (name, cv_results.mean(), cv_results.std())\n", - " print(msg)\n", - "\n", - "# boxplot algorithm comparison\n", - "fig = pyplot.figure()\n", - "fig.suptitle('Algorithm Comparison')\n", - "ax = fig.add_subplot(111)\n", - "pyplot.boxplot(results)\n", - "ax.set_xticklabels(names)\n", - "pyplot.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Naive Bayes gives the best accuarcy" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "
\n", - " \n", - " ## Final thoughts\n", - "\n", - "You are not doing a good job in documenting your work. Please improve in your report.\n", - "\n", - "You can talk to your friend and see how they are doing their reports on the work they are doing.\n", - "\n", - "- I need to know what you are thinking at each step, a description of the concept e.t.c\n", - "- Your explanation should be coherent, meaning, I need to see that you understand what you are doing, and if you don't also document that." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.4" - }, - "varInspector": { - "cols": { - "lenName": 16, - "lenType": 16, - "lenVar": 40 - }, - "kernels_config": { - 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Paul.ipynb +++ /dev/null @@ -1,1903 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Talent Paul" - ] - }, - { - "cell_type": "raw", - "metadata": { - "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", - "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" - }, - "source": [ - "# This Python 3 environment comes with many helpful analytics libraries installed\n", - "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", - "# For example, here's several helpful packages to load in \n", - "\n", - "import numpy as np # linear algebra\n", - "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", - "import matplotlib.pyplot as plt # Plotting\n", - "\n", - "# Input data files are available in the \"../input/\" directory.\n", - "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", - "\n", - "import os\n", - "for dirname, _, filenames in os.walk('/kaggle/input'):\n", - " for filename in filenames:\n", - " print(os.path.join(dirname, filename))\n", - "\n", - "# Any results you write to the current directory are saved as output." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "
\n", - " Please look out for colored cells for my notes.\n", - "
" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np # linear algebra\n", - "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", - "import matplotlib.pyplot as plt # Plotting" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": { - "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0", - "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a" - }, - "outputs": [], - "source": [ - "#Dealing with errors\n", - "import warnings\n", - "warnings.filterwarnings('ignore')" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201FULL_GEOR030101FULL_OOBM850104NT_EFC195AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CT_RACS820104CLASS
count3038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.000000
mean2.0602378.5215200.97141073.6687600.994007-2.4329270.08854515.68323373.6508285.9113611.2352550.500000
std3.8199297.5866520.1074138.5274890.0313331.7072230.28413311.5756659.1660920.6936890.2100120.500082
min-16.0000000.0000000.68400042.7500000.866000-10.4320000.0000000.04100042.7780003.5330000.7850000.000000
25%0.0000002.5160000.89500068.2940000.974000-3.6060000.0000005.58750067.5560005.4592501.0820000.000000
50%2.0000007.1430000.96300074.0595000.994000-2.2965000.00000014.98850073.6970005.9255001.1840000.500000
75%4.00000013.1580001.04100079.3437501.011000-1.2832500.00000026.80775079.7780006.3820001.3510001.000000
max30.00000046.6670001.451000101.6820001.1960003.5760001.00000051.280000103.1670008.6620002.1920001.000000
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FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201FULL_GEOR030101FULL_OOBM850104NT_EFC195AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CT_RACS820104CLASS
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FULL_AcidicMolPerc-0.6129961.0000000.7947960.5414810.1152010.513344-0.143168-0.4315900.4496210.002334-0.213543-0.598816
FULL_AURR980107-0.4909770.7947961.0000000.5482530.3461390.462712-0.169540-0.4260970.4562600.032958-0.403599-0.584111
FULL_DAYM780201-0.4346030.5414810.5482531.0000000.0101180.334778-0.090058-0.4087930.8941910.055915-0.326792-0.554838
FULL_GEOR030101-0.0587250.1152010.3461390.0101181.0000000.319157-0.230417-0.160269-0.0290850.040480-0.151935-0.260470
FULL_OOBM850104-0.2837580.5133440.4627120.3347780.3191571.000000-0.230561-0.3362970.275640-0.4527690.155304-0.453287
NT_EFC1950.088068-0.143168-0.169540-0.090058-0.230417-0.2305611.0000000.178683-0.0368440.1459240.0808980.260702
AS_MeanAmphiMoment0.355477-0.431590-0.426097-0.408793-0.160269-0.3362970.1786831.000000-0.3223780.0255800.1715240.693552
AS_DAYM780201-0.3653740.4496210.4562600.894191-0.0290850.275640-0.036844-0.3223781.0000000.045562-0.256060-0.437168
AS_FUKS010112-0.0905700.0023340.0329580.0559150.040480-0.4527690.1459240.0255800.0455621.000000-0.4452840.033432
CT_RACS8201040.232929-0.213543-0.403599-0.326792-0.1519350.1553040.0808980.171524-0.256060-0.4452841.0000000.267652
CLASS0.534602-0.598816-0.584111-0.554838-0.260470-0.4532870.2607020.693552-0.4371680.0334320.2676521.000000
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" - ], - "text/plain": [ - " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 \\\n", - "FULL_Charge 1.000000 -0.612996 -0.490977 \n", - "FULL_AcidicMolPerc -0.612996 1.000000 0.794796 \n", - "FULL_AURR980107 -0.490977 0.794796 1.000000 \n", - "FULL_DAYM780201 -0.434603 0.541481 0.548253 \n", - "FULL_GEOR030101 -0.058725 0.115201 0.346139 \n", - "FULL_OOBM850104 -0.283758 0.513344 0.462712 \n", - "NT_EFC195 0.088068 -0.143168 -0.169540 \n", - "AS_MeanAmphiMoment 0.355477 -0.431590 -0.426097 \n", - "AS_DAYM780201 -0.365374 0.449621 0.456260 \n", - "AS_FUKS010112 -0.090570 0.002334 0.032958 \n", - "CT_RACS820104 0.232929 -0.213543 -0.403599 \n", - "CLASS 0.534602 -0.598816 -0.584111 \n", - "\n", - " FULL_DAYM780201 FULL_GEOR030101 FULL_OOBM850104 \\\n", - "FULL_Charge -0.434603 -0.058725 -0.283758 \n", - "FULL_AcidicMolPerc 0.541481 0.115201 0.513344 \n", - "FULL_AURR980107 0.548253 0.346139 0.462712 \n", - "FULL_DAYM780201 1.000000 0.010118 0.334778 \n", - "FULL_GEOR030101 0.010118 1.000000 0.319157 \n", - "FULL_OOBM850104 0.334778 0.319157 1.000000 \n", - "NT_EFC195 -0.090058 -0.230417 -0.230561 \n", - "AS_MeanAmphiMoment -0.408793 -0.160269 -0.336297 \n", - "AS_DAYM780201 0.894191 -0.029085 0.275640 \n", - "AS_FUKS010112 0.055915 0.040480 -0.452769 \n", - "CT_RACS820104 -0.326792 -0.151935 0.155304 \n", - "CLASS -0.554838 -0.260470 -0.453287 \n", - "\n", - " NT_EFC195 AS_MeanAmphiMoment AS_DAYM780201 \\\n", - "FULL_Charge 0.088068 0.355477 -0.365374 \n", - "FULL_AcidicMolPerc -0.143168 -0.431590 0.449621 \n", - "FULL_AURR980107 -0.169540 -0.426097 0.456260 \n", - "FULL_DAYM780201 -0.090058 -0.408793 0.894191 \n", - "FULL_GEOR030101 -0.230417 -0.160269 -0.029085 \n", - "FULL_OOBM850104 -0.230561 -0.336297 0.275640 \n", - "NT_EFC195 1.000000 0.178683 -0.036844 \n", - "AS_MeanAmphiMoment 0.178683 1.000000 -0.322378 \n", - "AS_DAYM780201 -0.036844 -0.322378 1.000000 \n", - "AS_FUKS010112 0.145924 0.025580 0.045562 \n", - "CT_RACS820104 0.080898 0.171524 -0.256060 \n", - "CLASS 0.260702 0.693552 -0.437168 \n", - "\n", - " AS_FUKS010112 CT_RACS820104 CLASS \n", - "FULL_Charge -0.090570 0.232929 0.534602 \n", - "FULL_AcidicMolPerc 0.002334 -0.213543 -0.598816 \n", - "FULL_AURR980107 0.032958 -0.403599 -0.584111 \n", - "FULL_DAYM780201 0.055915 -0.326792 -0.554838 \n", - "FULL_GEOR030101 0.040480 -0.151935 -0.260470 \n", - "FULL_OOBM850104 -0.452769 0.155304 -0.453287 \n", - "NT_EFC195 0.145924 0.080898 0.260702 \n", - "AS_MeanAmphiMoment 0.025580 0.171524 0.693552 \n", - "AS_DAYM780201 0.045562 -0.256060 -0.437168 \n", - "AS_FUKS010112 1.000000 -0.445284 0.033432 \n", - "CT_RACS820104 -0.445284 1.000000 0.267652 \n", - "CLASS 0.033432 0.267652 1.000000 " - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#Correlation\n", - "Train.corr(method='pearson')" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "#Classification\n", - "Train.groupby('CLASS').size().plot(kind='bar')\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "
\n", - " I asked specifically for each of us to write their thoughts down specifically on what they are doing at each stage.\n", - " \n", - " You are not doing a good job documenting your work with mark down.\n", - " " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#The distribution of 0 and 1 is the same" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "FULL_Charge 0.534602\n", - "FULL_AcidicMolPerc -0.598816\n", - "FULL_AURR980107 -0.584111\n", - "FULL_DAYM780201 -0.554838\n", - "FULL_GEOR030101 -0.260470\n", - "FULL_OOBM850104 -0.453287\n", - "NT_EFC195 0.260702\n", - "AS_MeanAmphiMoment 0.693552\n", - "AS_DAYM780201 -0.437168\n", - "AS_FUKS010112 0.033432\n", - "CT_RACS820104 0.267652\n", - "CLASS 1.000000\n", - "Name: CLASS, dtype: float64" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#Looking at the correlation of \"CLASS\" with other attributes\n", - "Train.corr()['CLASS']" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Data With Visualization" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "#Univariate Plot\n", - "plt.figure(figsize=(50,50))\n", - "Train.hist()\n", - "plt.subplots_adjust(bottom=1,right=2,top=3)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Density Plots\n", - "\n", - "### Density plots are another way of getting a quick idea of the distribution of each attribute. The plots look like an abstracted histogram with a smooth curve drawn through the top of each bin\n", - "\n", - "
\n", - "\n", - "## ??\n", - "\n", - "What did you learn from the plots?" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 20, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "Train.plot(kind='box', subplots=True, layout=(3,4), sharex=False, sharey=False)\n", - "plt.subplots_adjust(bottom=1,right=2,top=3)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "
\n", - "Please your visual, is compact, the labels on the upper axis are overlapping, can you try a different library to plot this if you are having a hard time with matplotlib?" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "#Multivariate Plot\n", - "correlations = Train.corr()\n", - "# plot correlation matrix\n", - "fig = plt.figure()\n", - "ax = fig.add_subplot(111)\n", - "cax = ax.matshow(correlations, vmin=-1, vmax=1)\n", - "fig.colorbar(cax)\n", - "ticks = np.arange(0,9,1)\n", - "ax.set_xticks(ticks)\n", - "ax.set_yticks(ticks)\n", - "ax.set_xticklabels(Train.columns)\n", - "ax.set_yticklabels(Train.columns)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Scatter plot\n", - "\n", - "
\n", - "\n", - "## ??\n", - "\n", - "What are you trying to learn with the plots below? \n", - "Its not compulsory to do a pair plot if you are not trying to inform specific decisions.\n", - "\n", - "Please plot only those that you are interested in they could be 2 or 3 that have caught your eye." - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "#Scatter Plot Matrix\n", - "#A scatter plot shows the relationship between two variables as dots in two dimensions, one axis for each attribute\n", - "import seaborn as sns\n", - "#sns.set(style=\"ticks\")\n", - "sns.pairplot(Train)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Preparing data for machine learning\n", - "\n", - "
\n", - "\n", - "## ??" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Feature selection" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[0.457 0. 0.348 0.545 0.33 0.483 0. 0.005 0.508 0.415 0.182]\n", - " [0.435 0.116 0.322 0.489 0.276 0.458 1. 0.011 0.421 0.586 0.475]\n", - " [0.467 0.116 0.246 0.523 0.288 0.565 0. 0.011 0.442 0.273 0.666]\n", - " [0.457 0.089 0.275 0.399 0.403 0.647 0. 0.011 0.405 0.153 0.424]\n", - " [0.511 0.183 0.323 0.373 0.342 0.595 0. 0.011 0.5 0.196 0.536]\n", - " [0.457 0.165 0.451 0.614 0.333 0.524 1. 0.009 0.596 0.479 0.217]\n", - " [0.413 0.148 0.321 0.608 0.276 0.492 1. 0.007 0.587 0.536 0.485]\n", - " [0.391 0.126 0.24 0.574 0.252 0.328 0. 0.002 0.56 0.574 0.214]\n", - " [0.5 0.056 0.226 0.3 0.442 0.724 0. 0.003 0.357 0.062 0.81 ]\n", - " [0.543 0. 0.296 0.391 0.555 0.467 0. 0.006 0.339 0.545 0.306]\n", - " [0.391 0.074 0.4 0.482 0.376 0.48 0. 0.009 0.557 0.364 0.355]]\n" - ] - } - ], - "source": [ - "##Rescaling \n", - "from numpy import set_printoptions\n", - "from sklearn.preprocessing import MinMaxScaler\n", - "\n", - "###rescaling the data\n", - "array = Train.values\n", - "# separate array into input and output components\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "\n", - "##Scaling the data so that it's within the range of 0 and 1\n", - "scaler = MinMaxScaler(feature_range=(0, 1))\n", - "rescaledX = scaler.fit_transform(X)\n", - "# summarize transformed data\n", - "set_printoptions(precision=3) #number of decimal points\n", - "print(rescaledX[0:11,:])" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Num Features: 4\n", - "Selected Features: [ True True False True False False False True False False False]\n", - "Feature Ranking: [1 1 4 1 2 3 5 1 7 8 6]\n" - ] - } - ], - "source": [ - "#feature selection using recursive feature elimination\n", - "\n", - "from sklearn.feature_selection import RFE\n", - "from sklearn.linear_model import LogisticRegression\n", - "\n", - "# feature extraction\n", - "model = LogisticRegression()\n", - "rfe = RFE(model, 4)\n", - "\n", - "#I tried to test for the performance of the model with more features and the results hardly changed.\n", - "#I used 11 then 7,and finally 4 features. I selected the features ranndomly.\n", - "#As a trade off for faster performance , I decided to go with 4 features.\n", - "\n", - "#Accuracy at 11 =91.72482552342971\n", - "#Accuracy at 7 =91.72482552342971\n", - "#Accuracy at 4 =91.72482552342971\n", - "\n", - "#I chose RFE because it eliminates worst performing features\n", - "fit = rfe.fit(rescaledX, Y)\n", - "print(\"Num Features: \", fit.n_features_)\n", - "print(\"Selected Features:\", fit.support_)\n", - "print(\"Feature Ranking: \", fit.ranking_)" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[0.457, 0. , 0.545, 0.005],\n", - " [0.435, 0.116, 0.489, 0.011],\n", - " [0.467, 0.116, 0.523, 0.011],\n", - " ...,\n", - " [0.315, 0.268, 0.573, 0.329],\n", - " [0.391, 0.107, 0.526, 0.334],\n", - " [0.326, 0.338, 0.397, 0.334]])" - ] - }, - "execution_count": 26, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "rescaledX[:,fit.support_] #extracting features of interest\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Algorithms" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Accuracy: 91.72482552342971\n" - ] - } - ], - "source": [ - "###### Used on rescaled data\n", - "#Using Logistic Regression\n", - "#Splitting data into Train and Test Sets\n", - "\n", - "from sklearn.model_selection import train_test_split\n", - "from sklearn.linear_model import LogisticRegression \n", - "\n", - "test_size = 0.33 #Size of the test data\n", - "seed = 7\n", - "rescaledX_train, rescaledX_test, Y_train, Y_test = train_test_split(rescaledX, Y, test_size=test_size,\n", - "random_state=seed)\n", - "model = LogisticRegression() #Using Logistic Regression\n", - "model.fit(rescaledX_train, Y_train)\n", - "result = model.score(rescaledX_test, Y_test)\n", - "print(\"Accuracy: \", (result*100.0))" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Accuracy: 91.92422731804587\n" - ] - } - ], - "source": [ - "###Algorithm used on unscaled data\n", - "#Using Logistic Regression\n", - "#Splitting data into Train and Test Sets\n", - "\n", - "from sklearn.model_selection import train_test_split\n", - "from sklearn.linear_model import LogisticRegression \n", - "\n", - "array = Train.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "test_size = 0.33 #Size of the test data\n", - "seed = 7\n", - "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", - "random_state=seed)\n", - "model = LogisticRegression() #Using Logistic Regression\n", - "model.fit(X_train, Y_train)\n", - "result = model.score(X_test, Y_test)\n", - "print(\"Accuracy: \", (result*100.0))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Rescaled data gives accuracy of 91.72482552342971 and un scaled data with all the features gives 91.92422731804587. I have used unscaled data for the rest of the algorithms down" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[False True]\n", - "2\n", - "383\n", - "375\n" - ] - } - ], - "source": [ - "##Use the test dataset to see how the aligorithm is performing\n", - "out = model.predict(Test.values)\n", - "\n", - "out1 = pd.DataFrame(out) #Converting to data frame\n", - "out1.columns=[\"CLASS\"] #Naming the column\n", - "out1.index.name=\"Index\" #Creating a column index\n", - "out1[\"CLASS\"]=out1[\"CLASS\"].map({0.0:False,1.0:True}) # Chaninging 0 to \"False\" 1 to \"True\"\n", - "\n", - "out1.to_csv(\"talz_csv3\") ## Writing a csv file\n", - "print(out1['CLASS'].unique())\n", - "print(out1['CLASS'].nunique())\n", - "\n", - "#printing the numbers of False and True\n", - "print(out1.groupby('CLASS').size()[0].sum()) #\n", - "print(out1.groupby('CLASS').size()[1].sum()) " - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.880815746048289\n" - ] - } - ], - "source": [ - "###Naive Bayes\n", - "\n", - "from sklearn.naive_bayes import GaussianNB\n", - "from sklearn.model_selection import KFold\n", - "from sklearn.model_selection import cross_val_score\n", - "array = Train.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "kfold = KFold(n_splits=10, random_state=7)\n", - "model = GaussianNB()\n", - "model.fit(X, Y)\n", - "results = cross_val_score(model, X, Y, cv=kfold)\n", - "print(results.mean())" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[ True False]\n", - "2\n", - "370\n", - "388\n" - ] - } - ], - "source": [ - "##Use the test dataset to see how the aligorithm is performing\n", - "f = model.predict(Test.values)\n", - "\n", - "f1 = pd.DataFrame(f) #Converting to data frame\n", - "f1.columns=[\"CLASS\"] #Naming the column\n", - "f1.index.name=\"Index\" #Creating a column index\n", - "f1[\"CLASS\"]=f1[\"CLASS\"].map({0.0:False,1.0:True}) # Chaninging 0 to \"False\" 1 to \"True\"\n", - "\n", - "f1.to_csv(\"talz_csv8\") ## Writing a csv file\n", - "print(f1['CLASS'].unique())\n", - "print(f1['CLASS'].nunique())\n", - "\n", - "#printing the numbers of False and True\n", - "print(f1.groupby('CLASS').size()[0].sum()) #\n", - "print(f1.groupby('CLASS').size()[1].sum()) " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Classiffication and Regression Trees" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.7299407243355915\n" - ] - } - ], - "source": [ - "#Classiffication and Regression Trees\n", - "from sklearn.tree import DecisionTreeClassifier\n", - "array = Train.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "kfold = KFold(n_splits=10, random_state=7)\n", - "model = DecisionTreeClassifier()\n", - "model.fit(X, Y)\n", - "results = cross_val_score(model, X, Y, cv=kfold)\n", - "print(results.mean())" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[ True False]\n", - "2\n", - "385\n", - "373\n" - ] - } - ], - "source": [ - "fd = model.predict(Test.values)\n", - "\n", - "fd1 = pd.DataFrame(fd) #Converting to data frame\n", - "fd1.columns=[\"CLASS\"] #Naming the column\n", - "fd1.index.name=\"Index\" #Creating a column index\n", - "fd1[\"CLASS\"]=fd1[\"CLASS\"].map({0.0:False,1.0:True}) # Chaninging 0 to \"False\" 1 to \"True\"\n", - "\n", - "fd1.to_csv(\"talz_csv9\") ## Writing a csv file\n", - "print(fd1['CLASS'].unique())\n", - "print(fd1['CLASS'].nunique())\n", - "\n", - "#printing the numbers of False and True\n", - "print(fd1.groupby('CLASS').size()[0].sum()) #\n", - "print(fd1.groupby('CLASS').size()[1].sum()) " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Support Vector Machines (SVM)" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.8350280093798853\n", - "[False True]\n", - "2\n", - "397\n", - "361\n" - ] - } - ], - "source": [ - "from sklearn.svm import SVC\n", - "\n", - "array = Train.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "kfold = KFold(n_splits=10, random_state=7)\n", - "model = SVC()\n", - "model.fit(X, Y)\n", - "results = cross_val_score(model, X, Y, cv=kfold)\n", - "print(results.mean())\n", - "\n", - "svm = model.predict(Test.values)\n", - "\n", - "svm1 = pd.DataFrame(svm) #Converting to data frame\n", - "svm1.columns=[\"CLASS\"] #Naming the column\n", - "svm1.index.name=\"Index\" #Creating a column index\n", - "svm1[\"CLASS\"]=svm1[\"CLASS\"].map({0.0:False,1.0:True}) # Chaninging 0 to \"False\" 1 to \"True\"\n", - "\n", - "svm1.to_csv(\"talz_csv10\") ## Writing a csv file\n", - "print(svm1['CLASS'].unique())\n", - "print(svm1['CLASS'].nunique())\n", - "\n", - "#printing the numbers of False and True\n", - "print(svm1.groupby('CLASS').size()[0].sum()) #\n", - "print(svm1.groupby('CLASS').size()[1].sum()) " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Linear Discriminant Analysis" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.8535044293903076\n" - ] - } - ], - "source": [ - "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", - "\n", - "array = Train.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "num_folds = 10\n", - "kfold = KFold(n_splits=10, random_state=7)\n", - "model = LinearDiscriminantAnalysis()\n", - "results = cross_val_score(model, X, Y, cv=kfold)\n", - "print(results.mean())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## K-Nearest Neighbors" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "-0.16489729894042035\n" - ] - } - ], - "source": [ - "from sklearn.neighbors import KNeighborsRegressor\n", - "\n", - "array = Train.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "kfold = KFold(n_splits=10, random_state=7)\n", - "model = KNeighborsRegressor()\n", - "scoring = 'neg_mean_squared_error'\n", - "results = cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\n", - "print(results.mean())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Ridge Regression" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "-0.11583526542366822\n" - ] - } - ], - "source": [ - "from sklearn.linear_model import Ridge\n", - "\n", - "array = Train.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "num_folds = 10\n", - "kfold = KFold(n_splits=10, random_state=7)\n", - "model = Ridge()\n", - "scoring = 'neg_mean_squared_error'\n", - "results = cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\n", - "print(results.mean())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Random Forest" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.8087013635574085\n" - ] - } - ], - "source": [ - "# Random Forest Classification\n", - "from pandas import read_csv\n", - "from sklearn.model_selection import KFold\n", - "from sklearn.model_selection import cross_val_score\n", - "from sklearn.ensemble import RandomForestClassifier\n", - "array = Train.values\n", - "\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "\n", - "num_trees = 1000\n", - "\n", - "max_features = 3\n", - "\n", - "kfold = KFold(n_splits=10, random_state=7)\n", - "model = RandomForestClassifier(n_estimators=num_trees, max_features=max_features)\n", - "results = cross_val_score(model, X, Y, cv=kfold)\n", - "print(results.mean())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Stochastic Gradient Descent - SGD" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.7882935990967518\n" - ] - } - ], - "source": [ - "\n", - "# Stochastic Gradient Boosting Classification\n", - "from pandas import read_csv\n", - "from sklearn.model_selection import KFold\n", - "from sklearn.model_selection import cross_val_score\n", - "from sklearn.ensemble import GradientBoostingClassifier\n", - "\n", - "array = Train.values\n", - "\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "\n", - "seed = 7\n", - "num_trees = 100\n", - "\n", - "kfold = KFold(n_splits=10, random_state=seed)\n", - "model = GradientBoostingClassifier(n_estimators=num_trees, random_state=seed)\n", - "results = cross_val_score(model, X, Y, cv=kfold)\n", - "print(results.mean())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## XGB" - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.787307842626368\n" - ] - } - ], - "source": [ - "# Stochastic X Gradient Boosting Classification\n", - "from pandas import read_csv\n", - "from sklearn.model_selection import KFold\n", - "from sklearn.model_selection import cross_val_score\n", - "from xgboost import XGBClassifier\n", - "\n", - "array = Train.values\n", - "\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "\n", - "seed = 7\n", - "num_trees = 100\n", - "\n", - "kfold = KFold(n_splits=10, random_state=seed)\n", - "model = XGBClassifier(n_estimators=num_trees, random_state=seed)\n", - "results = cross_val_score(model, X, Y, cv=kfold)\n", - "print(results.mean())" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Comparinr the Algorithms used\n", - "from matplotlib import pyplot\n", - "from sklearn.model_selection import KFold\n", - "from sklearn.model_selection import cross_val_score\n", - "from sklearn.linear_model import LogisticRegression\n", - "from sklearn.tree import DecisionTreeClassifier\n", - "from sklearn.neighbors import KNeighborsClassifier\n", - "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", - "from sklearn.naive_bayes import GaussianNB\n", - "from sklearn.svm import SVC\n", - "from sklearn.ensemble import RandomForestClassifier\n", - "from sklearn.ensemble import GradientBoostingClassifier\n", - "from xgboost import XGBClassifier\n", - "# load dataset\n", - "\n", - "array = Train.values\n", - "\n", - "#split the dataset \n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "\n", - "# prepare models and add them to a list\n", - "models = []\n", - "models.append(('LR', LogisticRegression()))\n", - "models.append(('CART', DecisionTreeClassifier()))\n", - "models.append(('NB', GaussianNB()))\n", - "models.append(('SVM', SVC()))\n", - "models.append(('LDA', LinearDiscriminantAnalysis()))\n", - "models.append(('DTC', DecisionTreeClassifier()))\n", - "models.append(('KNN', KNeighborsClassifier()))\n", - "models.append(('RFC', RandomForestClassifier()))\n", - "models.append(('GBC', GradientBoostingClassifier()))\n", - "models.append(('XGB', XGBClassifier()))\n", - "# evaluate each model in turn\n", - "results = []\n", - "names = []\n", - "scoring = 'accuracy'\n", - "\n", - "for name, model in models:\n", - " kfold = KFold(n_splits=10, random_state=7)\n", - " cv_results = cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\n", - " results.append(cv_results)\n", - " names.append(name)\n", - " msg = (name, cv_results.mean(), cv_results.std())\n", - " print(msg)\n", - "\n", - "# boxplot algorithm comparison\n", - "fig = pyplot.figure()\n", - "fig.suptitle('Algorithm Comparison')\n", - "ax = fig.add_subplot(111)\n", - "pyplot.boxplot(results)\n", - "ax.set_xticklabels(names)\n", - "pyplot.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Naive Bayes gives the best accuarcy" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "
\n", - " \n", - " ## Final thoughts\n", - "\n", - "You are not doing a good job in documenting your work. Please improve in your report.\n", - "\n", - "You can talk to your friend and see how they are doing their reports on the work they are doing.\n", - "\n", - "- I need to know what you are thinking at each step, a description of the concept e.t.c\n", - "- Your explanation should be coherent, meaning, I need to see that you understand what you are doing, and if you don't also document that." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.4" - }, - "varInspector": { - "cols": { - "lenName": 16, - "lenType": 16, - "lenVar": 40 - }, - "kernels_config": { - 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-684,False -685,False -686,False -687,False -688,False -689,False -690,False -691,False -692,False -693,False -694,False -695,False -696,False -697,False -698,False -699,False -700,False -701,False -702,False -703,False -704,False -705,False -706,False -707,False -708,False -709,False -710,False -711,False -712,False -713,False -714,False -715,False -716,False -717,True -718,False -719,True -720,False -721,True -722,False -723,False -724,False -725,False -726,False -727,False -728,False -729,False -730,False -731,False -732,False -733,False -734,True -735,False -736,True -737,False -738,False -739,False -740,False -741,False -742,False -743,True -744,True -745,True -746,False -747,False -748,False -749,False -750,True -751,False -752,False -753,False -754,False -755,False -756,False -757,False From 8c4398cf4b3132a15a8e7ae7b9f47669936733ea Mon Sep 17 00:00:00 2001 From: Maria_Magdalene_Namaganda Date: Thu, 12 Mar 2020 19:40:50 +0300 Subject: [PATCH 16/29] This is Maria's updated version --- .Rhistory | 0 .../Fezile Dlamini-checkpoint.ipynb | 778 +++++ .../KAYAGA NASHIM MILVAT-checkpoint.ipynb | 2767 +++++++++++++++++ .../MARIA MAGDALENE NAMAGANDA (1).ipynb | 1 - .../MARIA MAGDALENE NAMAGANDA FINAL.ipynb | 1 + .../MARIA MAGDALENE NAMAGANDA.ipynb | 1 - Fezile Dlamini.ipynb | 778 +++++ KAYAGA NASHIM MILVAT.ipynb | 2767 +++++++++++++++++ Thur 20 Feb/ACE_ClassML Pipeline.ipynb | 2 +- kakooza trevor Starter Kernel.ipynb | 1 + 10 files changed, 7093 insertions(+), 3 deletions(-) create mode 100644 .Rhistory create mode 100644 .ipynb_checkpoints/Fezile Dlamini-checkpoint.ipynb create mode 100644 .ipynb_checkpoints/KAYAGA NASHIM MILVAT-checkpoint.ipynb delete mode 100644 Assignment Colab/MARIA MAGDALENE NAMAGANDA (1).ipynb create mode 100644 Assignment Colab/MARIA MAGDALENE NAMAGANDA FINAL.ipynb delete mode 100644 Assignment Colab/MARIA MAGDALENE NAMAGANDA.ipynb create mode 100644 Fezile Dlamini.ipynb create mode 100644 KAYAGA NASHIM MILVAT.ipynb create mode 100644 kakooza trevor Starter Kernel.ipynb diff --git a/.Rhistory b/.Rhistory new file mode 100644 index 0000000..e69de29 diff --git a/.ipynb_checkpoints/Fezile Dlamini-checkpoint.ipynb b/.ipynb_checkpoints/Fezile Dlamini-checkpoint.ipynb new file mode 100644 index 0000000..2dd9fe7 --- /dev/null +++ b/.ipynb_checkpoints/Fezile Dlamini-checkpoint.ipynb @@ -0,0 +1,778 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", + "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" + }, + "outputs": [], + "source": [ + "# This Python 3 environment comes with many helpful analytics libraries installed\n", + "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", + "# For example, here's several helpful packages to load in \n", + "\n", + "import numpy as np # linear algebra\n", + "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", + "\n", + "# Input data files are available in the \"../input/\" directory.\n", + "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", + "\n", + "import os\n", + "for dirname, _, filenames in os.walk('/kaggle/input'):\n", + " for filename in filenames:\n", + " print(os.path.join(dirname, filename))\n", + "\n", + "# Any results you write to the current directory are saved as output." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Importing Libraries" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0", + "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a" + }, + "outputs": [], + "source": [ + "###Importing libraries\n", + "import pandas\n", + "import scipy\n", + "import numpy\n", + "import matplotlib\n", + "import sklearn\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Loading some libraries\n", + "### These are some of the libraries I think I will need" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from pandas import read_csv\n", + "from pandas.plotting import scatter_matrix\n", + "from matplotlib import pyplot\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.model_selection import StratifiedKFold\n", + "from sklearn.metrics import classification_report\n", + "from sklearn.metrics import confusion_matrix\n", + "from sklearn.metrics import accuracy_score\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "from sklearn.neighbors import KNeighborsClassifier\n", + "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", + "from sklearn.naive_bayes import GaussianNB\n", + "from sklearn.svm import SVC" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import warnings\n", + "warnings.filterwarnings('ignore')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Loading My Dataset\n", + "\n", + "##### I am going to first use my training dataset, then the test dataset last." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train = pandas.read_csv('/kaggle/input/ace-class-assignment/AMP_TrainSet.csv')\n", + "train\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "test= pandas.read_csv('/kaggle/input/ace-class-assignment/Test.csv')\n", + "test" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Inspecting my train dataset" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train.shape" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train.isnull().sum() ###this will show the number of null values in my data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train.count() #returns number of non-null values in my data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "##### It seems i have no missing values in my data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train.describe() #returns summary of the whole data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train.info() #It returns range, column, number of non-null objects of each column, datatype and memory usage" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "##### This shows that my dataset has 3038 rows (instances) and 12 columns (attributes)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "##### I will also take a look at how many instances i have for each class" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train.groupby('CLASS').size()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train.groupby('CLASS').size().plot(kind='bar')\n", + "pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### I have two groups of classes, each with 1519 instances" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# DATA VISUALISATION" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### I will start with univariate plots to see each indiviadual variable" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train.hist(figsize=(16,16))\n", + "pyplot.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train.corr(method='pearson')['CLASS'] #Here I tried to see the correlation of all attributes with the class" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Multivariate " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "correlations = train.corr()\n", + "# plot correlation matrix\n", + "fig = pyplot.figure()\n", + "ax = fig.add_subplot(111)\n", + "cax = ax.matshow(correlations, vmin=-1, vmax=1)\n", + "fig.colorbar(cax)\n", + "ticks = np.arange(0,9,1)\n", + "ax.set_xticks(ticks)\n", + "ax.set_yticks(ticks)\n", + "ax.set_xticklabels(train.columns)\n", + "ax.set_yticklabels(train.columns)\n", + "pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### i did this plot in order to see which features are highly correlated as this can be a problem in soome models if some features are used together whereas they are highly correlated." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# EVALUATING ALGORITHMS\n", + "#### I will now evaluate some algorithms and estimate their accuracy on unseen data." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Building models" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "array = train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "test_size = 0.32\n", + "seed = 3\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", + "random_state=seed)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "len(X_test)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "\n", + "models = []\n", + "models.append(('LR', LogisticRegression(solver='liblinear', multi_class='ovr')))\n", + "models.append(('LDA', LinearDiscriminantAnalysis()))\n", + "models.append(('KNN', KNeighborsClassifier()))\n", + "models.append(('CART', DecisionTreeClassifier()))\n", + "models.append(('NB', GaussianNB()))\n", + "models.append(('SVM', SVC(gamma='auto')))\n", + "# evaluate each model in turn\n", + "results = []\n", + "names = []\n", + "for name, model in models:\n", + " kfold = StratifiedKFold(n_splits=10)\n", + " cv_results = cross_val_score(model, X_train, Y_train, cv=kfold, scoring='accuracy')\n", + " results.append(cv_results)\n", + " names.append(name)\n", + " print('%s: %f (%f)' % (name, cv_results.mean(), cv_results.std()))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Compare Algorithms\n", + "pyplot.boxplot(results, labels=names)\n", + "pyplot.title('Algorithm Comparison')\n", + "pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### from here, NB is the best performing." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Make predictions on validation dataset\n", + "model = GaussianNB()\n", + "model.fit(X_train, Y_train)\n", + "predictions = model.predict(X_test)\n", + "print(predictions)\n", + "\n", + "#from sklearn.metrics import matthews_corrcoef\n", + "#print('MCC', matthews_corrcoef(model.predict(X_test), Y_test))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#with all features\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.naive_bayes import GaussianNB\n", + "\n", + "array = train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "test_size = 0.32\n", + "seed = 3\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", + "random_state=seed)\n", + "model = GaussianNB()\n", + "model.fit(X_train, Y_train)\n", + "result = model.score(X_test, Y_test)\n", + "print(\"Accuracy: \", (result*100.0))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Evaluate predictions\n", + "print(accuracy_score(Y_test, predictions))\n", + "print(confusion_matrix(Y_test, predictions))\n", + "print(classification_report(Y_test, predictions))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "test" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "Y=train.CLASS\n", + "X=train.drop(\"CLASS\",axis=1)\n", + "OUTPUT=model.fit(X, Y).predict(test.values)\n", + "OUTPUT_1=pd.DataFrame(OUTPUT)\n", + "OUTPUT_1.columns=[\"CLASS\"]\n", + "OUTPUT_1.index.name=\"Index\"\n", + "OUTPUT_1[\"CLASS\"]=OUTPUT_1[\"CLASS\"].map({0.0:False,1.0:True})\n", + "OUTPUT_1.to_csv(\"output\")\n", + "print(OUTPUT_1[\"CLASS\"].unique())\n", + "print(OUTPUT_1[\"CLASS\"].nunique())\n", + "print(OUTPUT_1.groupby(\"CLASS\").size()[0].sum())\n", + "print(OUTPUT_1.groupby(\"CLASS\").size()[1].sum())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#feature selection using feature importance\n", + "X = train.iloc[:,0:11] #independent columns\n", + "y = train.iloc[:,-1] #target column\n", + "from sklearn.ensemble import ExtraTreesClassifier\n", + "import matplotlib.pyplot as plt\n", + "model = ExtraTreesClassifier()\n", + "model.fit(X,y)\n", + "print(model.feature_importances_) #use inbuilt class feature_importances of tree based classifiers\n", + "#plot graph of feature importances for better visualization\n", + "feat_importances = pd.Series(model.feature_importances_, index=X.columns)\n", + "feat_importances.nlargest(10).plot(kind='barh')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train.columns" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "newtrain=train.drop([ 'FULL_AURR980107', 'FULL_OOBM850104', 'NT_EFC195', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104'], axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "newtest=test.drop([ 'FULL_AURR980107', 'FULL_OOBM850104', 'NT_EFC195', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104'], axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "newtrain" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "array = newtrain.values\n", + "X = array[:,0:5]\n", + "Y = array[:,-1]\n", + "test_size = 0.32\n", + "seed = 3\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", + "random_state=seed)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "models = []\n", + "models.append(('LR', LogisticRegression(solver='liblinear', multi_class='ovr')))\n", + "models.append(('LDA', LinearDiscriminantAnalysis()))\n", + "models.append(('KNN', KNeighborsClassifier()))\n", + "models.append(('CART', DecisionTreeClassifier()))\n", + "models.append(('NB', GaussianNB()))\n", + "models.append(('SVM', SVC(gamma='auto')))\n", + "# evaluate each model in turn\n", + "results = []\n", + "names = []\n", + "for name, model in models:\n", + " kfold = StratifiedKFold(n_splits=23, shuffle=True)\n", + " cv_results = cross_val_score(model, X_train, Y_train, cv=kfold, scoring='accuracy')\n", + " results.append(cv_results)\n", + " names.append(name)\n", + " print('%s: %f (%f)' % (name, cv_results.mean(), cv_results.std()))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "model = GaussianNB()\n", + "model.fit(X_train, Y_train)\n", + "result = model.score(X_test, Y_test)\n", + "print(\"Accuracy: \", (result*100.0))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Evaluate predictions\n", + "print(accuracy_score(Y_test, predictions))\n", + "print(confusion_matrix(Y_test, predictions))\n", + "print(classification_report(Y_test, predictions))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "Y=newtrain.CLASS\n", + "X=newtrain.drop(\"CLASS\",axis=1)\n", + "OUTPUT=model.fit(X, Y).predict(newtest.values)\n", + "OUTPUT_1=pd.DataFrame(OUTPUT)\n", + "OUTPUT_1.columns=[\"CLASS\"]\n", + "OUTPUT_1.index.name=\"Index\"\n", + "OUTPUT_1[\"CLASS\"]=OUTPUT_1[\"CLASS\"].map({0.0:False,1.0:True})\n", + "OUTPUT_1.to_csv(\"out1\")\n", + "print(OUTPUT_1[\"CLASS\"].unique())\n", + "print(OUTPUT_1[\"CLASS\"].nunique())\n", + "print(OUTPUT_1.groupby(\"CLASS\").size()[0].sum())\n", + "print(OUTPUT_1.groupby(\"CLASS\").size()[1].sum())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#checking accuracy using data with selected features from feature importance\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.naive_bayes import GaussianNB\n", + "from sklearn.metrics import matthews_corrcoef\n", + "\n", + "array = train.values\n", + "X = array[:,[0,1,3,5,7]]\n", + "Y = array[:,11]\n", + "test_size = 0.32\n", + "seed = 3\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", + "random_state=seed)\n", + "model = GaussianNB()\n", + "model.fit(X_train, Y_train)\n", + "result = model.score(X_test, Y_test)\n", + "prediction=model.predict(X_test)\n", + "matrix=matthews_corrcoef(Y_test,prediction)\n", + "print(\"Accuracy: \", (result*100.0))\n", + "print(matrix)\n", + "\n", + "# making predictions on the test data\n", + "\n", + "#output=model.predict(test.values)\n", + "#output1=pd.DataFrame(output)\n", + "#output1.columns=['CLASS']\n", + "#output1.index.name='Index'\n", + "#output1['CLASS']=output1['CLASS'].map({0.0:False, 1.0:True})\n", + "\n", + "#print(output1['CLASS'].unique())\n", + "#print(output1['CLASS'].nunique())\n", + "\n", + "#print(output1.groupby('CLASS').size()[0].sum())\n", + "#print(output1.groupby('CLASS').size()[1].sum())\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "array2 = np.array(test)\n", + "X = array2[:,[0,1,3,5,7]]\n", + "x_t=array[:,[0,1,3,5,7]]\n", + "y_t=array[:,11]\n", + "\n", + "#array3 = train.values\n", + "#X_t = array3[:,[0,1,3,5,7]]\n", + "#Y_t=array3[:,10]\n", + "test_size = 0.32\n", + "seed = 3\n", + "#X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", + "#random_state=seed)\n", + "test=array3[:,[0,1,3,5,7]]\n", + "model = GaussianNB()\n", + "\n", + "#result = model.score(X_t, Y_t)\n", + "model.fit(x_t, y_t)\n", + "prediction=model.predict(X)\n", + "\n", + "#matrix=matthews_corrcoef(Y_t,prediction)\n", + "#print(\"Accuracy: \", (result*100.0))\n", + "#print(matrix)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## FEATURE SELECTION" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#feature selection using Logistic regression\n", + "from sklearn.feature_selection import RFE\n", + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "array_1 = train.values\n", + "X = array_1[:,0:11]\n", + "Y = array_1[:,11]\n", + "# feature extraction\n", + "model = LogisticRegression()\n", + "rfe = RFE(model, 5)\n", + "fit = rfe.fit(X, Y)\n", + "print(\"Num Features: \", fit.n_features_)\n", + "print(\"Selected Features:\", fit.support_)\n", + "print(\"Feature Ranking: \", fit.ranking_)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#checking accuracy using data with selected features from feature importance\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.naive_bayes import GaussianNB\n", + "\n", + "array = train.values\n", + "X = array[:,[0,2,3,5,7]]\n", + "Y = array[:,11]\n", + "test_size = 0.32\n", + "seed = 3\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", + "random_state=seed)\n", + "model = GaussianNB()\n", + "model.fit(X_train, Y_train)\n", + "result = model.score(X_test, Y_test)\n", + "print(\"Accuracy: \", (result*100.0))\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#CHECKING ACCURACY WITH ALL FEATURES\n", + "array = train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "test_size = 0.32\n", + "seed = 3\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", + "random_state=seed)\n", + "model = GaussianNB()\n", + "model.fit(X_train, Y_train)\n", + "result = model.score(X_test, Y_test)\n", + "print(\"Accuracy: \", (result*100.0))\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train.head(5)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/.ipynb_checkpoints/KAYAGA NASHIM MILVAT-checkpoint.ipynb b/.ipynb_checkpoints/KAYAGA NASHIM MILVAT-checkpoint.ipynb new file mode 100644 index 0000000..60d7103 --- /dev/null +++ b/.ipynb_checkpoints/KAYAGA NASHIM MILVAT-checkpoint.ipynb @@ -0,0 +1,2767 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", + "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/kaggle/input/ace-class-assignment/Test.csv\n", + "/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\n" + ] + } + ], + "source": [ + "# This Python 3 environment comes with many helpful analytics libraries installed\n", + "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", + "# For example, here's several helpful packages to load in \n", + "\n", + "import numpy as np # linear algebra\n", + "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "# Input data files are available in the \"../input/\" directory.\n", + "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", + "\n", + "import os\n", + "for dirname, _, filenames in os.walk('/kaggle/input'):\n", + " for filename in filenames:\n", + " print(os.path.join(dirname, filename))\n", + "\n", + "# Any results you write to the current directory are saved as output." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0", + "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a" + }, + "outputs": [], + "source": [ + "import warnings\n", + "warnings.filterwarnings('ignore')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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count3038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.000000
mean2.0602378.5215200.97141073.6687600.994007-2.4329270.08854515.68323373.6508285.9113611.2352550.500000
std3.8199297.5866520.1074138.5274890.0313331.7072230.28413311.5756659.1660920.6936890.2100120.500082
min-16.0000000.0000000.68400042.7500000.866000-10.4320000.0000000.04100042.7780003.5330000.7850000.000000
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75%4.00000013.1580001.04100079.3437501.011000-1.2832500.00000026.80775079.7780006.3820001.3510001.000000
max30.00000046.6670001.451000101.6820001.1960003.5760001.00000051.280000103.1670008.6620002.1920001.000000
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+ "\n", + " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 CLASS \n", + "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", + "mean 73.650828 5.911361 1.235255 0.500000 \n", + "std 9.166092 0.693689 0.210012 0.500082 \n", + "min 42.778000 3.533000 0.785000 0.000000 \n", + "25% 67.556000 5.459250 1.082000 0.000000 \n", + "50% 73.697000 5.925500 1.184000 0.500000 \n", + "75% 79.778000 6.382000 1.351000 1.000000 \n", + "max 103.167000 8.662000 2.192000 1.000000 " + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Generate descriptive statistics that summarize the central tendency, dispersion, and shape of a dataset’s distribution, excluding NaN values\n", + "data.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "FULL_Charge 0\n", + "FULL_AcidicMolPerc 0\n", + "FULL_AURR980107 0\n", + "FULL_DAYM780201 0\n", + "FULL_GEOR030101 0\n", + "FULL_OOBM850104 0\n", + "NT_EFC195 0\n", + "AS_MeanAmphiMoment 0\n", + "AS_DAYM780201 0\n", + "AS_FUKS010112 0\n", + "CT_RACS820104 0\n", + "CLASS 0\n", + "dtype: int64" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#number of null values in each column\n", + "data.isnull().sum()\n", + "#since my data has no null values then its good to go" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201FULL_GEOR030101FULL_OOBM850104NT_EFC195AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CT_RACS820104CLASS
FULL_Charge1.000000-0.612996-0.490977-0.434603-0.058725-0.2837580.0880680.355477-0.365374-0.0905700.2329290.534602
FULL_AcidicMolPerc-0.6129961.0000000.7947960.5414810.1152010.513344-0.143168-0.4315900.4496210.002334-0.213543-0.598816
FULL_AURR980107-0.4909770.7947961.0000000.5482530.3461390.462712-0.169540-0.4260970.4562600.032958-0.403599-0.584111
FULL_DAYM780201-0.4346030.5414810.5482531.0000000.0101180.334778-0.090058-0.4087930.8941910.055915-0.326792-0.554838
FULL_GEOR030101-0.0587250.1152010.3461390.0101181.0000000.319157-0.230417-0.160269-0.0290850.040480-0.151935-0.260470
FULL_OOBM850104-0.2837580.5133440.4627120.3347780.3191571.000000-0.230561-0.3362970.275640-0.4527690.155304-0.453287
NT_EFC1950.088068-0.143168-0.169540-0.090058-0.230417-0.2305611.0000000.178683-0.0368440.1459240.0808980.260702
AS_MeanAmphiMoment0.355477-0.431590-0.426097-0.408793-0.160269-0.3362970.1786831.000000-0.3223780.0255800.1715240.693552
AS_DAYM780201-0.3653740.4496210.4562600.894191-0.0290850.275640-0.036844-0.3223781.0000000.045562-0.256060-0.437168
AS_FUKS010112-0.0905700.0023340.0329580.0559150.040480-0.4527690.1459240.0255800.0455621.000000-0.4452840.033432
CT_RACS8201040.232929-0.213543-0.403599-0.326792-0.1519350.1553040.0808980.171524-0.256060-0.4452841.0000000.267652
CLASS0.534602-0.598816-0.584111-0.554838-0.260470-0.4532870.2607020.693552-0.4371680.0334320.2676521.000000
\n", + "
" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 \\\n", + "FULL_Charge 1.000000 -0.612996 -0.490977 \n", + "FULL_AcidicMolPerc -0.612996 1.000000 0.794796 \n", + "FULL_AURR980107 -0.490977 0.794796 1.000000 \n", + "FULL_DAYM780201 -0.434603 0.541481 0.548253 \n", + "FULL_GEOR030101 -0.058725 0.115201 0.346139 \n", + "FULL_OOBM850104 -0.283758 0.513344 0.462712 \n", + "NT_EFC195 0.088068 -0.143168 -0.169540 \n", + "AS_MeanAmphiMoment 0.355477 -0.431590 -0.426097 \n", + "AS_DAYM780201 -0.365374 0.449621 0.456260 \n", + "AS_FUKS010112 -0.090570 0.002334 0.032958 \n", + "CT_RACS820104 0.232929 -0.213543 -0.403599 \n", + "CLASS 0.534602 -0.598816 -0.584111 \n", + "\n", + " FULL_DAYM780201 FULL_GEOR030101 FULL_OOBM850104 \\\n", + "FULL_Charge -0.434603 -0.058725 -0.283758 \n", + "FULL_AcidicMolPerc 0.541481 0.115201 0.513344 \n", + "FULL_AURR980107 0.548253 0.346139 0.462712 \n", + "FULL_DAYM780201 1.000000 0.010118 0.334778 \n", + "FULL_GEOR030101 0.010118 1.000000 0.319157 \n", + "FULL_OOBM850104 0.334778 0.319157 1.000000 \n", + "NT_EFC195 -0.090058 -0.230417 -0.230561 \n", + "AS_MeanAmphiMoment -0.408793 -0.160269 -0.336297 \n", + "AS_DAYM780201 0.894191 -0.029085 0.275640 \n", + "AS_FUKS010112 0.055915 0.040480 -0.452769 \n", + "CT_RACS820104 -0.326792 -0.151935 0.155304 \n", + "CLASS -0.554838 -0.260470 -0.453287 \n", + "\n", + " NT_EFC195 AS_MeanAmphiMoment AS_DAYM780201 \\\n", + "FULL_Charge 0.088068 0.355477 -0.365374 \n", + "FULL_AcidicMolPerc -0.143168 -0.431590 0.449621 \n", + "FULL_AURR980107 -0.169540 -0.426097 0.456260 \n", + "FULL_DAYM780201 -0.090058 -0.408793 0.894191 \n", + "FULL_GEOR030101 -0.230417 -0.160269 -0.029085 \n", + "FULL_OOBM850104 -0.230561 -0.336297 0.275640 \n", + "NT_EFC195 1.000000 0.178683 -0.036844 \n", + "AS_MeanAmphiMoment 0.178683 1.000000 -0.322378 \n", + "AS_DAYM780201 -0.036844 -0.322378 1.000000 \n", + "AS_FUKS010112 0.145924 0.025580 0.045562 \n", + "CT_RACS820104 0.080898 0.171524 -0.256060 \n", + "CLASS 0.260702 0.693552 -0.437168 \n", + "\n", + " AS_FUKS010112 CT_RACS820104 CLASS \n", + "FULL_Charge -0.090570 0.232929 0.534602 \n", + "FULL_AcidicMolPerc 0.002334 -0.213543 -0.598816 \n", + "FULL_AURR980107 0.032958 -0.403599 -0.584111 \n", + "FULL_DAYM780201 0.055915 -0.326792 -0.554838 \n", + "FULL_GEOR030101 0.040480 -0.151935 -0.260470 \n", + "FULL_OOBM850104 -0.452769 0.155304 -0.453287 \n", + "NT_EFC195 0.145924 0.080898 0.260702 \n", + "AS_MeanAmphiMoment 0.025580 0.171524 0.693552 \n", + "AS_DAYM780201 0.045562 -0.256060 -0.437168 \n", + "AS_FUKS010112 1.000000 -0.445284 0.033432 \n", + "CT_RACS820104 -0.445284 1.000000 0.267652 \n", + "CLASS 0.033432 0.267652 1.000000 " + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Its a good idea to review all the pairwise correlations of the attributes in the dataset because some machine learning algorithm like linear and logistic regression can suffer poor performance if there are highly c orrelated attributes in the dataset\n", + "data.corr(method='pearson')" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#plot a heat map to show the correlation of the data\n", + "plt.figure(figsize=(8,8))\n", + "sns.heatmap(data.corr(method='pearson'))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "FULL_Charge 0.534602\n", + "FULL_AcidicMolPerc -0.598816\n", + "FULL_AURR980107 -0.584111\n", + "FULL_DAYM780201 -0.554838\n", + "FULL_GEOR030101 -0.260470\n", + "FULL_OOBM850104 -0.453287\n", + "NT_EFC195 0.260702\n", + "AS_MeanAmphiMoment 0.693552\n", + "AS_DAYM780201 -0.437168\n", + "AS_FUKS010112 0.033432\n", + "CT_RACS820104 0.267652\n", + "CLASS 1.000000\n", + "Name: CLASS, dtype: float64" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#also checked the corelation in regards to the class since am trying to build a ML agorithm for that class\n", + "data.corr(method='pearson')['CLASS']" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + " data.skew().plot(kind='bar')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## understanding data with visualization" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Histogram\n", + "### I want to understand each attribute of my dataset independently" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Data pre-processing" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(20,20))\n", + "data.hist()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Standardize data" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[ 7.69712416e-01 -1.12341031e+00 -1.90047029e-01 1.37605977e-01\n", + " -6.06718766e-01 -7.20629784e-01 -3.11684110e-01 -1.33070267e+00\n", + " -2.25681314e-02 -3.60971652e-01 -9.25122883e-01]\n", + " [ 5.07884366e-01 -4.10857567e-01 -3.76275096e-01 -2.43225309e-01\n", + " -1.18128598e+00 -9.24503172e-01 3.20837658e+00 -1.30322672e+00\n", + " -5.92370366e-01 9.02050407e-01 1.03699430e+00]\n", + " [ 9.00626442e-01 -4.10857567e-01 -9.16336490e-01 -8.65106417e-03\n", + " -1.05360437e+00 -4.63244125e-02 -3.11684110e-01 -1.30383154e+00\n", + " -4.59030969e-01 -1.40916462e+00 2.31808537e+00]\n", + " [ 7.69712416e-01 -5.74065761e-01 -7.11485617e-01 -8.70124978e-01\n", + " 1.59370848e-01 6.27395116e-01 -3.11684110e-01 -1.30201709e+00\n", + " -7.01486075e-01 -2.30020073e+00 6.98862456e-01]\n", + " [ 1.42428254e+00 2.04070778e-03 -3.66963693e-01 -1.04957427e+00\n", + " -4.79037163e-01 2.00315519e-01 -3.11684110e-01 -1.30184429e+00\n", + " -7.71259861e-02 -1.97723618e+00 1.44656245e+00]]\n" + ] + } + ], + "source": [ + "from sklearn.preprocessing import StandardScaler\n", + "array = data.values\n", + "#separate array into input and output components\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "scaler = StandardScaler().fit(X)\n", + "rescaledX = scaler.transform(X)\n", + "# summarize transformed data\n", + "#set_printoptions(precision=3)\n", + "print(rescaledX[0:5,:])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Feature selection\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Chose Recursive Feature Elimination because i dont have the library for my data in this case\n" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Num Features: 8\n", + "Selected Features: [ True False True False True True True True False True True]\n", + "Feature Ranking: [1 3 1 2 1 1 1 1 4 1 1]\n" + ] + } + ], + "source": [ + "from sklearn.feature_selection import RFE\n", + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "array1 = data.values\n", + "X = array1[:,0:11]\n", + "Y = array[:,11]\n", + "# feature extraction\n", + "model = LogisticRegression()\n", + "rfe = RFE(model,8)\n", + "fit = rfe.fit(X,Y)\n", + "print(\"Num Features:\", fit.n_features_)\n", + "print(\"Selected Features:\", fit.support_)\n", + "print(\"Feature Ranking:\", fit.ranking_)" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", + " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", + " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", + " 'CLASS'],\n", + " dtype='object')" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data.columns" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " FULL_Charge FULL_AURR980107 FULL_GEOR030101 FULL_OOBM850104 \\\n", + "0 4.0 0.873 0.987 -4.833 \n", + "1 4.0 0.892 0.931 -0.584 \n", + "2 2.0 0.901 1.039 -5.664 \n", + "3 4.5 0.869 0.982 -5.423 \n", + "4 -4.0 1.061 0.976 -2.002 \n", + ".. ... ... ... ... \n", + "753 -1.5 1.100 0.991 -1.987 \n", + "754 -1.0 1.085 1.027 -0.745 \n", + "755 -1.0 1.108 1.033 -1.789 \n", + "756 -1.0 0.955 1.023 1.141 \n", + "757 -7.0 1.078 1.009 -0.066 \n", + "\n", + " NT_EFC195 AS_MeanAmphiMoment AS_FUKS010112 CT_RACS820104 \n", + "0 0 0.382 7.225 1.234 \n", + "1 0 0.320 4.942 1.853 \n", + "2 0 0.164 5.969 1.174 \n", + "3 0 2.010 5.462 1.138 \n", + "4 0 2.758 5.582 1.453 \n", + ".. ... ... ... ... \n", + "753 0 15.185 7.053 1.325 \n", + "754 0 16.550 6.729 1.132 \n", + "755 0 16.112 6.036 1.219 \n", + "756 0 20.630 5.669 1.111 \n", + "757 0 17.168 6.688 1.305 \n", + "\n", + "[758 rows x 8 columns]" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "drop_test = test.drop(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'AS_DAYM780201'],axis=1)\n", + "drop_test" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "seleceted_train = X[:,fit.support_]\n", + "selected_test = test.values[:,fit.support_]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Evaluate the Performance of Machine Learning Algorithms with Resampling¶\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Split into Train and Test Sets" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 91.55701754385966\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "array = data.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "test_size = 0.30\n", + "seed = 7\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", + "random_state=seed)\n", + "model = LogisticRegression()\n", + "model.fit(X_train, Y_train)\n", + "result = model.score(X_test, Y_test)\n", + "print(\"Accuracy: \", (result*100.0))\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## K-fold Cross Validation" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: (83.5359128018065, 27.08521320979506)\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "\n", + "array = data.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "\n", + "num_folds = 10 #number of folds to use\n", + "seed = 7 #reproducibility\n", + "\n", + "kfold = KFold(n_splits=num_folds, random_state=seed)\n", + "model = LogisticRegression()\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "\n", + "print(f\"Accuracy:\", (results.mean()*100.0, results.std()*100.0))\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Leave One Out Cross Validation" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: (91.4417379855168, 27.974673416141517)\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import LeaveOneOut\n", + "from sklearn.model_selection import cross_val_score\n", + "\n", + "array = data.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "num_folds = 10\n", + "loocv = LeaveOneOut()\n", + "model = LogisticRegression()\n", + "results = cross_val_score(model, X, Y, cv=loocv)\n", + "print(\"Accuracy:\", (results.mean()*100.0, results.std()*100.0))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Repeated Random Test-Train Splits" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: (91.30482456140349, 0.5803122202806698)\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import ShuffleSplit\n", + "from sklearn.model_selection import cross_val_score\n", + "\n", + "array = data.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "n_splits = 10\n", + "test_size = 0.30\n", + "seed = 7\n", + "kfold = ShuffleSplit(n_splits=n_splits, test_size=test_size, random_state=seed)\n", + "model = LogisticRegression()\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(\"Accuracy: \" , (results.mean()*100.0, results.std()*100.0))\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Machine Learning Algorithm Performance Metrics" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Algorithms Overview\n", + "### linear machine learning algorithms:\n", + "\n", + " Logistic Regression.\n", + " Linear Discriminant Analysis.\n", + "### onlinear machine learning algorithms\n", + "\n", + " k-Nearest Neighbors.\n", + " Naive Bayes.\n", + " Classication and Regression Trees.\n", + " Support Vector Machines.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Linear Machine Learning Algorithms" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Logistic Regression" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.835359128018065\n", + "MCC: 0.8342865299822478\n", + "[False True]\n", + "False: 383\n", + "True: 375\n" + ] + } + ], + "source": [ + "# Logistic Regression Classification\n", + "from pandas import read_csv\n", + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "array = data.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "num_folds = 10\n", + "kfold = KFold(n_splits=10, random_state=7)\n", + "model = LogisticRegression()\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(results.mean())\n", + "\n", + "model.fit(X,Y)\n", + "output = model.predict(test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "my_report = pd.DataFrame(output)\n", + "my_report.columns = ['CLASS']\n", + "my_report.index.name = \"Index\"\n", + "my_report['CLASS']=my_report['CLASS'].map({0.0:False, 1.0:True})\n", + "my_report.to_csv(\"report_XGB.csv\")\n", + "\n", + "print(my_report['CLASS'].unique())\n", + "print('False: ',my_report.groupby('CLASS').size()[0].sum())\n", + "print('True: ',my_report.groupby('CLASS').size()[1].sum())" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " FULL_Charge FULL_AURR980107 FULL_GEOR030101 FULL_OOBM850104 \\\n", + "0 4.0 0.873 0.987 -4.833 \n", + "1 4.0 0.892 0.931 -0.584 \n", + "2 2.0 0.901 1.039 -5.664 \n", + "3 4.5 0.869 0.982 -5.423 \n", + "4 -4.0 1.061 0.976 -2.002 \n", + ".. ... ... ... ... \n", + "753 -1.5 1.100 0.991 -1.987 \n", + "754 -1.0 1.085 1.027 -0.745 \n", + "755 -1.0 1.108 1.033 -1.789 \n", + "756 -1.0 0.955 1.023 1.141 \n", + "757 -7.0 1.078 1.009 -0.066 \n", + "\n", + " NT_EFC195 AS_MeanAmphiMoment AS_FUKS010112 CT_RACS820104 \n", + "0 0 0.382 7.225 1.234 \n", + "1 0 0.320 4.942 1.853 \n", + "2 0 0.164 5.969 1.174 \n", + "3 0 2.010 5.462 1.138 \n", + "4 0 2.758 5.582 1.453 \n", + ".. ... ... ... ... \n", + "753 0 15.185 7.053 1.325 \n", + "754 0 16.550 6.729 1.132 \n", + "755 0 16.112 6.036 1.219 \n", + "756 0 20.630 5.669 1.111 \n", + "757 0 17.168 6.688 1.305 \n", + "\n", + "[758 rows x 8 columns]" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "drop_test" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Linear Discriminant Analysis¶\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", + "\n", + "\n", + "array = data.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "num_folds = 10\n", + "kfold = KFold(n_splits=10, random_state=7)\n", + "model = LinearDiscriminantAnalysis()\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(results.mean())\n", + "\n", + "\n", + "model.fit(X,Y)\n", + "output = model.predict(test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "lda_report = pd.DataFrame(output)\n", + "lda_report.columns = ['CLASS']\n", + "lda_report.index.name = \"Index\"\n", + "lda_report['CLASS']=lda_report['CLASS'].map({0.0:False, 1.0:True})\n", + "lda_report.to_csv(\"ldareport.csv\")\n", + "\n", + "print(lda_report['CLASS'].unique())\n", + "print('False: ',lda_report.groupby('CLASS').size()[0].sum())\n", + "print('True: ',lda_report.groupby('CLASS').size()[1].sum())\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Nonlinear Machine Learning Algorithms" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### k-Nearest Neighbors" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.8027933385443807\n", + "MCC: 0.8690586462107053\n", + "[False True]\n", + "False: 402\n", + "True: 356\n" + ] + } + ], + "source": [ + "from sklearn.neighbors import KNeighborsClassifier\n", + "\n", + "array = data.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "num_folds = 10\n", + "kfold = KFold(n_splits=10, random_state=7)\n", + "model = KNeighborsClassifier()\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(results.mean())\n", + "\n", + "\n", + "\n", + "model.fit(X,Y)\n", + "output = model.predict(test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "report_k = pd.DataFrame(output)\n", + "report_k.columns = ['CLASS']\n", + "report_k.index.name = \"Index\"\n", + "report_k['CLASS']=report_k['CLASS'].map({0.0:False, 1.0:True})\n", + "report_k.to_csv(\"report_k.csv\")\n", + "\n", + "\n", + "print(report_k['CLASS'].unique())\n", + "print('False: ',report_k.groupby('CLASS').size()[0].sum())\n", + "print('True: ',report_k.groupby('CLASS').size()[1].sum())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Naive Bayes" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.880815746048289\n", + "MCC: 0.8407203694376205\n", + "[ True False]\n", + "False: 370\n", + "True: 388\n" + ] + } + ], + "source": [ + "from sklearn.naive_bayes import GaussianNB\n", + "array = data.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "kfold = KFold(n_splits=10, random_state=7)\n", + "model = GaussianNB()\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(results.mean())\n", + "\n", + "\n", + "model.fit(X,Y)\n", + "output = model.predict(test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "report_bayes = pd.DataFrame(output)\n", + "report_bayes.columns = ['CLASS']\n", + "report_bayes.index.name = \"Index\"\n", + "report_bayes['CLASS']=report_bayes['CLASS'].map({0.0:False, 1.0:True})\n", + "report_bayes.to_csv(\"report_bayes.csv\")\n", + "\n", + "\n", + "print(report_bayes['CLASS'].unique())\n", + "print('False: ',report_bayes.groupby('CLASS').size()[0].sum())\n", + "print('True: ',report_bayes.groupby('CLASS').size()[1].sum())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Classiffication and Regression Trees" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.tree import DecisionTreeClassifier\n", + "array = data.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "kfold = KFold(n_splits=10, random_state=7)\n", + "model = DecisionTreeClassifier()\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(results.mean())\n", + "\n", + "\n", + "model.fit(X,Y)\n", + "output = model.predict(test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "report_tree = pd.DataFrame(output)\n", + "report_tree.columns = ['CLASS']\n", + "report_tree.index.name = \"Index\"\n", + "report_tree['CLASS']=report_tree['CLASS'].map({0.0:False, 1.0:True})\n", + "report_tree.to_csv(\"report_tree.csv\")\n", + "\n", + "\n", + "print(report_tree['CLASS'].unique())\n", + "print('False: ',report_tree.groupby('CLASS').size()[0].sum())\n", + "print('True: ',report_tree.groupby('CLASS').size()[1].sum())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Support Vector Machines " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.svm import SVC\n", + "\n", + "array = data.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "kfold = KFold(n_splits=10, random_state=7)\n", + "model = SVC()\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(results.mean())\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/Assignment Colab/MARIA MAGDALENE NAMAGANDA (1).ipynb b/Assignment Colab/MARIA MAGDALENE NAMAGANDA (1).ipynb deleted file mode 100644 index 1a8c68c..0000000 --- a/Assignment Colab/MARIA MAGDALENE NAMAGANDA (1).ipynb +++ /dev/null @@ -1 +0,0 @@ -{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n for filename in filenames:\n print(os.path.join(dirname, filename))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# MARIA MAGDALENE NAMAGANDA\n# 2019/HD07/24853U\n# Kaggle assignment"},{"metadata":{},"cell_type":"markdown","source":"## Importing some of the needed packages and libraries"},{"metadata":{"trusted":true},"cell_type":"code","source":"import pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib import pyplot\nimport seaborn as sns\nfrom sklearn.metrics import classification_report\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis\nfrom sklearn.svm import SVC\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis\nfrom sklearn.metrics import confusion_matrix\nfrom sklearn.model_selection import KFold\nfrom sklearn.model_selection import train_test_split\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> Now i need to get rid of some unecessary warnings "},{"metadata":{"trusted":true},"cell_type":"code","source":"#To avoid unnecessary warnings, I will ignore them in the code below\nimport warnings\nwarnings.filterwarnings('ignore')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Loading the datasets to be used\n> There are two datasets, the train and test datasets "},{"metadata":{"_cell_guid":"","_uuid":"","trusted":true},"cell_type":"code","source":"#Loading the datasets, \n\nTrain = pd.read_csv(\"../input/amp-data-set/AMP_TrainSet.csv\")\nTest = pd.read_csv(\"../input/amp-data-set/Test.csv\")\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Exploring my data\n## Trying to know more about the data am dealing with"},{"metadata":{"trusted":true},"cell_type":"code","source":"#here, am trying to find the type of data\ntype(Train)\ntype(Test)\nTrain.dtypes\n#Test.dtypes","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# checking the dimensions of the data\n# this retuns the number of rows and columns in the data\n\nTrain.shape, Test.shape\n\n#this helps to know how big the data is in terms of rows and columns.\n#it also informs one of which data is labeled","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Data description\n>for now, I will focus more on the train dataset because its what I will use to train the model "},{"metadata":{"trusted":true},"cell_type":"code","source":"#getting a description of the data\n\nTrain.describe()\n\n#description gives a summary of the data.","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#looking at the first 5 entries of my data\nTrain.head()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> *From the Train dataset, i see there is an extra class column which will be my validation set*"},{"metadata":{},"cell_type":"markdown","source":"## Class Distribution"},{"metadata":{"trusted":true},"cell_type":"code","source":"Train.groupby('CLASS').size().plot(kind='bar')\npyplot.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> From the above barplot, I can see that the classes are evenly distributed so no need to use smote"},{"metadata":{},"cell_type":"markdown","source":"> I would like to know how many instaces i have for each class"},{"metadata":{"trusted":true},"cell_type":"code","source":"#getting the number of instances in each class\nTrain.groupby('CLASS').size()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Data Visualisation"},{"metadata":{},"cell_type":"markdown","source":"## Looking at the correlation of the data"},{"metadata":{"trusted":true},"cell_type":"code","source":"#first ill checkfor the pairwise correlation of the attributes.\nTrain.corr(method='pearson')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Reviewing inter-correlation of attributes using heatmap\n#graphical representation\nplt.figure(figsize=(6,6))\nsns.heatmap(Train.corr(method='pearson'))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Ill also check the correlation in regards to the 'CLASS' attribute\nTrain.corr(method='pearson')['CLASS']","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Train['CLASS'].value_counts","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Skewnwess of the data\n> knowing data skewness allows one to perform data preparation and improve a model"},{"metadata":{"trusted":true},"cell_type":"code","source":"Train.skew().plot(kind='bar')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Comparing Models"},{"metadata":{"trusted":true},"cell_type":"code","source":"#comparing different models to from which ill choose.\n\n\n# load dataset\n\narray = Train.values\n\n#split the dataset \nX = array[:,0:11] #X = Train.drop(columns=['CLASS'])\nY = array[:,11] #Y = Train['CLASS']\n\n# prepare models and add them to a list\nmodels = []\nmodels.append(('LR', LogisticRegression()))\nmodels.append(('LDA', LinearDiscriminantAnalysis()))\nmodels.append(('KNN', KNeighborsClassifier()))\nmodels.append(('CART', DecisionTreeClassifier()))\nmodels.append(('NB', GaussianNB()))\nmodels.append(('SVM', SVC()))\n\n# evaluate each model in turn\nresults = []\nnames = []\n\nfor name, model in models:\n kfold = KFold(n_splits=40, random_state=10)\n cv_results = cross_val_score(model, X, Y, cv=kfold, scoring='accuracy')\n results.append(cv_results)\n names.append(name)\n msg = (name, cv_results.mean(), cv_results.std())\n print(msg)\n\n# boxplot algorithm comparison\nfig = pyplot.figure()\nfig.suptitle('Algorithm Comparison')\nax = fig.add_subplot(111)\npyplot.boxplot(results)\nax.set_xticklabels(names)\npyplot.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Feature selection \n## Using recursive feature elimination"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.feature_selection import RFE\nfrom sklearn.linear_model import LogisticRegression\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = LogisticRegression()\nrfe = RFE(model, 4)\nfit = rfe.fit(X, Y)\nprint(\"Num Features: \", fit.n_features_)\nprint(\"Selected Features:\", fit.support_)\nprint(\"Feature Ranking: \", fit.ranking_)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Calling out the column names so I can know which features am going to drop from RFE\nTrain.columns","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Using Feature importance"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.ensemble import ExtraTreesClassifier\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = ExtraTreesClassifier()\nmodel.fit(X, Y)\nprint(model.feature_importances_)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## If am to use 4 features and drop the rest"},{"metadata":{"trusted":true},"cell_type":"code","source":"# I will call the new Train data with selected features New_Train.\nTrain\nNew_Train4 = Train.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#dropping the same features in the test dataset\nNew_Test4 = Test.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#viewing tselected features\nNew_Train4.columns","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Rescaling data"},{"metadata":{"trusted":true},"cell_type":"code","source":"from numpy import set_printoptions\nfrom sklearn.preprocessing import MinMaxScaler\narray = New_Train4.values\n\n#seperating data into onput and output options\nX = array[:,0:4]\nY = array[:,4]\nscaler = MinMaxScaler(feature_range = (0,1))\nrescaledX = scaler.fit_transform(X)\n\n#summarising transformed data\nset_printoptions(precision = 3)\nprint(rescaledX[0:4,:])\n ","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Standardising data"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.preprocessing import StandardScaler\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now splitting data\n#array = New_Train.values\nX = New_Train4.values[:,0:4]\nY = New_Train4.values[:,4]\nfrom sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size=0.2, random_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# also train and test the model on Matthews correlation coefficient.\nfrom sklearn.metrics import matthews_corrcoef\n\nGS = GaussianNB()\nGS.fit(X_Train,Y_Train)\npred = GS.predict(X_Test)\n\nprint(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Using four features gives me a very low MCC and low overall score.\n## I'll therefore consider using 8 features and see what score get"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.feature_selection import RFE\nfrom sklearn.linear_model import LogisticRegression\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = LogisticRegression()\nrfe = RFE(model, 8)\nfit = rfe.fit(X, Y)\nprint(\"Num Features: \", fit.n_features_)\nprint(\"Selected Features:\", fit.support_)\nprint(\"Feature Ranking: \", fit.ranking_)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# I will call the new Train data with selected features New_Train.\nTrain\nNew_Train8 = Train.drop(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'AS_DAYM780201'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#dropping the same features in the test dataset\nNew_Test8 = Test.drop(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'AS_DAYM780201'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now splitting data\n#array = New_Train.values\n\n\nX = New_Train8.values[:,0:8]\nY = New_Train8.values[:,8]\nfrom sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size=0.2, random_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now creating a model and training it on 8 features\nmodel = LogisticRegression(solver='liblinear', C=0.05, multi_class='ovr', random_state=30)\nmodel.fit(X_Train, Y_Train)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2,\nrandom_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.metrics import matthews_corrcoef\n\nnv = GaussianNB()\nnv.fit(X_Train,Y_Train)\npred = nv.predict(X_Test)\n\nprint(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Logistic Regression using 8 features"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = New_Train8.values\nX = array[:,0:8]\nY = array[:,8]\ntest_size = 0.30\nseed = 7\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\nrandom_state=seed)\nmodel = LogisticRegression()\nmodel.fit(X_train, Y_train)\nresult = model.score(X_test, Y_test)\nprint(\"Accuracy: \", (result*100.0))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Test.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#we now need to predict on the test dataset\n#md = pd.DataFrame((New_Test.index,nv.predict(New_Test))).T\n#md = md.rename(columns={0:\"Index\",1:\"CLASS\"}).set_index('Index')\n#md.to_csv('maria.csv')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#we now need to predict on the test dataset\nmd = pd.DataFrame((New_Test8.index,nv.predict(New_Test8))).T\nmd = md.rename(columns={0:\"Index\",1:\"CLASS\"}).set_index('Index')\nmd.to_csv('maria1.csv')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"import os\nos.listdir()\n!ls ../../kaggle/working/","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Using Naive Bayes and all the features"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\ntest_size = 0.35\nseed = 3\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\nrandom_state=seed)\nmodel = GaussianNB()\nmodel.fit(X_train, Y_train)\nresult = model.score(X_test, Y_test)\nprediction=model.predict(X_test)\nmatrix=matthews_corrcoef(Y_test,prediction)\nprint(\"Accuracy: \", (result*100.0))\nprint(matrix)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\nkfold = KFold(n_splits=10, random_state=7)\nmodel = GaussianNB()\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())\n\n\nmodel.fit(X,Y)\noutput = model.predict(Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria2_bayes = pd.DataFrame(output)\nmaria2_bayes.columns = ['CLASS']\nmaria2_bayes.index.name = \"Index\"\nmaria2_bayes['CLASS']=maria2_bayes['CLASS'].map({0.0:False, 1.0:True})\nmaria2_bayes.to_csv(\"maria2_bayes.csv\")\n\n\nprint(maria2_bayes['CLASS'].unique())\nprint('False: ',maria2_bayes.groupby('CLASS').size()[0].sum())\nprint('True: ',maria2_bayes.groupby('CLASS').size()[1].sum())","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4} \ No newline at end of file diff --git a/Assignment Colab/MARIA MAGDALENE NAMAGANDA FINAL.ipynb b/Assignment Colab/MARIA MAGDALENE NAMAGANDA FINAL.ipynb new file mode 100644 index 0000000..64c2fef --- /dev/null +++ b/Assignment Colab/MARIA MAGDALENE NAMAGANDA FINAL.ipynb @@ -0,0 +1 @@ +{"cells":[{"metadata":{},"cell_type":"markdown","source":"# MARIA MAGDALENE NAMAGANDA\n# 2019/HD07/24853U\n# Ace_class Kaggle assignment_1"},{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n for filename in filenames:\n print(os.path.join(dirname, filename))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Importing some of the needed packages and libraries"},{"metadata":{"trusted":true},"cell_type":"code","source":"import pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib import pyplot\nimport seaborn as sns\n\nfrom sklearn.model_selection import KFold\nfrom pandas import read_csv\nfrom sklearn.metrics import confusion_matrix\nfrom sklearn.metrics import classification_report\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.model_selection import train_test_split\n\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis\nfrom sklearn.svm import SVC\nfrom sklearn.ensemble import AdaBoostClassifier\nfrom sklearn.ensemble import GradientBoostingClassifier\nfrom sklearn.ensemble import ExtraTreesClassifier\nfrom sklearn.ensemble import RandomForestClassifier\nfrom xgboost import XGBClassifier\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> *Now i need to get rid of some unnecessary warnings by ignoring them*"},{"metadata":{"trusted":true},"cell_type":"code","source":"#To avoid unnecessary warnings, I will ignore them in the code below\nimport warnings\nwarnings.filterwarnings('ignore')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Loading the datasets \n### There are two datasets given; \n1. AMP_TrainSet.csv and \n2. Test.csv "},{"metadata":{"_cell_guid":"","_uuid":"","trusted":true},"cell_type":"code","source":"#Loading the datasets, \n\nTrain = pd.read_csv(\"../input/amp-data-set/AMP_TrainSet.csv\")\nTest = pd.read_csv(\"../input/amp-data-set/Test.csv\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### For training the model, I will first use the training set which I will further split into the train and validation set. \n### Then I will test the model on the Test set provided to gauge its performance."},{"metadata":{},"cell_type":"markdown","source":"# Exploring my data\n## Exploring data helps one understand what kind of data is given. That is to say knowing how much data it is, the shape, type, dimensions, missing values, data summary, correlation of attributes among others as am going to do in the following steps."},{"metadata":{"trusted":true},"cell_type":"code","source":"#here, am trying to find the type of data\ntype(Train)\ntype(Test)\nTrain.dtypes, Test.dtypes","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# checking the dimensions of the data\n# this retuns the number of rows and columns in the data\n\nTrain.shape, Test.shape\n\n#this helps to know how big the data is in terms of rows and columns.\n#also from here I can tell which data is labeled","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Data description\n>For now, I will focus more on the train dataset because its what I will use to train the model "},{"metadata":{"trusted":true},"cell_type":"code","source":"#getting a description of the train dataset\n#description gives a summary of the data.\n\nTrain.describe()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#looking at the first 5 entries of my data\nTrain.head()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Class Distribution\n> From the Train dataset, i see there is an extra 'CLASS' column which will be my validation set.\n### I need to know how this class is distributed to guide me on what to do with it."},{"metadata":{"trusted":true},"cell_type":"code","source":"#to see the class distribution, I will plot a bar graph\nTrain.groupby('CLASS').size().plot(kind='bar')\npyplot.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> I would like to know how many instaces i have for each class"},{"metadata":{"trusted":true},"cell_type":"code","source":"#getting the number of instances in each class\nTrain.groupby('CLASS').size()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### There are 1519 intances for each class which is proof for even distribution.\n### From the above barplot and class instances, I can see that the classes are evenly distributed so no need to use smote."},{"metadata":{},"cell_type":"markdown","source":"# Data Visualisation\n### Data visualization is the technique to present the data in a pictorial or graphical format. It enables one to analyze data visually. The data in a graphical format allows identification of new trends and patterns easily.\n### Visualisation identifies the relationship between data points and variables."},{"metadata":{},"cell_type":"markdown","source":"## Density plots"},{"metadata":{},"cell_type":"markdown","source":"> I chose to use density plots because they are better at determing the distribution shape as they are not affected by the number of bins as is the case with Histograms."},{"metadata":{"trusted":true},"cell_type":"code","source":"#now plotting density subplots\n#setting the figsize to 12 so that my graphs are not congested\nTrain.plot(kind='density', subplots = True, layout=(3,4), sharex= False, sharey= False, figsize=(12,12))\nplt.show()\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> From the above density subpots, I can see that most of the data follows a Gaussian distribution given some of the characteristics such as bell shaped curves and graphs being symmetrical about the mean."},{"metadata":{},"cell_type":"markdown","source":"## Box and whisker plots\n> A box plot is a type of graph that displays a summary of a large amount of data in terms of the median, upper quartile, lower quartile, minimum and maximum data values.\n\n> It handles large data easily, gives a clear summary and displays outliers."},{"metadata":{"trusted":true},"cell_type":"code","source":"#plotting a box and whisker graph\n#setting the figsize to 10 so that the plots are not congested.\nTrain.plot(kind='box', subplots = True, layout=(3,4), sharex= False, sharey= False, figsize=(10,10))\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Looking at the correlation of the data"},{"metadata":{},"cell_type":"markdown","source":"> Correlation is the relationship between two variables. The commonly used method is Pearson's correlation coefficient. It assumes a normal distribution of the attributes involved.\n\n> -1 shows full negative correlation, \n\n> +1 shows full negative correlation and \n\n> 0 shows no correlation at all."},{"metadata":{"trusted":true},"cell_type":"code","source":"#first I will checkfor the pairwise correlation of the attributes.\nTrain.corr(method='pearson')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Then now am reviewing the inter-correlation of attributes using heatmap\n#graphical representation\nplt.figure(figsize=(6,6))\nsns.heatmap(Train.corr(method='pearson'))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Ill also check the correlation in regards to the 'CLASS' attribute\nTrain.corr(method='pearson')['CLASS']","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Skewnwess of the data\n> knowing data skewness allows one to perform data preparation and improve a model\n\n> If Skewness value lies above +1 or below -1 then the data is highly skewed. \n\n> If skewness value lies between +0.5 and -0.5 then the data ids moderately skewed.\n\n> If skewness is 0 then data is symmetrical"},{"metadata":{"trusted":true},"cell_type":"code","source":"#Checking out skewness of data\nTrain.skew().plot(kind='bar')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Comparing Machine Learning Algorithms\n> This helps to choose the best model for the problem at hand.\n\n> Using resampling methods like cross validation, gives an estimate for how accurate each model may be on unseen data.\n\n> It is important to ensure that each algorithm is evaluated in the same way on the same data to avoid bias."},{"metadata":{"trusted":true},"cell_type":"code","source":"#comparing different models to from which ill choose.\n\n\n# load dataset\n\narray = Train.values\n\n#split the dataset \nX = array[:,0:11] #X = Train.drop(columns=['CLASS'])\nY = array[:,11] #Y = Train['CLASS']\n\n# preparing models and adding them to a list\nmodels = []\nmodels.append(('LR', LogisticRegression()))\nmodels.append(('LDA', LinearDiscriminantAnalysis()))\nmodels.append(('KNN', KNeighborsClassifier()))\nmodels.append(('CART', DecisionTreeClassifier()))\nmodels.append(('NB', GaussianNB()))\nmodels.append(('SVM', SVC()))\nmodels.append(('AB', AdaBoostClassifier()))\nmodels.append(('GBC', GradientBoostingClassifier()))\nmodels.append(('EXT', ExtraTreesClassifier()))\nmodels.append(('RTC', RandomForestClassifier()))\n#models.append(('XGB', XGBClassifier)) \n#am commenting out XGB it does not seem to be a scikit-learn estimator as it does not implement a 'get_params' methods.\n\n# evaluating each model in turn\nresults = []\nnames = []\n\nfor name, model in models:\n kfold = KFold(n_splits=50, random_state=42)\n cv_results = cross_val_score(model, X, Y, cv=kfold, scoring='accuracy')\n results.append(cv_results)\n names.append(name)\n msg = (name, cv_results.mean(), cv_results.std())\n print(msg)\n\n# boxplot algorithm comparison\nfig = pyplot.figure()\nfig.suptitle('Algorithm Comparison')\nax = fig.add_subplot(111)\npyplot.boxplot(results)\nax.set_xticklabels(names)\npyplot.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> ## From the above algorithm comparison, I can see that Naive Bayes(NB), ExtraTreesClassifiers(EXT) and RandomForestClassifiers(RTC) are some of the best performing algorithms. \n> ## Am yet to find out the overall best valgorithm after prediction on the Test set"},{"metadata":{},"cell_type":"markdown","source":"# Feature selection \n## Using recursive feature elimination\n> Sometimes, you may asses a dataset and find out that you do not need to use all the given features. This can be because some of them are highly correlates or they are not in any way helpful in developing the model.\n* It is therefore important to get rid of some features where applicable.\n\n> For this data, I will use Recursive Feature Elimination(RFE)"},{"metadata":{"trusted":true},"cell_type":"code","source":"#feature selection using RFE\n#first i will start with choosing 4 features\nfrom sklearn.feature_selection import RFE\nfrom sklearn.linear_model import LogisticRegression\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = LogisticRegression()\nrfe = RFE(model, 4)\nfit = rfe.fit(X, Y)\nprint(\"Num Features: \", fit.n_features_)\nprint(\"Selected Features:\", fit.support_)\nprint(\"Feature Ranking: \", fit.ranking_)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Calling out the column names so I can know which features am going to drop from RFE\nTrain.columns","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Using Feature importance"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.ensemble import ExtraTreesClassifier\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = ExtraTreesClassifier()\nmodel.fit(X, Y)\nprint(model.feature_importances_)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## If am to use 4 features and drop the rest\n> I will assign the new dataset a variable 'New_Train4' after choosing the 4 features and dropping the rest."},{"metadata":{"trusted":true},"cell_type":"code","source":"# I will call the new Train data with selected features New_Train4.\nTrain\nNew_Train4 = Train.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#dropping the same features in the test dataset\nNew_Test4 = Test.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#viewing the selected features\nNew_Train4.columns","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now splitting data\n#array = New_Train.values\nX = New_Train4.values[:,0:4]\nY = New_Train4.values[:,4]\nfrom sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size=0.2, random_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# also train and test the model on Matthews correlation coefficient.\nfrom sklearn.metrics import matthews_corrcoef\n\nGS = GaussianNB()\nGS.fit(X_Train,Y_Train)\npred = GS.predict(X_Test)\n\nprint(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Using four features gives me a very low MCC and low overall score.\n## I'll therefore consider using 8 features and see what score I get."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.feature_selection import RFE\nfrom sklearn.linear_model import LogisticRegression\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = LogisticRegression()\nrfe = RFE(model, 8)\nfit = rfe.fit(X, Y)\nprint(\"Num Features: \", fit.n_features_)\nprint(\"Selected Features:\", fit.support_)\nprint(\"Feature Ranking: \", fit.ranking_)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# I will call the new Train data with selected features New_Train8.\nTrain\nNew_Train8 = Train.drop(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'AS_DAYM780201'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#dropping the same features in the test dataset\nNew_Test8 = Test.drop(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'AS_DAYM780201'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now splitting data\n#array = New_Train.values\n\n\nX = New_Train8.values[:,0:8]\nY = New_Train8.values[:,8]\nfrom sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size=0.2, random_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now creating a model and training it on 8 features\nmodel = LogisticRegression(solver='liblinear', C=0.05, multi_class='ovr', random_state=30)\nmodel.fit(X_Train, Y_Train)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2,\nrandom_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.metrics import matthews_corrcoef\n\nnv = GaussianNB()\nnv.fit(X_Train,Y_Train)\npred = nv.predict(X_Test)\n\nprint(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Standardising data\n> This is useful to transform attributes with a Gaussian distribution and it workd better with rescaled data(also known as normalistaion where attributes are scaled into a range between 0 and 1)"},{"metadata":{},"cell_type":"markdown","source":"# Below are some of the algorithms I will be using;"},{"metadata":{},"cell_type":"markdown","source":"# LINEAR ALGORITHMS\n1. Linear Regression\n2. Logistic Regression\n3. Linear Discriminant Analysis"},{"metadata":{},"cell_type":"markdown","source":"# Logistic Regression using 8 features"},{"metadata":{"trusted":true},"cell_type":"code","source":"# here am using a dataset 'New_Train8' with 8 selected features\narray = New_Train8.values\nX = array[:,0:8]\nY = array[:,8]\n\nkfold = KFold(n_splits=10, random_state=42) #spliiting my data into 10 folds and random_state of 42 for reproducibility\nmodel = LogisticRegression() #calling out the prediction algorithm\nresults = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\nprint(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n\nmodel.fit(X,Y)\noutput = model.predict(New_Test8.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_logistic = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_logistic.columns = ['CLASS'] #renaming the output column to 'CLASS'\nmaria_logistic.index.name = \"Index\" #naming the index column as 'Index'\nmaria_logistic['CLASS']=maria_logistic['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_logistic.to_csv(\"maria_logistic.csv\") #changing my output file as a 'csv' file\n\nprint(maria_logistic['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\nprint('False: ',maria_logistic.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_logistic.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Applying Linear Dicriminant Analysis (LDA) using all features "},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\nnum_folds = 10\nkfold = KFold(n_splits=10, random_state=42) #spliiting my data into 10 folds and random_state of 42 for reproducibility\nmodel = LinearDiscriminantAnalysis() #calling out the prediction algorithm\nresults = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\nprint(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n\nmodel.fit(X,Y)\noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_LDA = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_LDA.columns = ['CLASS'] #renaming the output column to 'CLASS'\nmaria_LDA.index.name = \"Index\" #naming the index column as 'Index'\nmaria_LDA['CLASS']=maria_LDA['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_LDA.to_csv(\"maria_LDA.csv\") #changing my output file as a 'csv' file\n\nprint(maria_LDA['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\nprint('False: ',maria_LDA.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_LDA.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# NON LINEAR ALGORITHMS\n1. Naive Bayes\n2. Support Vector Machines\n3. K-Nearest Neighbours\n4. Classification and Regression Trees\n5. Learning Vector Quantization"},{"metadata":{},"cell_type":"markdown","source":"# Using Naive Bayes and all the features"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\ntest_size = 0.35 \n\nkfold = KFold(n_splits=10) #spliiting my data into 10 folds \n\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size, random_state=42) #random_state of 42 for reproducibility\n\nmodel = GaussianNB() #calling out the prediction algorithm\nresults = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\nprint(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n\n\nmodel.fit(X,Y)\noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria2_bayes = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria2_bayes.columns = ['CLASS'] #renaming the output column to 'CLASS'\nmaria2_bayes.index.name = \"Index\" #naming the index column as 'Index'\nmaria2_bayes['CLASS']=maria2_bayes['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria2_bayes.to_csv(\"maria2_bayes.csv\") #changing my output file as a 'csv' file\n\n\nprint(maria2_bayes['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\nprint('False: ',maria2_bayes.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria2_bayes.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Support Vector Machines algorithm using all features"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\nkfold = KFold(n_splits=10) #spliiting my data into 10 folds\n\nmodel = SVC() #calling out the prediction algorithm\nscoring = 'acuracy'\nresults = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\nprint(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n\nmodel.fit(X, Y)\noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nmcc = matthews_corrcoef(model.predict(X), Y)\nprint('MCC: ',mcc)\n\nmaria_svc = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_svc.columns = ['CLASS'] #renaming the output column to 'CLASS'\nmaria_svc.index.name = 'Index' #naming the index column as 'Index'\nmaria_svc['CLASS'] = maria_svc['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\n\nmaria_svc.to_csv('maria_svc.csv') #changing my output file as a 'csv' file\n\nprint(maria_svc['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\nprint('False: ',maria_svc.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_svc.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Applying Classification and Regression Trees"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.tree import DecisionTreeClassifier\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\nkfold = KFold(n_splits=10, random_state=42) #spliiting my data into 10 folds and random_state of 42 for reproducibility\nmodel = DecisionTreeClassifier() #calling out the prediction algorithm\nresults = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\nprint(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n\n\nmodel.fit(X,Y)\noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_tree = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_tree.columns = ['CLASS'] #renaming the output column to 'CLASS'\nmaria_tree.index.name = \"Index\" #naming the index column as 'Index'\nmaria_tree['CLASS']=maria_tree['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_tree.to_csv(\"maria_tree.csv\") #changing my output file as a 'csv' file\n\n\nprint(maria_tree['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\nprint('False: ',maria_tree.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_tree.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# K-Nearest Neighbours"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\n\nkfold = KFold(n_splits=10, random_state=42) #spliiting my data into 10 folds and random_state of 42 for reproducibility\nmodel = KNeighborsClassifier() #calling out the prediction algorithm\nresults = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\nprint(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n\nmodel.fit(X,Y) \noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_knn = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_knn.columns = ['CLASS'] #renaming the output column to 'CLASS' \nmaria_knn.index.name = \"Index\" #naming the index column as 'Index'\nmaria_knn['CLASS']=maria_knn['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_knn.to_csv(\"maria_knn.csv\") #changing my output file as a 'csv' file\n\n\nprint(maria_knn['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\nprint('False: ',maria_knn.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_knn.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Esemble Algorithms\n1. Boosting and Adaboost\n2. Bagging and Random forest"},{"metadata":{},"cell_type":"markdown","source":"# Applying Adaboost "},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\n\nX = array[:,0:11]\nY = array[:,11]\n\nkfold = KFold(n_splits=10, random_state=42)\n\nmodel = AdaBoostClassifier(n_estimators=200, random_state=42) \nresults = cross_val_score(model, X, Y, cv=kfold)\n\nprint(results.mean())\n\n\ntest_set = Test.values\nmodel.fit(X, Y)\noutput = model.predict(test_set)\n\nmcc = matthews_corrcoef(model.predict(X), Y)\nprint('MCC: ',mcc)\n\nmaria_AB= pd.DataFrame(output)\nmaria_AB.columns = ['CLASS']\nmaria_AB.index.name = 'Index'\nmaria_AB['CLASS'] = maria_AB['CLASS'].map({0.0:False, 1.0:True})\n\nmaria_AB.to_csv('maria_AB.csv')\n\nprint(maria_AB['CLASS'].unique())\nprint('False: ',maria_AB.groupby('CLASS').size()[0].sum())\nprint('True: ',maria_AB.groupby('CLASS').size()[1].sum())","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Applying Gradient Boosting Classifier"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\n\nX = array[:,0:11]\nY = array[:,11]\n\n#num_trees = 200\n#seed =42\n\nkfold = KFold(n_splits=10, random_state=42)\nmodel = GradientBoostingClassifier(n_estimators=200, random_state=42)\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())\n\nmodel.fit(X,Y) \noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_GBC = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_GBC.columns = ['CLASS'] #renaming the output column to 'CLASS' \nmaria_GBC.index.name = \"Index\" #naming the index column as 'Index'\nmaria_GBC['CLASS']=maria_GBC['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_GBC.to_csv(\"maria_GBC.csv\") #changing my output file as a 'csv' file\n\n\nprint(maria_GBC['CLASS'].unique()) #checking out the unique instances in the \nprint('False: ',maria_GBC.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_GBC.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Using Stochastic Gradient Boosting Classification"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\n\nkfold = KFold(n_splits=10, random_state=42)\nmodel = XGBClassifier(n_estimators=200, random_state=42)\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())\n\nmodel.fit(X,Y) \noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_XGB = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_XGB.columns = ['CLASS'] #renaming the output column to 'CLASS' \nmaria_XGB.index.name = \"Index\" #naming the index column as 'Index'\nmaria_XGB['CLASS']=maria_XGB['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_XGB.to_csv(\"maria_XGB.csv\") #changing my output file as a 'csv' file\n\n\nprint(maria_GBC['CLASS'].unique()) #checking out the unique instances in the \nprint('False: ',maria_XGB.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_XGB.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Using Extra Trees Classifier"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\n\nX = array[:,0:11]\nY = array[:,11]\n\nkfold = KFold(n_splits=10, random_state=42)\nmodel = ExtraTreesClassifier(n_estimators=200) # (max_features=11)\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())\n \nmodel.fit(X,Y) \noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_ETX = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_ETX.columns = ['CLASS'] #renaming the output column to 'CLASS' \nmaria_ETX.index.name = \"Index\" #naming the index column as 'Index'\nmaria_ETX['CLASS']=maria_ETX['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_ETX.to_csv(\"maria_ETX.csv\") #changing my output file as a 'csv' file\n\n\nprint(maria_ETX['CLASS'].unique()) #checking out the unique instances in the \nprint('False: ',maria_ETX.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_ETX.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column ","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# CONCLUSION\n## From the algorithm comparisons and my prediction scores, Naive Bayes algorithm performed the best.\n## I think this is because the data was following a Gaussian distribution(normally distributed) as seen earlier from the density subplots."}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4} \ No newline at end of file diff --git a/Assignment Colab/MARIA MAGDALENE NAMAGANDA.ipynb b/Assignment Colab/MARIA MAGDALENE NAMAGANDA.ipynb deleted file mode 100644 index 2f53cab..0000000 --- a/Assignment Colab/MARIA MAGDALENE NAMAGANDA.ipynb +++ /dev/null @@ -1 +0,0 @@ -{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n for filename in filenames:\n print(os.path.join(dirname, filename))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#import the necessary libraries you are going to use\nimport warnings\nwarnings.filterwarnings('ignore')\n\n# -----> Put your code here below:\n\n\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Working with AMP_Data_set\n## `Training and testing data in Machine Learning`\n"},{"metadata":{"_cell_guid":"","_uuid":"","trusted":true},"cell_type":"code","source":"#Load the datasets, there are two i.e the Train and Test datasets\n\nTrain = pd.read_csv(\"../input/amp-data-set/AMP_TrainSet.csv\")\nTest = pd.read_csv(\"../input/amp-data-set/Test.csv\")\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":">Getting to know more about the data"},{"metadata":{"trusted":true},"cell_type":"code","source":"#here, am trying to find the kind of data am dealing with.\nprint(type(Train))\nprint(type(Test))\nprint(Train.dtypes)\nprint(Test.dtypes)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# check the dimensions of your data\n# this retuns the number of rows and columns in the data\n\nTrain.shape, Test.shape\n\n#this helps to know how big the data is in terms of rows and columns.\n#it also informs one of which data is labeled","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> The data is pre-prepared so ill just continue to work with it, since the Train dataset is already labeled with a CLASS attribute."},{"metadata":{"trusted":true},"cell_type":"code","source":"#getting a description of the data\n#Train.describe, Test.describe\nTrain.describe()\nTest.describe()\n#description gives a summary of the data.","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#looking at the first 5 entries of my data\nTrain.head()\nTest.head()\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":">Looking at the skewness of the data"},{"metadata":{"trusted":true},"cell_type":"code","source":"#knowing data skewness allows one to perform data preparation and improve a model\nTrain.skew().plot(kind='bar')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> Data correlation."},{"metadata":{"trusted":true},"cell_type":"code","source":"#first ill review the pairwise correlation of the attributes.\nTrain.corr(method='pearson')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Reviewing inter-correlation of attributes using heatmap\n#graphical representation\nplt.figure(figsize=(6,6))\nsns.heatmap(Train.corr(method='pearson'))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Ill also check the correlation in regards to the 'CLASS' attribute\nTrain.corr(method='pearson')['CLASS']","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Train['CLASS'].value_counts","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#I need to know the distribution of the class attribute of my data.\nprint(Train.groupby('CLASS').size().plot(kind='bar'))\n#train.CLASS.value_counts().plot(kind='bar')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"\n### From the above bar graph, the Class distribution is even which means am dealing with balanced data."},{"metadata":{},"cell_type":"markdown","source":"# Feature selection \n## Using recursive feature elimination"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.feature_selection import RFE\nfrom sklearn.linear_model import LogisticRegression\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = LogisticRegression()\nrfe = RFE(model, 4)\nfit = rfe.fit(X, Y)\nprint(\"Num Features: \", fit.n_features_)\nprint(\"Selected Features:\", fit.support_)\nprint(\"Feature Ranking: \", fit.ranking_)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Calling out the column names so I can know which features am going to drop from RFE\nTrain.columns","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Using Feature importance"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.ensemble import ExtraTreesClassifier\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = ExtraTreesClassifier()\nmodel.fit(X, Y)\nprint(model.feature_importances_)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Am going to use 4 features and drop the rest"},{"metadata":{"trusted":true},"cell_type":"code","source":"# I will call the new Train data with selected features New_Train.\nTrain\nNew_Train = Train.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#dropping the same features in the test dataset\nNew_Test = Test.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#viewing tselected features\nNew_Train.columns","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Rescaling data"},{"metadata":{"trusted":true},"cell_type":"code","source":"from numpy import set_printoptions\nfrom sklearn.preprocessing import MinMaxScaler\narray = New_Train.values\n\n#seperating data into onput and output options\nX = array[:,0:4]\nY = array[:,4]\nscaler = MinMaxScaler(feature_range = (0,1))\nrescaledX = scaler.fit_transform(X)\n\n#summarising transformed data\nset_printoptions(precision = 3)\nprint(rescaledX[0:4,:])\n ","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Standardising data"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.preprocessing import StandardScaler\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Comparing models to use"},{"metadata":{"trusted":true},"cell_type":"code","source":"#comparing different models to from which ill choose.\nfrom matplotlib import pyplot\nfrom sklearn.model_selection import KFold\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.svm import SVC\n\n\n# load dataset\n\narray = New_Train.values\n\n#split the dataset \nX = array[:,0:4] #X = Train.drop(columns=['CLASS'])\nY = array[:,4] #Y = Train['CLASS']\n\n# prepare models and add them to a list\nmodels = []\nmodels.append(('LR', LogisticRegression()))\nmodels.append(('LDA', LinearDiscriminantAnalysis()))\nmodels.append(('KNN', KNeighborsClassifier()))\nmodels.append(('CART', DecisionTreeClassifier()))\nmodels.append(('NB', GaussianNB()))\nmodels.append(('SVM', SVC()))\n\n# evaluate each model in turn\nresults = []\nnames = []\n\nfor name, model in models:\n kfold = KFold(n_splits=40, random_state=10)\n cv_results = cross_val_score(model, X, Y, cv=kfold, scoring='accuracy')\n results.append(cv_results)\n names.append(name)\n msg = (name, cv_results.mean(), cv_results.std())\n print(msg)\n\n# boxplot algorithm comparison\nfig = pyplot.figure()\nfig.suptitle('Algorithm Comparison')\nax = fig.add_subplot(111)\npyplot.boxplot(results)\nax.set_xticklabels(names)\npyplot.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now slitting data\n#array = New_Train.values\nX = New_Train.values[:,0:4]\nY = New_Train.values[:,4]\nfrom sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size=0.2, random_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# also train and test the model on Matthews correlation coefficient.\nfrom sklearn.metrics import matthews_corrcoef\n\nGS = GaussianNB()\nGS.fit(X_Train,Y_Train)\npred = GS.predict(X_Test)\n\nprint(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now creating a model and training it\nmodel = LogisticRegression(solver='liblinear', C=0.05, multi_class='ovr', random_state=30)\nmodel.fit(X_Train, Y_Train)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2,\nrandom_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.metrics import matthews_corrcoef\n\nnv = GaussianNB()\nnv.fit(X_Train,Y_Train)\npred = nv.predict(X_Test)\n\nprint(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#model = DecisionTreeClassifier()\n\n#model.fit(X_train, y_train)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Test.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#we now need to predict on the test dataset\nmd = pd.DataFrame((New_Test.index,nv.predict(New_Test))).T\nmd = md.rename(columns={0:\"Index\",1:\"CLASS\"}).set_index('Index')\nmd.to_csv('maria.csv')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"import os\nos.listdir()\n!ls ../../kaggle/working/","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4} \ No newline at end of file diff --git a/Fezile Dlamini.ipynb b/Fezile Dlamini.ipynb new file mode 100644 index 0000000..2dd9fe7 --- /dev/null +++ b/Fezile Dlamini.ipynb @@ -0,0 +1,778 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", + "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" + }, + "outputs": [], + "source": [ + "# This Python 3 environment comes with many helpful analytics libraries installed\n", + "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", + "# For example, here's several helpful packages to load in \n", + "\n", + "import numpy as np # linear algebra\n", + "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", + "\n", + "# Input data files are available in the \"../input/\" directory.\n", + "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", + "\n", + "import os\n", + "for dirname, _, filenames in os.walk('/kaggle/input'):\n", + " for filename in filenames:\n", + " print(os.path.join(dirname, filename))\n", + "\n", + "# Any results you write to the current directory are saved as output." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Importing Libraries" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0", + "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a" + }, + "outputs": [], + "source": [ + "###Importing libraries\n", + "import pandas\n", + "import scipy\n", + "import numpy\n", + "import matplotlib\n", + "import sklearn\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Loading some libraries\n", + "### These are some of the libraries I think I will need" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from pandas import read_csv\n", + "from pandas.plotting import scatter_matrix\n", + "from matplotlib import pyplot\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.model_selection import StratifiedKFold\n", + "from sklearn.metrics import classification_report\n", + "from sklearn.metrics import confusion_matrix\n", + "from sklearn.metrics import accuracy_score\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "from sklearn.neighbors import KNeighborsClassifier\n", + "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", + "from sklearn.naive_bayes import GaussianNB\n", + "from sklearn.svm import SVC" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import warnings\n", + "warnings.filterwarnings('ignore')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Loading My Dataset\n", + "\n", + "##### I am going to first use my training dataset, then the test dataset last." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train = pandas.read_csv('/kaggle/input/ace-class-assignment/AMP_TrainSet.csv')\n", + "train\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "test= pandas.read_csv('/kaggle/input/ace-class-assignment/Test.csv')\n", + "test" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Inspecting my train dataset" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train.shape" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train.isnull().sum() ###this will show the number of null values in my data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train.count() #returns number of non-null values in my data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "##### It seems i have no missing values in my data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train.describe() #returns summary of the whole data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train.info() #It returns range, column, number of non-null objects of each column, datatype and memory usage" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "##### This shows that my dataset has 3038 rows (instances) and 12 columns (attributes)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "##### I will also take a look at how many instances i have for each class" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train.groupby('CLASS').size()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train.groupby('CLASS').size().plot(kind='bar')\n", + "pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### I have two groups of classes, each with 1519 instances" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# DATA VISUALISATION" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### I will start with univariate plots to see each indiviadual variable" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train.hist(figsize=(16,16))\n", + "pyplot.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train.corr(method='pearson')['CLASS'] #Here I tried to see the correlation of all attributes with the class" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Multivariate " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "correlations = train.corr()\n", + "# plot correlation matrix\n", + "fig = pyplot.figure()\n", + "ax = fig.add_subplot(111)\n", + "cax = ax.matshow(correlations, vmin=-1, vmax=1)\n", + "fig.colorbar(cax)\n", + "ticks = np.arange(0,9,1)\n", + "ax.set_xticks(ticks)\n", + "ax.set_yticks(ticks)\n", + "ax.set_xticklabels(train.columns)\n", + "ax.set_yticklabels(train.columns)\n", + "pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### i did this plot in order to see which features are highly correlated as this can be a problem in soome models if some features are used together whereas they are highly correlated." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# EVALUATING ALGORITHMS\n", + "#### I will now evaluate some algorithms and estimate their accuracy on unseen data." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Building models" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "array = train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "test_size = 0.32\n", + "seed = 3\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", + "random_state=seed)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "len(X_test)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "\n", + "models = []\n", + "models.append(('LR', LogisticRegression(solver='liblinear', multi_class='ovr')))\n", + "models.append(('LDA', LinearDiscriminantAnalysis()))\n", + "models.append(('KNN', KNeighborsClassifier()))\n", + "models.append(('CART', DecisionTreeClassifier()))\n", + "models.append(('NB', GaussianNB()))\n", + "models.append(('SVM', SVC(gamma='auto')))\n", + "# evaluate each model in turn\n", + "results = []\n", + "names = []\n", + "for name, model in models:\n", + " kfold = StratifiedKFold(n_splits=10)\n", + " cv_results = cross_val_score(model, X_train, Y_train, cv=kfold, scoring='accuracy')\n", + " results.append(cv_results)\n", + " names.append(name)\n", + " print('%s: %f (%f)' % (name, cv_results.mean(), cv_results.std()))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Compare Algorithms\n", + "pyplot.boxplot(results, labels=names)\n", + "pyplot.title('Algorithm Comparison')\n", + "pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### from here, NB is the best performing." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Make predictions on validation dataset\n", + "model = GaussianNB()\n", + "model.fit(X_train, Y_train)\n", + "predictions = model.predict(X_test)\n", + "print(predictions)\n", + "\n", + "#from sklearn.metrics import matthews_corrcoef\n", + "#print('MCC', matthews_corrcoef(model.predict(X_test), Y_test))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#with all features\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.naive_bayes import GaussianNB\n", + "\n", + "array = train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "test_size = 0.32\n", + "seed = 3\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", + "random_state=seed)\n", + "model = GaussianNB()\n", + "model.fit(X_train, Y_train)\n", + "result = model.score(X_test, Y_test)\n", + "print(\"Accuracy: \", (result*100.0))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Evaluate predictions\n", + "print(accuracy_score(Y_test, predictions))\n", + "print(confusion_matrix(Y_test, predictions))\n", + "print(classification_report(Y_test, predictions))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "test" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "Y=train.CLASS\n", + "X=train.drop(\"CLASS\",axis=1)\n", + "OUTPUT=model.fit(X, Y).predict(test.values)\n", + "OUTPUT_1=pd.DataFrame(OUTPUT)\n", + "OUTPUT_1.columns=[\"CLASS\"]\n", + "OUTPUT_1.index.name=\"Index\"\n", + "OUTPUT_1[\"CLASS\"]=OUTPUT_1[\"CLASS\"].map({0.0:False,1.0:True})\n", + "OUTPUT_1.to_csv(\"output\")\n", + "print(OUTPUT_1[\"CLASS\"].unique())\n", + "print(OUTPUT_1[\"CLASS\"].nunique())\n", + "print(OUTPUT_1.groupby(\"CLASS\").size()[0].sum())\n", + "print(OUTPUT_1.groupby(\"CLASS\").size()[1].sum())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#feature selection using feature importance\n", + "X = train.iloc[:,0:11] #independent columns\n", + "y = train.iloc[:,-1] #target column\n", + "from sklearn.ensemble import ExtraTreesClassifier\n", + "import matplotlib.pyplot as plt\n", + "model = ExtraTreesClassifier()\n", + "model.fit(X,y)\n", + "print(model.feature_importances_) #use inbuilt class feature_importances of tree based classifiers\n", + "#plot graph of feature importances for better visualization\n", + "feat_importances = pd.Series(model.feature_importances_, index=X.columns)\n", + "feat_importances.nlargest(10).plot(kind='barh')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train.columns" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "newtrain=train.drop([ 'FULL_AURR980107', 'FULL_OOBM850104', 'NT_EFC195', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104'], axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "newtest=test.drop([ 'FULL_AURR980107', 'FULL_OOBM850104', 'NT_EFC195', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104'], axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "newtrain" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "array = newtrain.values\n", + "X = array[:,0:5]\n", + "Y = array[:,-1]\n", + "test_size = 0.32\n", + "seed = 3\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", + "random_state=seed)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "models = []\n", + "models.append(('LR', LogisticRegression(solver='liblinear', multi_class='ovr')))\n", + "models.append(('LDA', LinearDiscriminantAnalysis()))\n", + "models.append(('KNN', KNeighborsClassifier()))\n", + "models.append(('CART', DecisionTreeClassifier()))\n", + "models.append(('NB', GaussianNB()))\n", + "models.append(('SVM', SVC(gamma='auto')))\n", + "# evaluate each model in turn\n", + "results = []\n", + "names = []\n", + "for name, model in models:\n", + " kfold = StratifiedKFold(n_splits=23, shuffle=True)\n", + " cv_results = cross_val_score(model, X_train, Y_train, cv=kfold, scoring='accuracy')\n", + " results.append(cv_results)\n", + " names.append(name)\n", + " print('%s: %f (%f)' % (name, cv_results.mean(), cv_results.std()))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "model = GaussianNB()\n", + "model.fit(X_train, Y_train)\n", + "result = model.score(X_test, Y_test)\n", + "print(\"Accuracy: \", (result*100.0))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Evaluate predictions\n", + "print(accuracy_score(Y_test, predictions))\n", + "print(confusion_matrix(Y_test, predictions))\n", + "print(classification_report(Y_test, predictions))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "Y=newtrain.CLASS\n", + "X=newtrain.drop(\"CLASS\",axis=1)\n", + "OUTPUT=model.fit(X, Y).predict(newtest.values)\n", + "OUTPUT_1=pd.DataFrame(OUTPUT)\n", + "OUTPUT_1.columns=[\"CLASS\"]\n", + "OUTPUT_1.index.name=\"Index\"\n", + "OUTPUT_1[\"CLASS\"]=OUTPUT_1[\"CLASS\"].map({0.0:False,1.0:True})\n", + "OUTPUT_1.to_csv(\"out1\")\n", + "print(OUTPUT_1[\"CLASS\"].unique())\n", + "print(OUTPUT_1[\"CLASS\"].nunique())\n", + "print(OUTPUT_1.groupby(\"CLASS\").size()[0].sum())\n", + "print(OUTPUT_1.groupby(\"CLASS\").size()[1].sum())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#checking accuracy using data with selected features from feature importance\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.naive_bayes import GaussianNB\n", + "from sklearn.metrics import matthews_corrcoef\n", + "\n", + "array = train.values\n", + "X = array[:,[0,1,3,5,7]]\n", + "Y = array[:,11]\n", + "test_size = 0.32\n", + "seed = 3\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", + "random_state=seed)\n", + "model = GaussianNB()\n", + "model.fit(X_train, Y_train)\n", + "result = model.score(X_test, Y_test)\n", + "prediction=model.predict(X_test)\n", + "matrix=matthews_corrcoef(Y_test,prediction)\n", + "print(\"Accuracy: \", (result*100.0))\n", + "print(matrix)\n", + "\n", + "# making predictions on the test data\n", + "\n", + "#output=model.predict(test.values)\n", + "#output1=pd.DataFrame(output)\n", + "#output1.columns=['CLASS']\n", + "#output1.index.name='Index'\n", + "#output1['CLASS']=output1['CLASS'].map({0.0:False, 1.0:True})\n", + "\n", + "#print(output1['CLASS'].unique())\n", + "#print(output1['CLASS'].nunique())\n", + "\n", + "#print(output1.groupby('CLASS').size()[0].sum())\n", + "#print(output1.groupby('CLASS').size()[1].sum())\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "array2 = np.array(test)\n", + "X = array2[:,[0,1,3,5,7]]\n", + "x_t=array[:,[0,1,3,5,7]]\n", + "y_t=array[:,11]\n", + "\n", + "#array3 = train.values\n", + "#X_t = array3[:,[0,1,3,5,7]]\n", + "#Y_t=array3[:,10]\n", + "test_size = 0.32\n", + "seed = 3\n", + "#X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", + "#random_state=seed)\n", + "test=array3[:,[0,1,3,5,7]]\n", + "model = GaussianNB()\n", + "\n", + "#result = model.score(X_t, Y_t)\n", + "model.fit(x_t, y_t)\n", + "prediction=model.predict(X)\n", + "\n", + "#matrix=matthews_corrcoef(Y_t,prediction)\n", + "#print(\"Accuracy: \", (result*100.0))\n", + "#print(matrix)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## FEATURE SELECTION" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#feature selection using Logistic regression\n", + "from sklearn.feature_selection import RFE\n", + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "array_1 = train.values\n", + "X = array_1[:,0:11]\n", + "Y = array_1[:,11]\n", + "# feature extraction\n", + "model = LogisticRegression()\n", + "rfe = RFE(model, 5)\n", + "fit = rfe.fit(X, Y)\n", + "print(\"Num Features: \", fit.n_features_)\n", + "print(\"Selected Features:\", fit.support_)\n", + "print(\"Feature Ranking: \", fit.ranking_)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#checking accuracy using data with selected features from feature importance\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.naive_bayes import GaussianNB\n", + "\n", + "array = train.values\n", + "X = array[:,[0,2,3,5,7]]\n", + "Y = array[:,11]\n", + "test_size = 0.32\n", + "seed = 3\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", + "random_state=seed)\n", + "model = GaussianNB()\n", + "model.fit(X_train, Y_train)\n", + "result = model.score(X_test, Y_test)\n", + "print(\"Accuracy: \", (result*100.0))\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#CHECKING ACCURACY WITH ALL FEATURES\n", + "array = train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "test_size = 0.32\n", + "seed = 3\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", + "random_state=seed)\n", + "model = GaussianNB()\n", + "model.fit(X_train, Y_train)\n", + "result = model.score(X_test, Y_test)\n", + "print(\"Accuracy: \", (result*100.0))\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train.head(5)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/KAYAGA NASHIM MILVAT.ipynb b/KAYAGA NASHIM MILVAT.ipynb new file mode 100644 index 0000000..60d7103 --- /dev/null +++ b/KAYAGA NASHIM MILVAT.ipynb @@ -0,0 +1,2767 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", + "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/kaggle/input/ace-class-assignment/Test.csv\n", + "/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\n" + ] + } + ], + "source": [ + "# This Python 3 environment comes with many helpful analytics libraries installed\n", + "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", + "# For example, here's several helpful packages to load in \n", + "\n", + "import numpy as np # linear algebra\n", + "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "# Input data files are available in the \"../input/\" directory.\n", + "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", + "\n", + "import os\n", + "for dirname, _, filenames in os.walk('/kaggle/input'):\n", + " for filename in filenames:\n", + " print(os.path.join(dirname, filename))\n", + "\n", + "# Any results you write to the current directory are saved as output." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0", + "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a" + }, + "outputs": [], + "source": [ + "import warnings\n", + "warnings.filterwarnings('ignore')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": 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+ "\n", + " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 CLASS \n", + "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", + "mean 73.650828 5.911361 1.235255 0.500000 \n", + "std 9.166092 0.693689 0.210012 0.500082 \n", + "min 42.778000 3.533000 0.785000 0.000000 \n", + "25% 67.556000 5.459250 1.082000 0.000000 \n", + "50% 73.697000 5.925500 1.184000 0.500000 \n", + "75% 79.778000 6.382000 1.351000 1.000000 \n", + "max 103.167000 8.662000 2.192000 1.000000 " + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Generate descriptive statistics that summarize the central tendency, dispersion, and shape of a dataset’s distribution, excluding NaN values\n", + "data.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "FULL_Charge 0\n", + "FULL_AcidicMolPerc 0\n", + "FULL_AURR980107 0\n", + "FULL_DAYM780201 0\n", + "FULL_GEOR030101 0\n", + "FULL_OOBM850104 0\n", + "NT_EFC195 0\n", + "AS_MeanAmphiMoment 0\n", + "AS_DAYM780201 0\n", + "AS_FUKS010112 0\n", + "CT_RACS820104 0\n", + "CLASS 0\n", + "dtype: int64" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#number of null values in each column\n", + "data.isnull().sum()\n", + "#since my data has no null values then its good to go" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201FULL_GEOR030101FULL_OOBM850104NT_EFC195AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CT_RACS820104CLASS
FULL_Charge1.000000-0.612996-0.490977-0.434603-0.058725-0.2837580.0880680.355477-0.365374-0.0905700.2329290.534602
FULL_AcidicMolPerc-0.6129961.0000000.7947960.5414810.1152010.513344-0.143168-0.4315900.4496210.002334-0.213543-0.598816
FULL_AURR980107-0.4909770.7947961.0000000.5482530.3461390.462712-0.169540-0.4260970.4562600.032958-0.403599-0.584111
FULL_DAYM780201-0.4346030.5414810.5482531.0000000.0101180.334778-0.090058-0.4087930.8941910.055915-0.326792-0.554838
FULL_GEOR030101-0.0587250.1152010.3461390.0101181.0000000.319157-0.230417-0.160269-0.0290850.040480-0.151935-0.260470
FULL_OOBM850104-0.2837580.5133440.4627120.3347780.3191571.000000-0.230561-0.3362970.275640-0.4527690.155304-0.453287
NT_EFC1950.088068-0.143168-0.169540-0.090058-0.230417-0.2305611.0000000.178683-0.0368440.1459240.0808980.260702
AS_MeanAmphiMoment0.355477-0.431590-0.426097-0.408793-0.160269-0.3362970.1786831.000000-0.3223780.0255800.1715240.693552
AS_DAYM780201-0.3653740.4496210.4562600.894191-0.0290850.275640-0.036844-0.3223781.0000000.045562-0.256060-0.437168
AS_FUKS010112-0.0905700.0023340.0329580.0559150.040480-0.4527690.1459240.0255800.0455621.000000-0.4452840.033432
CT_RACS8201040.232929-0.213543-0.403599-0.326792-0.1519350.1553040.0808980.171524-0.256060-0.4452841.0000000.267652
CLASS0.534602-0.598816-0.584111-0.554838-0.260470-0.4532870.2607020.693552-0.4371680.0334320.2676521.000000
\n", + "
" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 \\\n", + "FULL_Charge 1.000000 -0.612996 -0.490977 \n", + "FULL_AcidicMolPerc -0.612996 1.000000 0.794796 \n", + "FULL_AURR980107 -0.490977 0.794796 1.000000 \n", + "FULL_DAYM780201 -0.434603 0.541481 0.548253 \n", + "FULL_GEOR030101 -0.058725 0.115201 0.346139 \n", + "FULL_OOBM850104 -0.283758 0.513344 0.462712 \n", + "NT_EFC195 0.088068 -0.143168 -0.169540 \n", + "AS_MeanAmphiMoment 0.355477 -0.431590 -0.426097 \n", + "AS_DAYM780201 -0.365374 0.449621 0.456260 \n", + "AS_FUKS010112 -0.090570 0.002334 0.032958 \n", + "CT_RACS820104 0.232929 -0.213543 -0.403599 \n", + "CLASS 0.534602 -0.598816 -0.584111 \n", + "\n", + " FULL_DAYM780201 FULL_GEOR030101 FULL_OOBM850104 \\\n", + "FULL_Charge -0.434603 -0.058725 -0.283758 \n", + "FULL_AcidicMolPerc 0.541481 0.115201 0.513344 \n", + "FULL_AURR980107 0.548253 0.346139 0.462712 \n", + "FULL_DAYM780201 1.000000 0.010118 0.334778 \n", + "FULL_GEOR030101 0.010118 1.000000 0.319157 \n", + "FULL_OOBM850104 0.334778 0.319157 1.000000 \n", + "NT_EFC195 -0.090058 -0.230417 -0.230561 \n", + "AS_MeanAmphiMoment -0.408793 -0.160269 -0.336297 \n", + "AS_DAYM780201 0.894191 -0.029085 0.275640 \n", + "AS_FUKS010112 0.055915 0.040480 -0.452769 \n", + "CT_RACS820104 -0.326792 -0.151935 0.155304 \n", + "CLASS -0.554838 -0.260470 -0.453287 \n", + "\n", + " NT_EFC195 AS_MeanAmphiMoment AS_DAYM780201 \\\n", + "FULL_Charge 0.088068 0.355477 -0.365374 \n", + "FULL_AcidicMolPerc -0.143168 -0.431590 0.449621 \n", + "FULL_AURR980107 -0.169540 -0.426097 0.456260 \n", + "FULL_DAYM780201 -0.090058 -0.408793 0.894191 \n", + "FULL_GEOR030101 -0.230417 -0.160269 -0.029085 \n", + "FULL_OOBM850104 -0.230561 -0.336297 0.275640 \n", + "NT_EFC195 1.000000 0.178683 -0.036844 \n", + "AS_MeanAmphiMoment 0.178683 1.000000 -0.322378 \n", + "AS_DAYM780201 -0.036844 -0.322378 1.000000 \n", + "AS_FUKS010112 0.145924 0.025580 0.045562 \n", + "CT_RACS820104 0.080898 0.171524 -0.256060 \n", + "CLASS 0.260702 0.693552 -0.437168 \n", + "\n", + " AS_FUKS010112 CT_RACS820104 CLASS \n", + "FULL_Charge -0.090570 0.232929 0.534602 \n", + "FULL_AcidicMolPerc 0.002334 -0.213543 -0.598816 \n", + "FULL_AURR980107 0.032958 -0.403599 -0.584111 \n", + "FULL_DAYM780201 0.055915 -0.326792 -0.554838 \n", + "FULL_GEOR030101 0.040480 -0.151935 -0.260470 \n", + "FULL_OOBM850104 -0.452769 0.155304 -0.453287 \n", + "NT_EFC195 0.145924 0.080898 0.260702 \n", + "AS_MeanAmphiMoment 0.025580 0.171524 0.693552 \n", + "AS_DAYM780201 0.045562 -0.256060 -0.437168 \n", + "AS_FUKS010112 1.000000 -0.445284 0.033432 \n", + "CT_RACS820104 -0.445284 1.000000 0.267652 \n", + "CLASS 0.033432 0.267652 1.000000 " + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Its a good idea to review all the pairwise correlations of the attributes in the dataset because some machine learning algorithm like linear and logistic regression can suffer poor performance if there are highly c orrelated attributes in the dataset\n", + "data.corr(method='pearson')" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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S90XEYoD0c4v8TkkbpPO6ttLBkiZKmi1p9mtvuvBjZmatpdELlJelKZa8aqlhrVLGNmBKej0FGA9c18O4P0zrbrYA9inrd5WkDYF+wIcBIuIlSV8CrgE6gT+QVXtK5zE5Is6X9FHgl5J2BdTNOayJTwC/rzaFFRGTgEkA2w7erXlTczMzqx0vUG6oF4FNy9oGAy/0duC09uXTwBmSFgL/ARwmaaMexv0m8AGy9TZXlPX9PLA98N/ARaXGiLgpIvaOiI8CjwFPpF3HAVNTn3uA9YDNySo5Q3PjDuHdKa5qlkjaKl3jVsDzZfvH4SksMzMrqGZMdmYB+0raEiDdhTWQlad21tTBwMMRMTQihkXEdmRTO0dExGvA4tIC4nTX0hiyhczviIhO4KfAOvk7pdK+t8kSoX0kfSiNs0X6uSnwZeDS1P0ZoBTrQ2TJzl+AacA4SQMlbQ8MB+7v5rqmAcem18cCN5Z2SNoY+Pt8m5mZmRcoN1BELAFOBqZLmgP8BGhLSUbJXEkdaft/qW1Crq1D0pAKw7cB5WuDrgU+l14fA5ye4v4O+F5a21N+jgH8APhWhX3LgPOBU1LTTyU9AvweOCciHk/t3wBOkPQwWdVlQmQWkFV8HgFuAU6MiBUAkq4mWwC9U7rG49JY5wAfl/QE8PH0vuRI4NaIeL3C52FmZtbyGrpmJyIGVWm/kSqViIgYVmW4yT2IN6FC2zSyyggR8QhwQE+OjYhrSQt+I2J02b7zc68r3t6eYu1bZd/ZwNkV2quN9SKpSlRh32R68NmYmVnBNPHdU7XW6AXKZmZm1ggFWqDcssmOpPvI1vrkjY+IeY04HzMzM2uMlk12ImLvRp+DmZlZ0ypQZafpFiibmZmZ1VLLVnbMzMysC+EFymZmZtbKPI1lZmZm1hqc7JiZmRVRZ9R+6wFJYyQ9Jqld0qlV+nxW0iOSFkj6795eqqexzMzMrC7SMyovIvu2/w5glqRp6Yt2S32GA6cB+6YHam/R27hOdszMzIqoMc+y2gtoj4inACRNAcaSPSKp5ATgooh4CSAiyh9uvdo8jWVmZlZEjZnG2oaVH+zdkdrydgR2lPR7SfdKGtPbS3Vlx1ay0YAN6h5zxczb6h4ToPP2mQ2Ju+7Xzm1I3JuuOKMhcf9h+XN1j7l5NOaftgHq15C4632z4rKHPjfw1sl1jzm4/4Z1jwkwsP+AhsRd20iaCEzMNU2KiEn5LhUOK8+S+gPDgdHAEOAuSbtGxMtrel5OdszMzAoo+uDW85TYTOqiSwcwNPd+CLCoQp97I+Jt4GlJj5ElP7PW9Lw8jWVmZmb1MgsYLml7SesC44BpZX1uAA4AkLQ52bTWU70J6sqOmZlZEfXwVvFaiojlkk4CZgD9gMsiYoGks4DZETEt7TtE0iPACuCbEfFib+I62TEzM7O6iYjpwPSytjNyrwP4etpqwsmOmZlZETXm1vOGcLJjZmZWRA2YxmoUL1A2MzOzlubKjpmZWRH5qedmZmZmrcGVHTMzsyIq0JodJztmZmZFVKC7sTyNZWZmZi3NlR0zM7MiKtA0lis7ZmZm1tJc2TEzMyugvnjqebNqWGVH0gpJc3LbMEkTJF1Y1u8OSaPS64XpCaj5/asc00XMhZLmpe0RST+QNLCsz9ck/U3Sxun9FpKelrRlrs/Fkk6VNFpSSDout29kajslvb8md40LJc1J7QMkXZHO5VFJp+XGGCPpMUntkk7NtV+V2udLukzSgNQuSRek/nMlfTh3zC2SXpb0m558RmZmVhCdUfutSTVyGmtZRIzIbQvrFPeAiNgN2At4PzCpbH8b2SPojwSIiOeBc4EfAaREYj/g/NR/HnB07vhxwMOlNxFxdOkagWuB69KuzwAD07nsCXwxJXz9gIuAw4CdgTZJO6djrgI+COwGrA8cn9oPA4anbSLws9z5/BAY39MPx8zMrNUUds1ORLwG/AtwhKTBAJJ2AAYBp5MlPSWTgB0kHQBcCJwUEW+nfc8A60l6nyQBY4Cby+OlfZ8Fri6dArChpP5kictbwKtkSVh7RDwVEW8BU4Cx6ZynRwLcDwxJY40Frky77gU2kbRVOmYm8NfefFZmZtaCXNmpi/Vz0zvXN+IEIuJV4GmyighkCc7VwF3ATpK2SP06gS+RVWYej4g7y4b6NVml5u+AB4E3K4TbH1gSEU/kjnkdWEyWMP0oIpYC2wDP5o7rSG3vSNNX44FbUlO3x3RF0kRJsyXNfmnZ8z09zMzMbK3QyAXKy9LUTl61tLAv00XlXo8DjoyITknXkSUwFwFExBxJ84GLK4wxFbiGbIrparKkp1wpkSrZC1gBbA1sCtwl6bdl51NSfv0XA3dGxF0VrqHaMVVFxCTSdN4u79u7eVNzMzOrnQJ9qWCz3Y31Itkv/rzBwAt9EUzSRsAw4HFJu5NVeG7LZpxYF3iKlOwknWlbSUT8WdLbwMeBkylLdtJU1afI1uaUfA64JU2HPS/p98AosgrN0Fy/IcCi3FjfBd4LfDHXp6OrY8zMzIqs2dbszAL2Ld35lO7CGsjKUzQ1IWkQWYXkhoh4iazycmZEDEvb1sA2krbr4ZBnAN+OiBUV9h0M/DEiOnJtzwAHpjupNgT2Af5I9hkMl7S9pHXJqk3T0jkfDxwKtKWptZJpwDFprH2AVyJicQ/P28zMiqhAa3aaqrITEUsknQxMl7QO8Bqr/mKfK6n0fiowF5gg6Yhcn33KEou829Ni4XWA64Hvp/ZxZHc15V2f2s/twbn/oYvd41h5CguyitHlwHyyaajLI2IugKSTgBlAP+CyiFiQjrkE+BNwT6o+XRcRZwHTgcOBduAN4J9KQSTdRTa9NkhSB3BcRMzo7nrMzKy1RRMnJ7XWsGQnIgZVab8RuLHKvmFVhpvcw5jVjicitq/Q9vWy96PL3t8B3FHhuDPL3k+o0Oc1sjVBlc5lOlkCU95e8c8r3Z11YpV9+1dqNzMzK4qmquyYmZlZnbiys3aTdB/ZWp+88RExrxHnY2ZmZo3TkslOROzd6HMwMzNragV6NlZLJjtmZmbWjQJNYzXbredmZmZmNeXKjpmZWRG5smNmZmbWGlzZMTMzK6DsK9qKwcmOmZlZEXkay8zMzKw1uLJjZmZWRAWq7DjZsZWMX2943WPefdnyuscEGLHTnxsS96YrzmhI3AlzzmpI3D8fdkLdY7azrO4xAfZfb0hD4l5y+BUNibtZ9kDiutqt36Z1jwmwyWa7NCSu1YaTHTMzswIq0lPPvWbHzMzMWporO2ZmZkVUoMqOkx0zM7MiKs5zQD2NZWZmZq3NlR0zM7MC8gJlMzMzsxbhyo6ZmVkRFaiy42THzMysiLxA2czMzKw1uLJjZmZWQF6gbGZmZtYiXNkxMzMrIq/ZMTMzs1YWnVHzrSckjZH0mKR2Sad20e8oSSFpVG+v1cmOmZmZ1YWkfsBFwGHAzkCbpJ0r9NsI+CpwXy3iNjTZkbRC0pzcNkzSBEkXlvW7o5TZSVooafOy/asc00XMQZJ+JulJSQ9JekDSCWnfMEnLys7pmLRvY0lXpuOeTK83rnDcI2nfgFzM01IG+5ikQ1PbepLul/SwpAWSvpfrv72k+yQ9IekaSeum9o9JelDScklHlV3Xsan/E5KOzbWfLelZSa/15PMxM7OC6OyDrXt7Ae0R8VREvAVMAcZW6Pd94Dzgb2t0bWUaXdlZFhEjctvCOsS8FHgJGB4RI4ExwODc/ifLzunK1P4L4KmI2CEidgCeTmOtdBywGzAE+CxAyljHAbukWBenzPZN4MCI2AMYAYyRtE8a61zgxxExPJ3rcan9GWAC8N/5C5I0GPgusDfZX6TvSto07b4ptZmZmTXaNsCzufcdqe0dkkYCQyPiN7UK2uhkp64k7UD2i//0iOgEiIi/RMS53Rz3AWBPskyz5CxgVBrzHRGxArifd//wxgJTIuLNiHgaaAf2ikyp2jIgbSFJwIHAr9O+K4Aj0tgLI2Iuq+bPhwK3RcTSiHgJuI0ssSIi7o2Ixd19NmZmVizRWftN0kRJs3PbxLKwqnQq7+yU1gF+DHyjltfa6GRn/dx00fV1iLcL8HAp0alih7JprP3J5hXnpEQGeCepmZPGfIek9cgqLLekpqpZrKR+kuYAz5MlK/cBmwEvR8Ty8v5d6DZT7kr+L+f9rz3R08PMzGxt1gfTWBExKSJG5bZJZVE7gKG590OARbn3GwG7AndIWgjsA0zr7SLlRic7+WmsI1NbteXcNf/2I0nfSQlN/oMun8a6iywTrRQ/375DSlxeBJ5JFZhSn3IBWcKUpr6GAHtJ2rWr/l1dyhoc827H3F/OvQYN7+lhZmZmq2sWMDytTV2XbJnHtNLOiHglIjaPiGERMQy4F/hkRMzuTdBGJzuVvAhsWtY2GHihBmM/AuyRymRExNkp2XhPN8ctAEaWjoN3Sm17AI+mptKanQ8A+0j6ZGrvLoslIl4G7iCbenoB2ERS/2r9K+g2hpmZWV5fTGN1GzObtTgJmEH2+3NqRCyQdFbu92bNNWOyMwvYV9KWAKl0NZCVp2nWSES0A7OBH6RFwqVpp0qVkfLjHgJOzzWfDjyY9uX7LgZOBU5LTdOAcZIGStoeGA7cL+m9kjZJ57A+cDDwx4gI4HagdLfVscCN3VzaDOAQSZumhcmHpDYzM7OmEhHTI2LHdMPP2antjIiYVqHv6N5WdaAJk52IWAKcDExP00I/AdrK1tnMldSRtv+X2ibk2jokDakS4niydTHtkh4Afgt8O7e/fM3OV1P7ccCO6RbyJ4EdefcuqXI3ABtI2j8iFgBTyapKtwAnpvU+WwG3S5pLluDdllt5/m3g65La07n+AkDSRyR1AJ8B/lPSgvSZLSVbPD0rbWelNiSdl47ZIH0uZ1Y5ZzMzK5LG3HreEA19XEREDKrSfiNVqhlpDq+SyT2M+SrwxSr7FgLrV9n3EvCFLo7bNfc+yKa4Su/PBs4uO2YuMLLKeE9R4XbxiJhFNkVV6ZjLgMsqtH8L+FalY8zMzIrAz8YyMzMroJ6ssWkVLZvsSLqPbK1P3viImNeI8zEzM2smTnZaQETs3ehzMDMzs8Zr2WTHzMzMqitSZafp7sYyMzMzqyVXdszMzIoouvyKuZbiZMfMzKyAPI1lZmZm1iJc2TEzMyug6CzONJYrO2ZmZtbSXNkxMzMroCKt2XGyY2ZmVkDhu7GsqO6Jl+se88S2xvwfrvOVxvz1/4flzzUk7p8PO6Ehcbe8+ef1D7rnKfWPCcxbvrQhcU/epDErEg5b8mLdY17auX3dYwIcv2JRQ+JabTjZMTMzK6AiTWN5gbKZmZm1NFd2zMzMCsi3npuZmZm1CFd2zMzMCiii0WdQP052zMzMCsjTWGZmZmYtwpUdMzOzAnJlx8zMzKxFuLJjZmZWQF6gbGZmZi3N01hmZmZmLcKVHTMzswIq0lPPXdkxMzOzllb3ZEfSCklzctswSRMkXVjW7w5Jo9LrhZI2L9u/yjFdxNxY0pWSnkzblZI2zu3fRdLvJD0u6QlJ/yZJuTh/See6QNKvJW2Q9p0pKSR9IDfW11Jb6dzbJM2TNFfSLaXrSMc+l/scDs+NcZqkdkmPSTo0136ZpOclzS+7vsGSbkvnfpukTcv2fyR97kf15PMyM7PWF52135pVIyo7yyJiRG5bWIeYvwCeiogdImIH4GngUgBJ6wPTgHMiYkdgD+DvgC/njr8mnesuwFvA0bl984BxufdHAY+ksfsDPwUOiIjdgbnASbm+P859DtPTMTun8XYBxgAXS+qX+k9ObeVOBWZGxHBgZnpPGq8fcC4wo9tPyczMCqMzVPOtWbX8NFaquuwJfD/XfBYwStIOwOeA30fErQAR8QZZQnJqhbH6AxsCL+WabwDGpv3vB14B/lI6JG0bpkrRe4BF3ZzyWGBKRLwZEU8D7cBe6dzuBJZWOeaK9PoK4Ijcvq8A1wLPdxPXzMysJTUi2Vk/N3VzfR3i7QzMiYgVpYb0eg5Z9WQX4IH8ARHxJDBI0ntS09GS5gDPAYOBm3LdXwWelbQr0AZckxvnbeBLZNWfRelcfpE79qQ0vXVZbuppG+DZXJ+O1NaV90XE4hRzMbAFgKRtgCMIullZAAAgAElEQVSBS7o6WNJESbMlzV742jPdhDIzs1YQoZpvzarR01hHprZqX21Ui688UpVxSu3V9ufjXxMRI4AtyRKXb5b1m0I29XQE8E4CJ2kAWbIzEtiabBrrtLT7Z8AOwAhgMXB+7ryqncfq+gnw7XyiV0lETIqIURExatigbdcwlJmZWXNqlmmsF4FNy9oGAy/UYOwFwEhJ71xrer0H8GjaPyp/QJqOei0i/ppvj4ggq+p8rCzGTcB44JmIeDXXPiId92Q6dirZeiAiYklErIiITuDnpKkqskrO0NwYQ+h+6muJpK3SuW/Fu1NWo4ApkhaSrSW6WNIRlYcwM7MiiU7VfGtWzZLszAL2lbQlQLqTaSArT+eskYhoBx4CTs81nw48mPZdBewn6eAUe33gAuC8KkPuBzxZFmMZ8G3g7LK+zwE7S3pvev9xsgSrlJSUHAmU7rCaBoyTNFDS9sBw4P5uLnMacGx6fSxwYzqv7SNiWEQMA34NfDkibuhmLDMzs5bSFF8qGBFLJJ0MTE9Vl9eAtlT1KJkrqfR+KtmU0ISySsU+EdFRIcRxwH9IaiebJrontRERyySNTfsvAvoBvwTyt7UfLWk/suSwA5hQ4RqmVGhbJOl7wJ2S3gb+lDv2PEkjyKaoFgJfTMcskDSV7I6u5cCJpWkoSVcDo4HNJXUA342IXwDnAFMlHQc8A3ymwmdgZmb2Dj8bqw9FxKAq7TeSKhIV9g2rMtzkHsZ8CfhCF/vnkSURlfZNrhYnIs6s0j469/oSKiwQjojxXZzP2axaJSIi2qr0fxE4qNp4qc+ErvabmVmxNPO0U601yzSWmZmZWZ9oimmsWpF0H9lan7zxqXJjZmZmSTN/CWCttVSyExF7N/oczMzMrLm0VLJjZmZmPdPMXwJYa052zMzMCqhId2N5gbKZmZm1NFd2zMzMCqhIC5Rd2TEzM7O6kTRG0mOS2iWdWmH/1yU9kh6UPVPSdr2N6WTHzMysgBrx1HNJ/YCLgMOAnYE2STuXdXsIGBURu5M96qja45t6zMmOmZlZAUXUfuuBvYD2iHgqIt4CpgBjVz6vuD0i3khv7yV7IHavONkxMzOzetmGlR/y3ZHaqjkOuLm3Qb1A2czMrID6YoGypInAxFzTpIiYlO9S4bCKNSFJXwBGAX/f2/NysmMr+ee33lP3mN+9obP7Tn3gLTZoSNzNozH/t2tnWUPisucpdQ95+QM/qntMgAd2r/+1Akx7tTF/lyetU/9/L5YyoO4xAW7a7L0Nibu2SYnNpC66dABDc++HAIvKO0k6GPgO8PcR8WZvz8vJjpmZWQE16BuUZwHDJW0PPAeMAz6X7yBpJPCfwJiIeL4WQb1mx8zMzOoiIpYDJwEzgEeBqRGxQNJZkj6Zuv0QGAT8StIcSdN6G9eVHTMzswJq1JcKRsR0YHpZ2xm51wfXOqaTHTMzswIq0KOxPI1lZmZmrc2VHTMzswLys7HMzMzMWoQrO2ZmZgXUoFvPG8LJjpmZWQE15utcG8PTWGZmZtbSXNkxMzMroKj4mKrW5MqOmZmZtTRXdszMzAqos0DfKuhkx8zMrIA6PY1lZmZm1hqc7FQhKSSdn3t/iqQzJX0nPYV1jqQVuddfrTLOmZKey/WbI2kTSaMlvZJr+23umGMkzZe0QNIjkk5J7Z9JbZ2SRuX6ryvpcknzJD0saXRu3x2SHsvF2aJPPjAzM1urBKr51qw8jVXdm8CnJP17RLxQaoyIs4GzASS9FhEjejDWjyPiR/kGSQB3RcQ/lrUfBvwf4JCIWCRpPWB82j0f+BTwn2Xjn5DObbeUzNws6SMRUfoahc9HxOwenKeZmVnLcWWnuuXAJOBrdY57GnBKRCwCiIi/RcTP0+tHI+KxCsfsDMxMfZ4HXgZGVehXkaSJkmZLmj3jjfZeX4CZmTW/zj7YmpWTna5dBHxe0sa9HOdruWmk23Pt++fav5PadgUeWM3xHwbGSuovaXtgT2Bobv/lKca/KZWU8iJiUkSMiohRh27wgdUMbWZm1tw8jdWFiHhV0pXAV4FlvRhqlWmsZJVprDV0GfAhYDbwJ+APZJUpyKawnpO0EXAt2ZTYlTWIaWZma7FmXmNTa67sdO8nwHHAhnWKt4CsMtNjEbE8Ir4WESMiYiywCfBE2vdc+vlX4L+BvWp8vmZmthbyNJa9IyKWAlPJEp56+HfgPElbAkgaWO1OrxJJG0jaML3+OLA8Ih5J01qbp/YBwD+SLXI2MzMrDE9j9cz5wEm9OP5rkr6Qe39EtY4RMV3S+4DfpvU1QTZNhaQjgf8A3gv8j6Q5EXEosAUwQ1In8Bzv3r01MLUPAPoBvwV+3ovrMDOzFtHMlZhac7JTRUQMyr1eAmzQVZ8uxjkTOLPCroXAHVWOuRy4vEL79cD1FdoXAjtVaH+d1ZwSMzMzazVOdszMzAqoSAuUnezUSLp1/DNlzb9KX0JoZmbWVDqLk+s42amV/Dcrm5mZWfNwsmNmZlZAfuq5mZmZWYtwZcfMzKyAotEnUEdOdszMzAqoSN+z42ksMzMza2mu7JiZmRVQp7xA2czMzKwluLJjZmZWQF6gbIW1zwcX1T3mvz66rO4xAdSg75gYoH4Nibv/ekMaEnfe8qV1j/nA7qfUPSbAnnN/1JC4Z4z8ckPibtp/87rH3LGzMf9ebPuvIxoS12rDyY6ZmVkBFeluLCc7ZmZmBVSkZ2N5gbKZmZm1NFd2zMzMCsjPxjIzMzNrEa7smJmZFZBvPTczM7OW5gXKZmZmZi3ClR0zM7MCKtL37LiyY2ZmZi3NlR0zM7MC8gJlMzMza2leoGxmZmbWBySNkfSYpHZJp1bYP1DSNWn/fZKG9Tamkx0zM7MC6uyDrTuS+gEXAYcBOwNtknYu63Yc8FJEfAD4MXDuGl9k4mTHzMzM6mUvoD0inoqIt4ApwNiyPmOBK9LrXwMHSerVpFuPkh1JR0oKSR9M79eRdIGk+ZLmSZolafsujl8o6a6ytjmS5vfm5LuI11/SC5L+vcbjvlal/V8kHZNeT5b0hqSNcvt/mj6/zWt5Pj0l6V8bEdfMzJpXIyo7wDbAs7n3HamtYp+IWA68Amy2WhdXpqeVnTbgbmBcen80sDWwe0TsBhwJvNzNGBtJGgog6UNrcK6r4xDgMeCzvc0GeyIiLomIK3NN7aRMVdI6wAHAc319Hl1wsmNmZn1O0kRJs3PbxPIuFQ4rvzGsJ31WS7fJjqRBwL5kc2ilZGcrYHFEdAJEREdEvNTNUFPJkiTIkqerczH6SfphqhDNlfTFUmxJMyU9mCpIpQRimKRHJf1c0gJJt0paPxerDfgp8AywTy7OQkn/V9I96Q/hw5JmSHpS0r+kPqMl3SnpekmPSLokJSylMc6W9LCkeyW9L7WdKemUXPyrc9c6Gvg9sDw3xtdTVWy+pP+Tu6Y/Sro0tV8l6WBJv5f0hKS9Ur8NJV2WPquHcp/JBEnXSbol9T8vtZ8DrJ8qaVd182dkZmYFEeqDLWJSRIzKbZPKwnYAQ3PvhwCLqvWR1B/YGFjam2vtSWXnCOCWiHgcWCrpw2SJyyfSL9DzJY3swTi/Bj6VXn8CuCm37zjglYj4CPAR4IQ0LfY34MiI+DBZdeT8XKVmOHBRROxCVlX6NEBKeg4CfkOWdLSVncezEfFR4C5gMnAUWUJ0Vq7PXsA3gN2AHXLnvSFwb0TsAdwJnFDlWp8A3itp0xR/SmmHpD2BfwL2TnFPyH1+HyBL0nYHPgh8DtgPOIV3qzPfAX6XPqsDgB9K2jDtG0GWZO0GHC1paEScCiyLiBER8flKJ5vPxH+5qPzvnJmZtaIGTWPNAoZL2l7SumRFlGllfaYBx6bXR5H9zuvbyg4r/7KeArRFRAewE3Aa2fXNlHRQN+MsBV6SNA54FHgjt+8Q4BhJc4D7yObmhpOVsv6vpLnAb8nm8d6Xjnk6Iuak1w8Aw9LrfwRuj4g3gGuBI9Pq75LShzoPuC8i/hoRfwH+JmmTtO/+tHhqBVnCtF9qf4ssiSqPWcl1ZH+Ie5MlViX7AddHxOsR8Vrqt3/umualitkCYGb6A56Xi3UIcGr6rO4A1gO2TftmRsQrEfE34BFguy7O7x35THz81lv35BAzM7PVltbgnATMIMsFpkbEAklnSfpk6vYLYDNJ7cDXgVVuT19dXX6poKTNgAOBXSUF0A8ISd+KiDeBm4GbJS0hqwDN7CbeNWS3nE0oDwV8JSJmlMWfALwX2DMi3pa0kOyXO8Cbua4rgNI0Vhuwb+oLWeJ0AFmylD+us2yMTt79PMozyNL7t3PZ5Qq6/vymAA8CV0REZ27pUFdriMrPJ3+upVgCPh0Rj+UPlLQ3q34m/tJIMzOrqFHPxoqI6cD0srYzcq//BnymljG7q+wcBVwZEdtFxLCIGAo8DXxM0tbwzgLc3YE/9SDe9cB5ZBld3gzgS5IGpDF3TFMzGwPPp0TnALqpVEh6D1nlZNt0vsOAE1l1Kqs7e6US2zpk00J3r+bxRMQzZFNOF5ftuhM4QtIG6RqPZOXKT3dmAF8pTef1cArx7dJna2ZmVjTd/Zd/G3BOWdu1ZGtdlkoamNruBy7sLlhE/JX05UBlN0ldSjZN82D6Jf4XskrRVcBNkmYDc4A/dhPiU2Rze/kKx43Aeblz7Yl7yK57N7Lk5PrVOPYdEfGfFdoelDSZ7DMDuDQiHlLPvyHy+8BPgLnps1pINnXXlUmp/4PV1u2YmVmxFOnZWOrlmp+WI2k0cEpEdJdAtKQlo0fX/S/EgY8uq3dIANTljGLfGbDSErL62X+9IQ2JO295r26iWCP/3rlR9536wJ5zf9SQuP8w8ssNifu5zvp/ddiOnY3592LkuTs2JO76x/x7n/1D9dNtv1Dzf+9Pfua/mvKJW/4GZTMzM2tpNV3AKuk+oHy6aHxEzKtlnL4UEXeQ3eVkZmbWshq1QLkRaprsRMTetRzPzMzMrLd8a7KZmVkBubJjZmZmLa1Ityd5gbKZmZm1NFd2zMzMCqizKW8S7xuu7JiZmVlLc2XHzMysgIq0QNmVHTMzM2tpruyYmZkVUJHuxnKyYyv51BP1L/b94ZBBdY8JNKyuud43T21I3EsOv6IhcU/epP4f9LRXN6h7TIAzGvSMqv956OKGxJ26+xl1j/njdZfXPSbA/FNmNiTuo8f03didBUp3PI1lZmZmLc2VHTMzswLyAmUzMzOzFuHKjpmZWQEVZ8WOkx0zM7NC8jSWmZmZWYtwZcfMzKyA/GwsMzMzsxbhyo6ZmVkBFelLBZ3smJmZFVBxUh1PY5mZmVmLc2XHzMysgHzruZmZmVmLcGXHzMysgLxA2czMzFpacVKdtWgaS9KRkkLSB9P7dSRdIGm+pHmSZknavovjF6Z+8yQ9IukHkgaW9fmapL9J2ji930LS05K2zPW5WNKpkkan8zkut29kajslvb9G0py0LZQ0J7UPkHRFOpdHJZ2WG2OMpMcktUs6Ndd+VWqfL+kySQNSu9Ln0C5prqQP5465RdLLkn6z5p+8mZnZ2m2tSXaANuBuYFx6fzSwNbB7ROwGHAm83M0YB6S+ewHvByZViDErjUVEPA+cC/wIICUS+wHnp/7z0nmUjAMeLr2JiKMjYkREjACuBa5Luz4DDEznsifwRUnDJPUDLgIOA3YG2iTtnI65CvggsBuwPnB8aj8MGJ62icDPcufzQ2B8N5+JmZkVUGcfbM1qrUh2JA0C9gWO491kZytgcUR0AkRER0S81JPxIuI14F+AIyQNTjF2AAYBp5MlPSWTgB0kHQBcCJwUEW+nfc8A60l6nyQBY4CbK5y/gM8CV5dOAdhQUn+yxOUt4FWyJKw9Ip6KiLeAKcDYdM7TIwHuB4akscYCV6Zd9wKbSNoqHTMT+GtPPhMzM7NWtVYkO8ARwC0R8TiwNFVYpgKfSFNE50sauToDRsSrwNNkFRHIEpyrgbuAnSRtkfp1Al8iq8w8HhF3lg31a7JKzd8BDwJvVgi3P7AkIp7IHfM6sJgsYfpRRCwFtgGezR3XkdrekaavxgO3pKZuj+mOpImSZkua/efXF63OoWZmtpbqJGq+Nau1JdlpI6tykH62RUQHsBNwGln1bKakg1Zz3Pxj0MYBU1Jycx1ZAgNARMwB5gMXVxhjaupbSpaqnX9+317ACrJpuO2Bb0h6f9n5vBO+7P3FwJ0RcVeFa6h2TJciYlJEjIqIUVtuuPXqHGpmZtb0mv5uLEmbAQcCu0oKoB8Qkr4VEW+STRvdLGkJWQVoZg/H3QgYBjwuaXeyCs9t2YwT6wJPka2fKak4JRkRf5b0NvBx4GSyCk8+Tn/gU2Rrc0o+R1apeht4XtLvgVFkFZqhuX5DgEW5sb4LvBf4Yq5PR1fHmJmZVdK8dZjaWxsqO0eRrUnZLiKGRcRQsumnj0naGrI7s4DdgT/1ZMC0Buhi4Ia0zqcNODONPywitga2kbRdD8/xDODbEbGiwr6DgT+mSlTJM8CB6U6qDYF9gD+SLY4eLml7SeuSVZumpXM+HjiUrKqVT7qmAceksfYBXomIxT08bzMzK6giLVBu+soOWSJyTlnbtcBksvU7pdvH7ydbQNyV29Ni4XWA64Hvp/ZxZHc15V2f2s/t7gQj4g9d7B7HqtNbFwGXk02NCbg8IuYCSDoJmEFWwbosIhakYy4hS+buSdWn6yLiLGA6cDjQDrwB/FMpiKS7yO7gGiSpAzguImZ0dz1mZmatpOmTnYgYXaHtAuCC1RxnWBf7Vvl+noj4elfnERF3AHdUOO7MsvcTKvR5jdyaoLJ908kSmPL2in9W6e6sE6vs279Su5mZWRRoImttmMYyMzMzW2NNX9lZXZLuAwaWNY+PiHmNOB8zM7Nm1MxrbGqt5ZKdiNi70edgZmbW7Jr5e3FqzdNYZmZm1tJarrJjZmZm3StOXceVHTMzM2txTnbMzMwKqNmejSVpsKTbJD2Rfm5aoc8ISfdIWiBprqSjezK2kx0zM7MCasJvUD4VmBkRw8ke/XRqhT5vAMdExC7AGOAnkjbpbmAnO2ZmZtYMxgJXpNdXkD3vciUR8XhEPJFeLwKeJ3tmZJec7JiZmRVQ9MH/JE2UNDu3TVyNU3pf6dmO6ecWXXWWtBfZg7uf7G5g341lZmZmNRERk4BJ1fZL+i2wZYVd31mdOJK2An4JHFv2cOyKnOyYmZkVUCO+QTkiDq62T9ISSVtFxOKUzDxfpd97gP8BTo+Ie3sS18mOreTj/beqe8wpt6vuMQHWb9CXTAy8dXJD4m6mxnzOhy15se4xJ63znrrHBNi0/+YNiTt19zMaEvezc8+qe8zv79yjm29q7l8H7NSQuAUzDTgWOCf9vLG8g6R1geuBKyPiVz0d2Gt2zMzMCqgv1uz00jnAxyU9AXw8vUfSKEmXpj6fBT4GTJA0J20juhvYlR0zM7MCarYHgUbEi8BBFdpnA8en1/8F/Nfqju3KjpmZmbU0V3bMzMwKqDOK83QsV3bMzMyspbmyY2ZmVkDFqes42TEzMyuk3j64c23iaSwzMzNraa7smJmZFVANvhdnreHKjpmZmbU0V3bMzMwKqNm+VLAvOdkxMzMrIC9QNjMzM2sRruyYmZkVkBcoNzlJR0oKSR9M79eRdIGk+ZLmSZolafsujl+Y+pWemPp3kkZL+k1Zv8mSjkqv75A0Kr0eJukJSYdK2kDSVWm8+ZLuljQo9Rsj6TFJ7ZJOzY17UmoLSZvn2pWuo13SXEkfzu27RdLLFc6x2lifT2PMlfQHSXus6edtZma2NltbKzttwN3AOOBM4Ghga2D3iOiUNAR4vZsxDoiIF0pvJI3uSeA09gzgGxExQ9JpwJKI2C3t3wl4W1I/4CKyx9R3ALMkTYuIR4DfA78B7igb/jBgeNr2Bn6WfgL8ENgA+GLZMdXGehr4+4h4SdJhwKTcWGZmVnBFWqC81lV2UtVkX+A4smQHYCtgcUR0AkRER0S81AfhtwRuBU6PiGm52M+VOkTEYxHxJrAX0B4RT0XEW8AUYGzq81BELKww/ljgysjcC2wiaat0zEzgr+UHVBsrIv6Q+wzuBYasyQWbmZmt7da6ZAc4ArglIh4HlqapnqnAJ9KU1PmSRvZgnNtT//tWI/aVwIUR8atc22XAtyXdI+kHkoan9m2AZ3P9OlJbV9bkmJ44Dri52k5JEyXNljT7gdfaaxDOzMyaXUTUfGtWa2Oy00ZWJSH9bIuIDmAn4DSyytxMSQd1M84BETEiIkpTO9X+lPLtvwXGS9rgnZ0Rc4D3k00zDSabrvoQoG7GqmRNjul6QOkAsmTn29X6RMSkiBgVEaP2HPSB3oQzM7O1RCdR861ZrVVrdiRtBhwI7CopgH5ASPpWmjq6GbhZ0hKyCtDM1Rj+RWDTsrbBwAu59+cBXwB+JWlsRCwHiIjXgOuA6yR1AocDfwCG5o4dAizq5hw61uCYqiTtDlwKHBYRL67pOGZmZmuzta2ycxTZmpbtImJYRAwlW4j7MUlbQ3ZnFrA78KfVHPsJYOtUlUHSdsAewJyyfl8DXgV+ke6e2lfSpumYdYGdU+xZwHBJ26f2ccA0ujYNOCaNuw/wSkQsXs3rIJ3LtmQJ2Pg05WdmZvaOzj7YmtXaluy0AdeXtV0LTAZukjQfmAssBy5cnYFTZegLwOWS5gC/Bo6PiFfK+gVwLNnC5POAHYD/lTQPeAiYDVybqj4nkd259SgwNSIWAEj6qqQOssrNXEmXpuGnA08B7cDPgS+X4kq6C/gVcJCkDkmHdjPWGcBmwMVpbdLs1fk8zMzMWsVaNY0VEaMrtF0AXLCa4wyr0v57YJ/uYqe7qw7J7b6yyjHTyRKY8vaK55wSqROrjLV/lfZqYx0PHF/pGDMzsyJ9qeBaleyYmZlZbTTzguJaa+lkJ91WPrCseXxEzGvE+ZiZmVn9tXSyk7ut3MzMzHKa+Xtxam1tW6BsZmZmtlpaurJjZmZmlTXzreK15mTHzMysgIp0N5ansczMzKylubJjZmZWQEW69dyVHTMzM2tpruyYmZkVkG89NzMzM2sRruyYmZkVUJHW7DjZsZUc1e+V7jvV2Pkqf6LH/2/vvOPlqsq2fd0JRToEpYMBaQpCkAgoonRRQQSkBPVFpbx+WCiiAmJFEQQERJEXAY0NDChFlA4ioJTQCQHpHVEQkV5yf3+sNWQymTkn5Mza+5yZ58pvfpm99sy+18zsM/PsZz2lGm568R+16I6ZY75adN8+epFadE+ctnzlmk8yZ+WaACtPe74W3aPmeqUW3YPftmPlmrfc9tvKNQHu3WDPWnRLEqnnQRAEQRAEPUJ4doIgCIKgD5kWAcpBEARBEAS9QXh2giAIgqAP6R+/Thg7QRAEQdCX9FM2VixjBUEQBEHQ04RnJwiCIAj6kPDsBEEQBEEQ9Ajh2QmCIAiCPqSfemOFsRMEQRAEfUgsYwVBEARBEPQIYewEQRAEQR/iAv+GgqQxki6UdGf+v2NDP0kLSnpY0o9m5dhh7ARBEARBMBzYH7jY9krAxXm7EwcDl83qgcPYCYIgCII+xHbXb0Nka2Bivj8R+Ei7B0laG1gcuGBWDxzGThAEQRAEXUHSHpImN932eB1PX9z2owD5/8XaHH8UcCTwpdczrxFn7EhaQtKpku6WdJukSyU9J+lGSU9Kujffv6jD88dKej4/5jZJv5A0Z8tjjslrgaNaxj+QP7ypkm6XdEQeX0XSn/Mxp0o6IY/PKWmipFvy+AF5fNk876mSpkjaq0mj7ZqlpFUl/U3Si5L2a5nXFpLukHSXpJncfpKOlfTM7L3jQRAEQS8yDXf9ZvsE2+Obbic0a0q6SNKtbW5bz+K09wT+ZPvB1/NaR1TquSQBZwATbe+Ux8YBC9i+XNLPgXNsnz7Ioe62PU7SaOBCYAfg1/l4o4BtgAeB9wJ/zuOrAz8CPmT7dklzAA2L9YfAUbbPyo99ex7fHpjb9tslzQvcJukU4EXgi7avl7QAcJ2kC23fxvQ1y0Oz4bI/8BXgSeALtLj18mv4MbAZ8BBwraSz87GQNB5YeJbe4CAIgqBvqKPOju1NO+2T9A9JS9p+VNKSwONtHvYuYANJewLzA3NJesb2QPE9I86zsxHwsu3jGwO2b7R9+ewczParwDXA0i0atwI/ASY0jX8Z+K7t2/NzX7F9XN63JMnQaBz3lsZdYL5sGM0DvAQ8bftR29fnx/4XmNo0h7ZrlrYft30t8HLLy1gHuMv2PbZfAk7Nx2gYQofnuXek2e142tMPDPTQIAiCICjF2cAu+f4uwFmtD7D9MdvL2R4L7Af8YjBDB0aesbM6cF23DibpDcC6wHlNwxOAU0gepC2blrgG0j4KuETSuZL2kdTwpJwOPAs8CjwAHGH7yZY5jAXWAq7OQ4OuWbawNMkL1eAhphtOnwPObhyvE81ux+0XXG4QuSAIgqAXKLGMNUQOBTaTdCdpteJQSCsUkk4cyoFHmrHTLd4i6UbgCeAB2zcDSJoL+CBwpu2nSQbI5oMdzPbPgLcCpwEbAldJmpvkdXkVWApYHviipBUaz5M0P/A7YO+sNzuo3ZQkLUVaRjt2No8bBEEQBJVh+wnbm9heKf//ZB6fbHu3No//ue3PzcqxR5qxMwVYuwvHudv2OGBFYD1JH87jWwALAbdIug94D9OXsgbUtv2I7ZNtbw28QvIE7QycZ/tl248DVwLjIQUvkwydX9v+fdOh/pHXKhlgzbKZh4Blm7aXAR4heYtWBO7Kr2VeSXcNcqwgCIKgTxhuRQVLMtKMnUuAuSXt3hiQ9E5J75udg+Xlnf2BA/LQBGA322PzeuDywOY5uPhw4EBJK2fdUZL2zfe3aCx3SVoCWBR4mLR0tbES8wHrAbfnQOuTgKm2f9AyrUHXLFu4FlhJ0vLZM7UTaenqj7aXaHotz9le8XW/SVgktkAAACAASURBVEEQBEFPMs3u+m24MqKMHafQ8W1Ia3p3S5oCfJPkyZhdziR5Pd4HvB/4Y5Pes8AVwFZ5qWtv4BRJU0lBzEvmh24O3CrpJuB84Eu2HyNlSc2fH3st8LN8nPWBT5AMoRvz7YP5WJ3WLJeQ9BCwL3CQpIckLWj7FVJszvmkQOdJtqcM4f0IgiAIgp5iRKWeQ1ouIqWKt9v3yVl4/n2kJabGtoE18+aYNo/ftun+OcA5bR6zL8kIaR1/hhQ30zp+Be1jbbD9BLBJm/HHSEtU7Z7zJ+BP7fY1PWb+gfYHQRAE/cVwXnbqNiPKsxMEQRAEQfB6GXGenVklF/b7Zcvwi7bXrWM+QRAEQTCcGM4xNt2mZ42dXNhvXN3zCIIgCILhSCxjBUEQBEEQ9Ag969kJgiAIgqAz/bSMFZ6dIAiCIAh6mvDsBEEQBEEfEjE7QRAEQRAEPUJ4doIgCIKgD+mnmJ0wdoIgCIKgD4llrCAIgiAIgh4hPDvBDIzdfq7KNX999NWVawKMUj22/txzzFmL7sKLrlaL7m6vDqVP7+zxh0XfVLkmwHIH1lPH9Nb9Lq5F98A5V6lc894N9qxcE2D5y4+rRbck9rS6p1AZ4dkJgiAIgqCnCc9OEARBEPQh0/ooZieMnSAIgiDoQ9xH2VixjBUEQRAEQU8Tnp0gCIIg6EP6aRkrPDtBEARBEPQ04dkJgiAIgj6kn2J2wtgJgiAIgj6kn9pFxDJWEARBEAQ9TXh2giAIgqAPid5YQRAEQRAEPUJ4doIgCIKgD+mnAOXw7ARBEARB0NOEZycIgiAI+pAoKhhUgqQlJJ0q6W5Jt0n6k6SVJd3a4fFzSPqXpO+1jG8p6QZJN+Xj/G8eX0XSnyXdKGmqpBOqeF1BEATB8Md212/DlfDs1IQkAWcAE23vlMfGAYsP8LTNgTuAHSQdaNuS5gROANax/ZCkuYGx+fE/BI6yfVY+/tvLvJogCIIgGL6EZ6c+NgJetn18Y8D2jcCDAzxnAnAM8ACwXh5bgGS0PpGP8aLtO/K+JYGHmo5/S9dmHwRBEIxoptldvw1Xwtipj9WB62b1wZLmATYBzgFOIRk+2H4SOBu4X9Ipkj4mqfG5HgVcIulcSftIWrirryAIgiAIRgBh7IwctgQutf0c8DtgG0mjAWzvRjKErgH2A07O4z8D3gqcBmwIXJWXuWZA0h6SJkuafPKN91bxWoIgCIKa6aeYnTB26mMKsPbrePwEYFNJ95E8QouSlsKAtERl+yhgM2C7pvFHbJ9se2vgFZJHaQZsn2B7vO3xnx63/Gy9mCAIgmBkMQ13/TZcCWOnPi4B5pa0e2NA0juBN7c+UNKCwHuA5WyPtT0W+CwwQdL8kjZsevg44P78vC1yADOSliAZSA+XeTlBEARBMDyJbKyayJlU2wBHS9ofeAG4D9gbWEXSQ00PPwa4xPaLTWNnAd8H9gW+LOn/gOeBZ4FP5sdsDhwj6YW8/SXbjxV6SUEQBMEIYjgvO3WbMHZqxPYjwA5tds05C899EnhT3vxgh8fsSzKGgiAIgqBvCWMnCIIgCPqQ4Zwq3m3C2AmCIAiCPsTDOKC420SAchAEQRAEPU14doIgCIKgD+mnZazw7ARBEARB0NOEZycIgiAI+pB+Sj0Pz04QBEEQBLUjaYykCyXdmf9fpMPjlpN0gaSpkm6TNHawY4exEwRBEAR9iAv8GyL7AxfbXgm4OG+34xfA4bbfCqwDPD7YgWMZKwiCIAj6kGG4jLU1qWk1wETgz8BXmh8g6W3AHLYvBLD9zKwcODw7QRAEQRB0BUl7SJrcdNvjdTx9cduPAuT/F2vzmJWBpyT9XtINkg6XNHqwA4dnJwiCIAj6kBKeHdsnACd02i/pImCJNru+OosScwAbAGsBDwC/JfWDPGmwJwVBEARBEBTH9qad9kn6h6QlbT8qaUnax+I8BNxg+578nDOB9RjE2IllrCAIgiDoQ1zgNkTOBnbJ93cBzmrzmGuBRSQ1GmFvDNw22IE1DAOUghGKpD2yCzN0e0gzdHtXM3R7V3MkImlRYBKwHGmJanvbT0oaD3zG9m75cZsBRwICrgP2sP3SgMcOYyfoFpIm2x4fur2lGbq9qxm6vasZzEgsYwVBEARB0NOEsRMEQRAEQU8Txk7QTepak+4n3X56rf2m20+vtd90I16nZiJmJwiCIAiCniY8O0EQBEEQ9DRh7ARBEARB0NOEsRMEQRAEQU8Txk4wZJT4uKSv5+3lJK1TWPMQSQs3bS8i6TsF9RYe/FHVkgtr9TSSPlz3HEoi6ZezMlbRXHr+fKoDSXNKWktSu6aWQUWEsRN0g+OAdwET8vZ/gR8X1vyA7acaG7b/DXywoN6/JF0kaddhZPgM2AumFA2jtsBxt225bQec0NguoZl139iy/XFJP8zdm1VKN7Nai/ZoYO3Cmp0ocj5JerukqyQ9KOkESYs07bumhOYg8/l74eMfL2m1fH8h4CbgF8ANkiYM+OSgGNEINOgG69p+h6QbIBkekuYqrDla0ty2XwSQNA8wd0G9qcDRJIPu+5KuAE4BzrL9fClRSWd32gUsWkp3EHYDvl3guJOA80jN/xpGxnzAVqS2O78voAlwAfAOAEkHkToq/wbYEngrsE+3BSUdABwIzCPp6cYw8BIF05RrOp9+AnwTuIp07lwh6cO27wbmLKQJgKT/Mr1lU+OcmrcxbnvBArIb2P5Mvv8p4O+2PyJpCeBc0vdGUDFh7ATd4OV8RWqA3KBtWmHNXwEXS/pZ1v00MLGg3su2zwHOyYbVVsBOwI8lnW9750K6GwAfB55pGRdQbKmw6Qd4pl3APIVk3wUcSmr0d7xtS9rQ9qcK6TVo9t5sS/qxelbSb4DrSwja/h7wPUnfs31ACY0O1HE+zW/7vHz/CEnXAedJ+gRd6R05ID8HFgK+ZPsfAJLutb18Qc3mHk2bAacB2H6svKMw6EQYO0E3+CFwBrCYpO8CHwUOKilo+/uSbgY2JX1RH2z7/IKSr31LZU/OJGBSdlN/pKDuVcBzti+baULSHQV1nwLe2fiBaNF9sISg7Wtz3MjngUskfYXyP4aQvCtrkZb1R9t+Ns/nZUmvlhS2fYCkpYE30/R9bPsvhSTrOJ8kaSHb/wGwfWleovwdMKaQJlnr85LWBk6RdCbwI8qfU09J2hJ4GFgf2BVA0hyUu1AIBiGKCgZdQdKqwCYko+Bi21MLao0Gzre9aSmNNpr72T6iKr26ycHeZ9ueKaZC0mG2v1JYf2ngKGC87RUKa13aMrSz7UdzB+bzSzZwlHQoyUN4G9AwrGy7ZwKzJe0M3GP7qpbx5YCv2d69gjmMAj4HbA+8xfZSBbVWJl0ALgEcbfvnefz9wOa2v1hKO+hMGDvBkJHU7ursv7ZfLqh5NvCJxtViryNpcWBp0lXpI+08LkF3yUb13LafK6hxB7BGI/asKvr1fJK0JLCW7T/VPZegWmIZK+gG1wPLAv8meXYWBh6V9Diwu+3rCmi+ANwi6ULg2cag7S8U0GpkVRxAWrJ6Ux5+HDgLOLQ5M6zLumuRAjwXIrnFAZaR9BSwp+0iMSVZeyFgC5p+FEmejlKvtZb3uEl/POk8fgW40/btQDFDJ3MPKUi3EmOnzvOpw3xOsL1HYY1Vga1pOo9z3E4R77Ok3YE/274zZ/OdDGwH3AfsYvuGErrBwISxE3SD84AzGjEzkjYn/UhOIqWlr1tA84/5VhWTgEuADW0/BpCzK3YhBSCWqlHyM+B/bV/dPChpvbxvzRKikv4H+AYpU6nxo7gRcIikb9n+RQHZWt5jSe8DjiTFKa0NXAksIullkvewSIxS5jngRkkX02TwlDLaqeF86uD5hXRhVLJcBDnuawJwKtBYkl2GFMNzqu1DC8juRQqMJmuvASwPrEVa3tqggGYwCLGMFQwZSZNb4xoaY5JutD2ukO48wHK2SwbqNrTusL3K693XBd07ba/UYd9dtlcspHsHqaTAUy3jiwBX2165hGZN7/ENpFiKf0paHviB7W1ysPSXbG9eQjdr79Ju3HaRzMI6zqcc5H0/M2a9OW8vbbtYmYpcU2e11iX1XBpjSqf3Yoiar33n5Yy+q20fk7evt/2ObmsGgxOenaAbPJmvoE7N2zsC/84xD0VS0CVtBRwBzAUsL2kc8O2CgZ33S/oyMLEphXVx4JNAySv/cyX9kVSUrKGzLPA/JI9aKUT7rJVpzPij1U3qeo9H2/5nvv8AKTMK2xdKOrqgLrYnVmm0U8/5dA+wie0HWneUyuxrYhqwFMnYamZJypXHmJZjg/5NStr4btO+yMaqiTB2gm6wM2nJ48y8fUUeGw3sUEjzm6S6IH8GsH1jviovxY7A/sBlml72/R/A2ZR7jdj+gqQPMD3mQMBDwI8LB1l+F7he0gVM/1FcjrSUdHAhzVreY2CypJOAi0nv858BJM1LOoeLUbXRXtP5dDSwCMmQbOX7hTQb7E2qx3UnM57HK5Kys0rwdWAy6dw52/YUeG259J5CmsEgxDJWMCSy9+ZQ21+qWPdq2+tKusH2WnnsZttrVDmPXiYvWb2fGX8Uz3dqzdEzSJoT2B14G6m0/8m2X80el8Vst3oFuql9HbAxKaC1cR7fYvvtpTT7jZx2vg4znsfX2i5WQynX1Fmg+W+lYTzb/m8p3aAz4dkJhkT+Uaijl8+tuX7HaEkrAV8A/lrDPJD0Kds/K3Ts0aQS+8sA59r+a9O+g2wXa36av6hPHfSBFVDyPc7xHMe1GX+emZc/us0rtv+jGSvrFrsCrfN86jCfzWxfWFLD9jRSMcVW7fltt1aS7pbmK6RlLHJG1kYkb/dWwOIlNIOBiUagQTe4QdLZkj6hpkaOhTU/T2qi+CKpj9F/SC7rOvhWwWP/H/A+4AngWEk/aNpX+j1ui6RbapAt+R53RNK5hSVmMNolHUtZo324nU+1NLPN3Fby4JLWlXQMyWA+G7gcWLWkZtCZWMYKhoxSf6pWbPvThfTeRAoivat07ZUmzZs77QJWtl2kCWnz0lx2jR8HvJGU0npVY+mjgG6nHz6R+la9qcP+oWjW9R53yo4RcI7tJUvoZu15ga8Cm2e980mtT14opFf5+aSBm49ubHu+bms2ae87gPZXbXe9XYVSy5wdSDFKp5Ba6Ux22X5cwSCEsROMKCTtBhwC3E2qXbGH7U5fpt3U/QcpfqU1XkXAX0uVn5d0u+1VW8a+nueyWInU2azxMvBr2i+pfNT2AgU063qPXwUuo32W2Xq2eyaDpo7zSdK/6dx89Le2iy3rSHoBOJxUKLKVfWwvXEDzn8AdpMDsc2y/IOkeF257EgxMxOwEQ0bSG0jN7lYD3tAYL+TZ2ZtUN+OfklYg/SAXN3aAc0jdm29s3SHpzwV1J0vawtO7RmP725IeIVXCLcXNwBG2b23dIalUT7K63uOppEJ7d7bRLZoarVS1+UBgLDM2Ai0VaF/H+VRXM1tI1d3PdJsq7vnCqQRLkDx1E4CjlXqvzSNpjhzLE9RAeHaCISPpNOB2UgDet4GPAVNt71VAa4aiXFGkqwySNgDu71AbZbztyTVMqwiSPgrc0q7OjaSP2D6zzdO6pX0H8CXgFprqvpTMAOsnJK0CPNlUR6l53+Iu3BMsXwhuSTJ83kNqkrxzSc2gPWHsBEOmkf7diAfIqbzn2964gNbjzJghtFPztsuV2W9kVTRSWBu9oq5x4T8itentQ6rfUayzfF3U9R7XhaQrbL+nYs1azif1afPRBpIWJPUKPLLuufQjYewEQ0bSNbbXkfQXYE/gMdIPVNfXqNWhvH6DgmX2NycFc95JUwNFUnGyPW1fUEi3ubfPQ026OwGlevs0gld3BbYhVaBt/CieBZzUWn6/S5p1vcf7Av+xfVLL+OdJdVGKVVGWtAnp823tjfX7QnqVn0/q0HyU1Iusima2tTWXbTOfB2wvV6VmkAhjJxgyee37d6SGdz8D5ge+bvv4WifWRSRNBT5g+76W8eWBP9l+ayHdynv75OOfQvoxmsiMP4q7AGNs71hAs673+FbgHbZfahmfm1R8rlihSkm/IqUjT2H6MlbJTMZaekXRufno/9ku0sw2a5xPai470TM3l93UdqkGvp3m86DtZavUDBIRoBwMGdsn5ruXAUUzDiT9gQGKrrlcb6w5mP6j38zDwJyFNKGe3j6QfvxbG28+BFyVfzBLUNd77FZDJw++qJZqfwVY09VWS67jfJqv1dABsH2VpGJp55mxtg9r0X0MOExSEYNyEMK7UBNh7ARDJl8Bb8fMGSXfLiB3RIFjzgonA9dKOpUZe+zsSNnCaHX09oHUyHV74He5Am2j7P72zJwa3i3avcfLkpZYihafaxesmmNMSnOVpLfZLlrgrok6zqe6mtlCDc1lc9HNdkaNiOrJtRHLWMGQkXQeqYLxdcBr/WZKB+Jl1/vKefOOEnEkLXpvAz7MjD12zi79Q6V6evuMBQ4j9W36d9ZdmLQksL/tewvpvpWZm1QWfY8l/Q+p3cgXSanKAGuTmlT+uFQcWNaeCrwFuJcUsyOSp6nk0lkd51O75qNnu2wz20Z/t/2zdmtz2cNsP1lAcyWSUdNqTL2ZFJh9V7c1g8EJYycYMpJutb16xZobkuJJ7iN9eS4L7GL7LxXO4Y22/1WBznLA07afykbIeFJq/5TS2ll/UdJ3RfHXWhf5x3h/YHXSVfkUUgBr0XYRkt7cbrxk6nnd51OvI+kc4EDbN7eMjwe+YXurembW30RvrKAb/FVS1V2ajwQ2t/0+2+8lVYA9qpSYpA9IulfSFZLWkjQFuFrSQzmjppTu/qRYqKtyIPh5wAeASepcCr9b2utIeqftJ4DFJO2bjYJSels03V9I0omSbpb0m9JLSrbPzefSorbfmO+X7ovVMGoWJjWI3ApYuLChU9v51GE+J1SgsaqkTVrjg5rPty4zttXQAci1qcYW0gwGITw7wWzTtDY9B7AScA/VueJvbj1+u7Eu6t1IStldmFTp90M5wPKtwK9LFTbMRtV4YF6SF2sFp+rR8wFXl/KoSfoG6UdwDuBCYF3gz8CmpBpK3y2g+VqBSEknkkoY/JTUoPJ9tj/Sbc2sdYHtzfP9A2x/r4ROB+29gN2BRqr5NsAJto8tpFf5+SSpU/8pATfZXqbbmk3aXwA+S6qSPQ7Yy/ZZeV+RgqSS7rK94uvdF5QlApSDobBljdqTJZ0E/DJvf4wUM1SKaY2ia5Kes30VgO2pOQaiFK/afl7SS8DzpG7V2H62cKLQR0k/DnOTjI5lbD8t6XDgaqDrxk4L422Py/eP0iD1lYZIc1PT7YHKjB1SLaN1bT8LIOkw4G9AEWOHes6nf5Kyv5oFnLcXa/uM7rE7sLbtZ/KS3emSxto+pmU+3eRaSbvb/mnzoKRdKfsdFQxAGDvBUFgMeGOru1/SVqQCdCVL3v8/0hXbF0hfWn8hFaQrxVOS/hdYkJSptA8wieTpaG1w2E2ul/QbYD5S4bmJOSB8Y6BkYPQrOWD1OUl3234aIP9QlkpRXiwvpQhYUJI83fVc0qCs070tmoL68/2SVmwd59M9wCZu33qkaO8xUlHIZwBs35dj/U7PsVKl3ue9gTMkNV+AjQfmInnughoIYycYCoeTUjhbmQqcQPoCLYLtF4Ef5FsV7AIcRPphbDT5O59k0O1eUHc3krfBwOmkLJqdSV2Vf1xQ9yVJ89p+jpSZBLxWkbaUsfNToNFNfSLwRuCfSkXgZmoO2kVWkHQ26cevcf81CtZuglSE82pJZ+Ttj1A2zb6O8+loYBFgJmOHlPFWksckjXNuLps9PFuSyhwUiTPMKe7vlrQRKeAd4I+2LymhF8waEbMTzDaSbulUEE3STSUqo0qaKfCvmZJxQv2EpLmzQdk6/kZgSdu31DCtIkh630D73aZbd5f130FqEingL7ZvKKnXT0hahuSlfKzNvvVtX1nDtIIaCM9OMBTmGWBfqcqo00hXpb8B/kCKO6iEfKW2HSnN/RVSD6ef2r67oOb1pODVU0rqtNJUPbhdU84iKeg5kPVzWeck4EDgXSRP4SG2SxUzvKGxTNdmTkX6GLUE7d6Xb6/tK1H/JR+7lvNJNTUftf2QpOUkLdySan97GDr9RaSeB0PhIknfVUtko6RvkYrPdZ0ctDqB1H/rN6RA2dWAhwun7B5Kqvh6FfAyKQ7hbtL6//aldEnu/4WBSyVdI2kfSUsV1ANoNOW8E/gm8EHgQ8C3gDvzvhL8imQkrw1cCixBKmz4PPDzQpqQsswAkHRxy74zC2n+i7Q0Nznfrmu6TS6kCTWcT0rNR08lea6uAa7N90/JqfAltTul2v+2jlT7oD5iGSuYbXK66omkq/9GTMWapC/r3RqBgYXnsCMp1uAw24cX1HltyU6pI/hlttdXqtB6ecEU8OZ07A1Iht62JG/HKbaL1ClRDU05Jd1oe1w2nh+yvXTrvm5r5mPfYHut1vvttruoeQywIXAlcApwhSv4Mq7jfFJNzWyzRi2lG4LhR3h2gtnG9rO2JwCbka68f04q9LdTs6EjabVu6kpaWtIXJV0BfBzYB/hJNzXaMK1p6WEpYDRAXlop3SySrHW57T1JSwGHkZZ4SlFHU85R2XhcFpg/Lzk0KjjPVUgTZszGajU4ihggtvcipfafBnwCuEHS97MxWQkVnk+N5qOtlG5mCznVHniKllT7wrrBMCNidoIhY/se0rJOJ34JdKV4l6TLSBk7k0iZYI3YhrlKxjoAh5B+kO4AViWlviPpTcBNhTQBZuownlPCz6NsE8U6mnJ+D7g93/80cKIkA28jLaGVojnlvXGfvP2mzk8bGtmTc6mkG0jv68HkOLBSmtRzPtXVzBY6p9pvQtnSDcEwI5axguJ0cylA0n1Mv9puPnkbVZtX6IZOB+0xwArAXbafKqUzXFA9TTlHk76XXsnLheNI8ViPFtT8xkD7bXfd0MrLKFsDO5IMqt8Dv7Vduu5MLaiG5qNZdw5mTLVfl7R09wCpyWt4ePqEMHaC4qhQWfbhgKRVgP1sF6m1M1gQpe2q6gy9RqmU3ZyC3RHb1w+0vzTqYisJSc+SvDinAHfRslxm+/ftntcF3crPJ0nzAi83Ynby38wHgftsnzHgk7s/lzlJtW8etv14ldpBvcQyVjAikbQNcInt/+TthYENbRfJnpG0BnAEKfbgTFI5/+NIV4pHltDMHEEK/j6X6X3HipM9LDuQrsTPs31rLsZ2IKnkQNeDdkmB7VNI7QVg5vYCxYpUziLdbCVxGuk1rZpvzZjpvbK6TR3n03mkthh3SlqR1A7j18CWktaxfUApYUnHA8fanpILYv6NVKV6jKT9bJ9SSjsYXoRnJyiCpKVsP5LvX2V7vS4ff6bsnFKZM/nYV5OCoP8GbAF8mZT6/jXbL5TQzLrjSPEcW5DSkk8BLi6duSPp56QYnWtIBt39pADW/QsalPuQ6hj9h5SqfEYVGX2zSsnzqyrqOJ9aMhkPBsbY/mzOxrquU2HSLmlPsb1avr836YLoI0pVuc8d6Z9nMOuEsRMUQdIDtosUZMvHb9f1vGNF5y7ozWBcKfX0GVs65qBlDu8mxRtsCnzF9tmDPGUoWrcCa9ieJukNpLowK7arRFtAe3nS69yaZGQd0ij3XyfdXI6V9HHbv+q0rFTF8mRV51Pz36qkK4HDGwazClVab9JuLivwR+A02z9v3Rf0PrGMFZSitHt8sqQfkGrsGPg8ZTsKv0HSWkx/Xc8Aa+SaMMXjSXLW11qkfj4PAaXjDV6yPQ3A9guS/l6FoZP17pV0Fmm57BPAypTtjTWrdPOcblQYX2DARxWi4vPpZklHkMoWrAhckOewcEHNBk/l5deHgfVJy2mNwOWBKsAHPUZ4doIiVODZmQ/4GumqVKQv0O+Uyq6QdOkAu227SDyJpE+RMnbeQMommVRFYKWk50iBs5De37fk7UbWW9d7kElagbTEsjUpRflU4JySy4RZ93O2fzQLjzvQ9iEl51KaOs4nSfMAe5Hq6pxs+6Y8/m7gLbZ/WVB7ZeCHpGrcRzd5dd5Pqgn2xVLawfAijJ1gtpF0LO2LrgnYxfaCFU+p55A0DbiF6R2jW7N2inTklvTmgfa7QGuO/FpvBs4Cnmbm11pkaafObMHsYdkdGEuTp932pwvpVX4+SdrM9oUd9h1m+yvd1gyCVmIZKxgKA/XwKdLfR9LRtveW9AfaGFqlfvwHmM9mwJdtb1ZIYqNCxx2QhjGT42dWI73XU3MByVJ8m+mf6fwFdYYTZwGXAxeRsoRKU8f59GNJ+9j+Y2Mg1905meRxKYak7wP32D6+ZXwfYIkwtPqH8OwERZB0hO39Chx3bdvXSXpfu/22L+u2ZtbdGDie6annhwC/IHmxvluwLsqXgSOrDITOuguS+p6NJ8XLiNT37DpgV3foEj4SkfQK8Fy7XaQlu2IeynZZhSWp43xSavtxHnCg7d/ngPfTSd67XdzSM6vL2rcBqzfiz5rGRwE3O3pj9Q3RGysoxQ4lDmr7uvz/Ze1uJTQzRwJ7AIuSvqivAn5pe+1Shk7mzcB1ktYvqNGOH5LK6a9oe1vb25Didm4BBo1vmR0kvUHSLpI+rMSXJZ0j6RhJbyyhmbnF9oJtbgtUsBR7jqQPFtZopvLzyamZ7KbAwZI+Q2rb8HfbO5c0dKbLe6b+W3mskppVwfAgPDtBESQ9aHvZAse9hQGaM5YInM26M8R1SLrb9ltKaLXRfgepiOHtpFo/r315l8oCk3SnO3SjHmjfEDUnAS+TMpUWAW4F/gC8Bxhne8tua2bdylOQJf2XdB6L9HpfIr12KO9NqvR80vTK2EuSvKEXAt8vqdmkfS2ws+07W8ZXInV5H19KOxheRMxOMNtoehfwmXZR7qqp8YP32fx/I5PjY7RfiugWC0vatmlbzdslvTu2r5f0EFP/FAAAETdJREFUVeB3JO9Kc2+wUlWF67jqfZvt1XNa8EO2G0uV50kq2Wz1tILHbovtWlLOs3bV51NzhfGbgcWbxkpXxv46cK6k7zC9NMV44ABSg9KgTwjPTjDbSLqX6Venrdhlm3JeaXv9wca6qPezAXa7YPbMYqQfhhWAPRtpu6WRNBG4GzjYTV8Skr4GrGz7EwU0X/OetfGkFcuYUmoE2umL0LYPLqHbpL8tyXtl4HIXqlCdtWo5n+pE0urAl0g9sSC1JDnc9i31zSqomjB2ghGJpBuBz9m+Im+/GziuymDPKpB0D3Ao8FNX+MeaA5RPAt5BClA2qQjdDcBuLtD1XdLjpNo6ItWCObWxC9jB9uLd1sy67WqtzAvsBixqu1hmmKTjSIX2Gj2adgTutv3Zzs8akl7l51OLRxTSufQv4Ebb/61iDq3kIOmtbFfu1QvqIYydYLbRzF2qDfzL9oMVaK9NSl1dKA89BXy6YAxLa1n/xhf2FbbvLaGZdd9k+59txpcFdrJ9eCntrPMW4G0kg2OK7bsLau0y0H7bE0tpN81hAVIBvF2BSaTMpWJF9yRNIWULOW+PIgVMr1ZIr/LzqYNXdAywBimz75Jua3aYx2hgc1KLjPeTvGgfrUI7qJ+I2QmGQrtu32OUGvxNcMF+Rjkra83sgZBz9/OCtIuxGAt8VdI3bZ/aZv+Qaf5hyhlJ25O+rJcGziihmbU+bvtXtu+WtITtK5v2zVLF4ddLszEjaf40VKYidis5/mxfUuzXROAdtv9dgfQdwHKkHmCQmq/eXEqsjvPJ9qfajefClZNIjWaLIem9wM7Ah0iNbdcHlrddMsYvGGaEZyfoOpLGAz+w/d4Cx669gWLLfMYAFxWMJ1kA2Ib0Zb0y6QdpR9vLlNBr0q0rfub/kYJHG72jngEOs31cCb2seTiwLXAC8GNX2Gld0mXAO0k/wuT7fyMH27vLRTLrOp8GmE/R6tWSHiJVi/4JcKbt/0q61/bypTSD4Ul4doKuY3tyvjIvQa0NFFux/aSkkplLj5N+CA8iLZlZ0jYF9Rqow/12290RlA4C3g1s6FypWalf1jGSxtj+Tgld4IvAi6T3+KtNH2fxooKkbKEqqet8mglJq5De95L8DvgIKRbqVaUGs3GF34eEZyfoOpIWB/5ke+2651KaXFn5IJdrBLoPqTnmfMBvgN8CF5bMdMu6lXt2JN0BrOmWxp9KjSRvsr1ytzWHC3k5trk31pOFdCo/n9S+tcsYUt2dj9v+WyntrC9Sm4wJwAeBBUkxWX+q0osX1EsYO8Fso/aNQMeQrs73sv2HgtoTs8ZTeXsRUjBpqRTwdsUMxwCPkEreTy2h26S/AunLeidgJeAbwBm2/15Ir9H1vLnjOXl7BdvzdXruEDTvsL1Kh323216125p1I2kP4GDgeVJxv4Y3qbQxW9n5pJlbuxh4ArjT9kvd1htkLnMCW5Be++a2S1bmDoYRYewEs02b7JnGl9i1JTNYsvZMVW9LVsLVzF3ADTxRVQBty1zeToq52MGFqji3eb0z4DJdzy8GDrF9ccv4xsDXbNfSFLUkku4E3mX7XzXOoej5JGk921d1+7hDRdJ7bf+l7nkE1RDGTjDbSFrO9gM1ad9Eiu34d94eA1xm++0VzmE+UjzAzrY/VFhrYdIVOKS+QqWzzypH0mqkLuBXkKrdmhSwuz6wte0pNU6vCJLOA7atOjOoyvOpZUn0b7bfVUqrjfZoUp++pYHzbN8qaUvgQGCeUhdHwfAjApSDoXAmqegckn5ne7sKtY8E/irpdNKP4g6kTuRFyWn1HyRdCW9BCoA8vrDeCSSj6l7SMsebJZ0BfKbUMoCkXYExjborkh4mBYUL+LLtn3Rb0/aUXO12Z2C1rPUX4H9b43h6iANI5/HVNAXr2v5CCbGazqfmgPY3FDj+QJxESue/BvihpPuBdwH7u2Cl6mD4EcZOMBSav8SKxhi0YvsXkiaT+uqIdHV8Wyk9SZsxvRjZpaSeXOt0qiHSRQ4C5gSWbVSbzenDPwa+lm8l+AzJmGvwuO2lc+XZC0ipvF3H9guSLiVlDRmY2sOGDsD/AZeQusnP1J27AHWcT6NyTN2opvuvfXeUCsbOjAfWsD0tn7v/Ala0/VhBzWAYEstYwWwzUMZOxfOYj1Q7ZEKp5SRJ04DLgU86V0yWdE8FgaS3koyq51rG5weusr16+2cOWfe65mw6SQfaPiTfv9b2OwtoLgicCKxNalExCliTtKS1q+2nu61ZN5L+avvdFepVfj5Juo/pwdetFA3GrrJGVDC8Cc9OMBTWlPQ06UtsnnwfKqhPUvVyEukHeCfgIqX+QqcCowvqNZjWLp7D9jOSSl6pLNS80WTojAIWLaT5Q+A2UtuCaVlPJG/Dj4D/KaRbJ5fmjKw/MOMyVilvR+Xnk+2xs/I4SasViMtaVVKjIrWAt+TtxnfUGl3WC4Yp4dkJRhRtlpN+Cxw7q1+oXZrD+nkO25E8EGfYPqGQ1k3AhrS/Kr7U9pqFdI8DnrR9UMv4d4A32v5MAc07ba/0eveNZCS166tWzNtR1/k0K5TwutSRVRgMT8LYCUYUdS0ndZjLKGAzkifiU3msq1endS0B5KXBE0nZUDfl4TWByaSu510vxibpLtsrdtjXk8ZOOyTNVTDw/D5qWlIajJKlI2ZBu9IssaB6YhkrGGnUtZw0E3mp5fx8a/BLcoZalzTGzsrjum1k5fpBE3LxuUYH7tvc0vW8y7pXSvo6cLCbrsIkfQ0YdnVauklTld+dga2AxUvo1LykNBh1XnlXnSUWVEx4doIRS5XLSa9jTrVcndYVeNlN3RygfBLJWLyR9OO3FnADKUC5F2sLrUsycLYhVeT+LHC2q+m4PtC8Kj+fak5yiMDlHmdU3RMIgtnF9pW2P0cqGHY0qX4G8FqBulqmVZNuyWaklejaftr29sDmwM+BX5BK+n+02dCp8bPtGpK+m6snH0JKO18L+KftiXUbOpk6zqdKW0cE/UUsYwUjniqWk0YAdRlZXdfNS2V3D/CQXvhs9wDuINUrOifXFxpObvauzSUHCT/VMFglbUQqang/8KNGfJLt9bqlORvUdbEQVER4doJepbIvL0lLNW3G1Wl5euGHaQngu8CHgbsk/ZJUvqEXL0AnkbqsI2kccBrwACng/biSwpIumMWHfqLkPIL66cU/rCCAaj0dVwHLQbVXp5KWsv1I3qzMyKpLt4nh5AGZLWy/CpwLnJsr+24JzAs8LOli2zvXOsHufq7zNJ0vHwdOtn1kzma8sYs67XjTrDzI9q2F5xHUTBg7QTB06vI01GJk1ajbk+R2GKcDp+fWDduW0qppSan572NjUj8wcguH0n87C0nq+H7a/n1h/WCYEMZO0DPU6HGIoOTSgvV7k4ogaW5SNuFYqvk+nkTK/PpP05LS95i+pLRbAc1LJE0CHgUWIfUCQ9KSQOm+ZwuRvGZt6woBYez0CWHsBL1EMY+DpGNpb9QIWLibWq+DnglKngV61Zt0FvAfUv+vFwd5bDeoY0lpb2BHYEngPbZfzuMrkdLtS3K/7U8X1ghGAGHsBL1ESY/D5NncNyTqMrKGoXHXC0HJ7VjG9haDP6xrVL6klAtEngopQFnSXsAOwL2kkhElWUXS+ravbB6UtAHwSGuRzKB3CWMn6CWKeRxsT+y0T9IRpXSpyciqUbcTIz4ouQN/lfR227dUpFf5kpKklUlVzycAT5D62cn2RiX0Wrga+G+b8edJhtZWFcwhGAaEsROMKIahxwHSVep+JQ5cl5FVh+4w/WxL8x7gk7kh6IuU78Zdx5LS7aR+dlvZvgtA0j6FtFpZzPbNrYO2J0saW9EcgmFAGDvBSGO4eRygviWWYkZWTbrD8bMtzQeqFKtpSWk7kmfnUknnZf2q/mYG6nk1T0VzCIYBYewEI4q6PB2SOl31ij7KiiqpW+NSYW3Yvh9A0mJU0IyyjiUl22cAZ0iaj5Tmvg+wuKSfkPrZzWrhv9nhWkm72/5p86CkXUlB4UGfEI1Ag55B0gO2lyt07HtJSyxtU1htr1BIdyAj6ybby/SS7gDzKfbZ1omkDwNHAksBjwNvBqbaLtL/S9I00pLSrk1LSveUOn8HmMcYYHtgR9sbF9RZHDiDVK6gYdyMB+YCtrH9WCntYHgRxk7QM0h60Paydc+jm9RoZNWiO8B8eu6zBZB0Eykr6iLba+UifxNs71FIbxuSZ+fdQGNJ6UTby5fQGy7k93X1vDnF9iV1zieonjB2ghFFjZ6O1saTBv5l+8ESev3IcPMmVYGkybbHZ6NnrZwCfo3tdQrrNpaUJpCMrYmUX1IKgtoIYycYUdTo6bi0zfAYkjt8gu0iBdnqMrLq0B1u3qQqkHQRyeg4FFiUtJT1TtvvrnAOlSwpBUGdhLETBENA0njgB7bfW+j4dRlZtej2G9nD8jwwCvgYqb3Br20/UevEgqDHCGMnGFEMx+UkSdfbbp1Xac2iRlYdusPxs62C3JxzJdsXSZoXGG27XSG8IAhmk0g9D0YaR7YZGyOpFo9Dzvao/IohF0Wbv8d0h9VnWwWSdgf2IHnN3gIsDRwPbFLnvIKg1whjJxhRdKoHkj0OPwRKLSe1q+47hpTVslcJzUHmU4uRVVK3rs+2Zj4LrENqa4DtO3PNnSAIukgYO0FPUIGno7WCr0lF2fa1/Xgp0bqMrOFk3NXlxaqIF22/1OjBKWkOercPWBDURhg7QU9QgafjUtsPFDx+J2oxsmrUnYm6vFgVcZmkA4F5JG0G7An8oeY5BUHPEQHKwYhiMI+D7SI/FM1ByJJ+Z3u7EjptdJerw8iqQ7euz7ZOJI0CdgU2J6Xcn08q8hdfzEHQRcLYCUYUknZpGWp4HK4tvJx0g+21Wu+XpkYjq3Lduj7bIAh6n1jGCkYadS0nucP90jQX2KuyqF4dunV9tpUj6eaB9tteo6q5BEE/EMZOMNI4E6jc0wGsKelpkhEwT75P3rbtBQvp1mVk1aFb12dbB9NI7+tvSDE6z9c7nSDobcLYCUYatXg6bI+uSquFuoysOnTr8mJVju1xklYl9ab6DXBb/v8C26/UOrkg6EHC2AlGGnV5OmqhLiOrJt1++2xvB74BfEPSjsAvgMOAw2udWBD0IBGgHIwoJL0KPEv2OADPNXZR1tMRFKbfPltJSwM7AdsA/wYmkTqPP1PrxIKgBwljJwiCoGIkXQYsQDJwTgeebN5v+8l2zwuCYPYIYycIgqBiJN3H9KW65i/hhherp2OWgqBqwtgJgiAYpkhazfaUuucRBCOdUXVPIAiCIOjIL+ueQBD0AmHsBEEQDF80+EOCIBiMMHaCIAiGLxFnEARdIIydIAiCIAh6mjB2giAIhi8v1T2BIOgFIhsrCIKgYiS9GXjK9n/y9kbAR4D7gR/ZDiMnCLpIeHaCIAiqZxIwH4CkccBpwAPAmsBxNc4rCHqS6I0VBEFQPfPYfiTf/zhwsu0jJY0CbqxxXkHQk4RnJwiCoHqaU8o3Bi4GsD2NSDcPgq4Tnp0gCILquUTSJOBRYBHgEgBJSwIv1DmxIOhFwtgJgiConr2BHYElgffYfjmPrwSMqW1WQdCjRDZWEARBjeQA5Z2BHYB7gd/bPrbeWQVBbxGenSAIgoqRtDKwEzABeAL4Lenic6NaJxYEPUp4doIgCCpG0jTgcmBX23flsXtsr1DvzIKgN4lsrCAIgurZDngMuFTSTyVtQmRhBUExwrMTBEFQE5LmI1VOnkBKQZ8InGH7glonFgQ9Rhg7QRAEwwBJY4DtgR1tb1z3fIKglwhjJwiCIAiCniZidoIgCIIg6GnC2AmCIAiCoKcJYycIgiAIgp4mjJ0gCIIgCHqaMHaCIAiCIOhp/j8CrAVuH10W/gAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#plot a heat map to show the correlation of the data\n", + "plt.figure(figsize=(8,8))\n", + "sns.heatmap(data.corr(method='pearson'))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "FULL_Charge 0.534602\n", + "FULL_AcidicMolPerc -0.598816\n", + "FULL_AURR980107 -0.584111\n", + "FULL_DAYM780201 -0.554838\n", + "FULL_GEOR030101 -0.260470\n", + "FULL_OOBM850104 -0.453287\n", + "NT_EFC195 0.260702\n", + "AS_MeanAmphiMoment 0.693552\n", + "AS_DAYM780201 -0.437168\n", + "AS_FUKS010112 0.033432\n", + "CT_RACS820104 0.267652\n", + "CLASS 1.000000\n", + "Name: CLASS, dtype: float64" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#also checked the corelation in regards to the class since am trying to build a ML agorithm for that class\n", + "data.corr(method='pearson')['CLASS']" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + " data.skew().plot(kind='bar')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## understanding data with visualization" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Histogram\n", + "### I want to understand each attribute of my dataset independently" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Data pre-processing" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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Hj2vXTSGamppIy1QL6kGGStBZpVLVFk5HqGQroL1WVpZiWma5qIT8HY0XEZkFrABWA6tUdayIDAX+BDQCs4AjVHWJiAjwa+BA4G1gkqo+Wk75g/KjqnP9d4GI3AzsBLyZNPp8eGuBO58DbJLyvjEwt6oCB3VNZ5VKVVs4HaGSrYD2vgWR5eTRq0pqmXW2NZaLEuMlhji7KSIyEOilqiv8/37AGcBtwERgqv8m41G3ASeIyHVY2i7rqaMNQW46pVSihdNjiSHO7sNw4GbrZNIHuEZV7xKRR4DrReRYYDZwuLu/A+uJvoT1Rr9afZGrR5ya0HFKVirduYUT4+2tKPsQZ1A/qOorwPY5zBcBe+cwV+DbVRAt6KJ0pqcSLZyeQdmHODszb1auubJS5rgSip0jq+TKnu66cqhYYqFL/VKyUokWTs+gEkOcnZk3K9dcWUfnxdIUO0dWiTmxhO66cijo+sQpxUFeuvMQZ9D9KdSbOXn0qjWTgkF5CaUSFCKGOIMg6BChVIK8xBBnEAQdJQ6UDIIgCMpG9FSCoELECqWgJxJKJQiCoESi4dCWUCpBEPRIYpNzZYg5lSAIgqBsRE+ljolzh4Ig6GqEUgm6HTGsEQS1I4a/giAIgrIRSiUIgiAoGz1u+CuGRoIgCCpH9FSCIAiCshFKJQiCICgboVSCIAiCshFKJQiCICgbPW6iPgjqidjgGnQ3Qql0YXrqYXaxgi8I6peqKxURGQ/8GugNXKKqU6stQ1BZIo27N5G+HSNfI+jk0auYNPmv3a7hV1WlIiK9gQuBfYE5wCMicpuqPlPsM4ptpSYJFlSXcqRxUL9E+paf7jYEWu2eyk7AS/6ZWkTkOuBgoK4y5Mpnmlj+yC18sGgOvfoNoO8GW7Dup47g3VmPsWrJPBo+d0pev/OvmcwHC15l4xOuQvr0XWO+avlCltx3Me++/hS6ehV91lmfdXY6lEGj9wFgxeP3sPzfN7G6eRHSZy3W2vAjNHz+B/Raa+1OvUs2w2aVbQUybKfSuL0CdvLoVfSkUdv2WrlQ9UqnS5Th7kRXG+YW+6x4lQIT+SIwXlWP8/tjgJ1V9YSUm+OB4/12G+D5EoNrABaW4G84sCHwGrAcUGAdYDDwIbAW8Goev/2A0cBq978kJctQ4B3gDX/OAKCvhzEI2BJ4wd30BtZz/x+W8A6FaC9eNlPV9Ut9eAlpPAp7x/5YvL0DCDAwce6/SUZ9j/wVWBL/SZytAt4C5udwuw2WBo+nnp2wNrARli5JmAuARX6/pbvp4zI3A6+4XW9gMyy/gKXvay5TH2ATt+sFvAu8DqxMhT0UGOlulwOzPAyA9bH0GwC8DTyXkXswsKnHw0r3+37GTW9ge+Cfqrp7NlLaI0f6vgUM8XdJOB7rzbzs90k53oaWOOxH/rI02mVf0UHxkvR/C5idw3xmyqwBS9/3gbnAMKCRlrzzHlZWl2WeUShv9cfif223nwMsTdkPwfJVPw93RUbODYARWJ5fiuWbJG9uhNUJA4B5LnOabL5ZraoNACLSnHE7APitqp5IJVDVql3A4dgYbHJ/DHBBhcKaUYKfdbEK4vA89lOAqwr4/ynwIPBL4Pa0LP7cMXn8nQLcUqU06HC8VCqNgZOwyvoLmBLpC3wO+J98cV5IfqxSUKCP34/FKtd9c7hbDSzOpjWwq6fVqVjFI8COwPVuPxFTfFv6/YbA8Sn/vwXuwRoi6wL3Ar90uy38nUdglfvxmIIf5PajsIpmD6zCuwa4LvXsLwCHAL8DFmbkbsAqwMOxyu1/gIdyxNEfgAeAf5Qpfd8Cbs64GQfMyeG3CTjOy0PesoQplH1KkO10TGktBtbKly+SfARMA87y+0lJnGAK/xueD9YrJm9hlfkLnr69gc+4/dZuPxJTJAd4njrI8+AGbr8/8KbngSEeV1NT8k50v7cCUzLvXTDfZNwO9Pfao1J1QLX3qczBWmoJG9NW49aSXbECeXOJ/icAV/u1v4gMT9k9BFwoIkeKyKYZfw+7+5+JyG4islaJ4dcDRaWxiKwLnAF8W1VvUtWVqvqBqv5FVb9fDkFUdQbwNDAmYzUBS49pWGFN8z/A5ap6rqouVGOmqh7h9p8Elqvqyx7GfFW9OOV/c6yBsFxVl2F5aZS7fUVVf6mq81R1tfvrh7XgAY4G/qKqD6hqM3Aa8AURGez+b1LVW2hp7af5AvC0qv5ZVd/FKu3tReSjiQMR2RXYDvhju5GXn2z69skjTy2YAPwE+ABrnJSEqn4IXIlVwFvlcZPNWx/FehP/62n7f1gD8xi33xhYqqp3ep76K9br2dLtJwKXqurTqroEOBNTdEl4l6vqneTuvRXMNxm+iDXk/l5EVJREtZXKI8BWIrK5iPQDjgRuq7IMhRiGtQBXddSjiOyODXtcr6ozsa7/l1NODscS8jTgVRF5TEQ+CaCqf8cqhR2AvwKLROSXPina1Sg2jTurwNtFRHbBKtGXMlY5lb+IrO1y3VDgsQ8Bw0Tk+yIyNkcaXQh8VkSGiMgQ4DDgzjzyjcGUSiLfKGw4DgBXXO8DW7f3rjn8rsTy4CgPK5lgP4G2w30dIZu+A4F/deJ5ZUFEPo1V3NcB12NpXOqzegNfxZTTa3ncZPOW5HLmbsB6Rs+KyOdFpLeIHIKlwxNu3yr9/P9wERlWhMgdyTcTgSvUuy2VoKpKxSvrE4C7gWexCvjpCgV3cftO2rAIaBCRUmaCJwL3qGoyX3ENLa3gi1V1iapOVtVR2LzNY8AtIiIA3oL5HDY2ejDWSjmuBDnao5R4KZoOpHGpCrwY+ReKyDtYZfdb4JbEoh3lPwQrE/PyPVhVr8J6OPsDfwMWiMjklJNHMUWxyK/VLkMrRGQdrDX8M+/RgA1dLMs4XUbL/EyaFzL37fn9DvCwv3PJ5EjflcCvRWSpX7cUfIBRiTw4EbjTW/nXAAeIyAYdlGEXEVmKzQ/9AviKqi7IuMmXt57DegDfF5G+IrIfsCc2v4KqrgaucNne89+LXPlD2/RL/udK+yxF5RsfIdkTuLyIZ5ZM1Y9pUdU7VHVrVd1SVc+uYDilZNx/YRnqkI54EpEBwBHAniIyX0TmA9/Dhh+2z8riiucXWHd5aMbuQ1W9D/g/Wlo5ZaPEeOloGMWkcUkKvEj5k0nYU7Dx/b4pu0LKP1kYMaIdGY5T1X2widNvAmeIyP5u/Weswh+Mzau8DFyV9u/55S/YnMf/S1k1u58065B7yCOrVPL6FZGNMKXy40LvVSzp9MUqr0NUdT2/DsEmqfvm8NoX+KDcedDj83Cs54mq/gubAE8aC0nDZY1MLkNfrDeS8JCqroc1Lm4DPp0juJx5S1U/wOqNg7DJ+5OxHtMcl3Ef4Ofupx9WuX/Re6vQNv2S/8UsVig230zA5o3yLTQqC3H2VwpvMf4Um/s4RETW9lbHASLyc3fWS0T6p661sMy0GtgWG2MdA3wMG+6aACAi54rIdiLSx8c6/wtbmrlIRA72uZYhYuyEZbqHqhoB1aUkBV4sPq59nofxLShK+b/tch1WZBgfqOqfsSGMpAGwPd4C9fHt3wMHJn48v9yCrSz6RuaRT7v/xO0W2AqprALJRdbvQGy8/mlsGfAI4Bl/518DO3kcVGKIdTbWYEhWz+E98s3IM5zUSQ7FKtHfptJ1JC1DYPMw5dGY8bd5Lnk83b4FHCMin8hh3yZvufkTqrqnqg5T1f2xhRn/dusxwAOqOsMbjo9gc6n7uH2r9PP/b6pqMfNVxeabCVS4lwJUd/VXV7mwia8ZWNd+PjbP8Sls8lMz1xzgLuC8HM85wv33AS4AXsRaFW8BtwMfc3d7APdhK4FWYJnhB7WOhyrE80nYipdDsGGCvtgKl5+n3EyhwIq7zPMaabvK57PYQoH+wFHYyqBNsVVbyfVAkn6ezs3A94FhbrY9vpoGG5Y8iJZlwQdgq8F2d/v7Pa0H+PVb4EG364v1UG5Jy5iSdRS2HPTT2FzFVbRe/dXH3+P/YUNn/WlZjbQ+1ms4zM3PxVd/YRVM+n3/G6vQNixDGs4ix0ot4J/YHM4gD/8H7rZ/Kl2vcVmTa63UMw/I2LWJr1RYdwOXZt5xR6zXOdrdXAvchA279vW8sBQYnkrXf2Se+wt8ZVt7ecvvP+6yro31ZF5NvdOeWPke4/efwHrr+/n9eKyu2BbrKf0frVd/9fVnXwOc5f97F5NvUvl6JTC44uW61hVLWV7CMuGT2DzFDDcbCkzHKvLpwJAqyLGNy5Bcy4HvegF6I2V+YIXCvwwb130qZZYzHrBJxPOxicYngB1qlHY5FXjKfgquVLClmv8htVw786xcBV+wltyJFKH8/X4nbHJ9GaaEHgYmuN1XvHJY7dfLwKTUszbHFEeytPUuYCu329PlextTXMn16ZT/L2Mt/ZXY8tGhmbjINmqepKVS2wcb238HW5LamCeeJlHikuI8ZS+XUtkEGwqc7/F1N1Zhjsf2rCzO8S5zUs/M2p2VJ/yR2PDW6Bx2d2CKYRNs1GAJ1mN5G1uZNZ6WsvEU8K+M/42x+Y+Pt5e3/P5/PIxmzz8fyTzvRH/eKmxf09met14E/oQ1ZN7E6o0/0npZ9LQccZLOd3nzjdtfBFxZlTJdzQqkYi9hmbAhY/ZzYLL/nwycW2WZenuB2swrg1OqEOYe2AqytFLJGQ/YkMydXjB2wSZxa56W7bzfSVhLLadSqZIMlwPH+f9++D6GKoY/EmsBD/D769OVSz1fXiZexoaF+mErlratQrgj8EYT1sN8AVNwVa0jsvnX0+5I//974L9qnUbluLrznMrBtIwfXk6Fxu4LsDfwsqpWYgw5J6r6ANYCTJMvHg7Glxaq6kPAeiJScIK6lojIxtiw0yU1lGEdTHFfCqCq76vq0sK+KkIfYIAvclib+trrVYg1R7yo6vvY8t+DKx2o2r6gR/3/CmzV2kiqWEdk86/PMX2GluXrtaijKkJ3USoK3CMiM/0IELCx0nlgmQo7AqGaHImN4yacICJPiMhlvn+hWuSLh5HYESEJc9ysXvkVNi7/GWC8iDRnrkotTU+zBTYf9kcR+Y+IXOIT4lVDVd/AhnRmYxPQy1T1nmrK0AlKznMi8qMcad4sIjn3ABV4TiM2n/Ew1a0jkvybHPMyDNsMmaxMq/fyVzTdRanspqo7YJN73xaRPWopjG8K+zw2pgx2rMaW2AqQecB5NRItTa7NWlp1KYpARD4LLFDbY3EvcJeqDspco6ogSh9sePF3qvoJbPx6cmEv5cUbJAdjczcbAQNF5CvVlKETlJznVPWcHGk+SFUPKDpwW412I/BdVV1erL/Oksm/a4xzOK3L8tdRqnqgZEdpaGjQxsbGVmYrV65k4MCqNg5LoivJ+dZbb7Fs2TL69OnDu+++u1BV1xeRodjkYSM2Z3WEqi7xbvuvsTmZt7Hx/EcBRGQidkwG2MRqu8sXc6VxKe/QFeK6XHT2fWfOnLlQO3FoaEfpaBpXMz2rnXeqFV6107gVtZ7UKXTtuOOOmuX+++9vY1aPdCU5//a3v+nMmTN11KhRSsvquQ5N8GOrzF7x3yH+v90Vd7nSuJR36El09n2p8KGi2aujaVzN9Kx23qlWeNVO4/TV5T5M8eQbywp+fKuevitQD7T3LYZp4weyxx57MGvWrKzVwdjuX7BJxCbs5N41E/zAQyKSTPCPA6ar6mIAEZmOLdm8lirT1b4/EVSG7vbxq65Cd5lTCcpPRyf4u9rEfxAEFaDL9VSCmpNvgrHoiUdJfaRr+PDhNDU1dUqg5ubmVs+wr0MWprNh1pLs+wZBPRFKJcjHmyIyQlXn+fBWclprvu+lzKFluCwxb8r1YLXD/C4GGDt2rI4bNy6Xs6Jpamoi/YxCw6MJs47uXJi1JPu+QVBPxPBXkI/baDm9dyJ29ENiPsEPvtwF2ycxDzuGYz9p+Y7Ifm4WBEEPInoqAUcddRRNTU0sXLgQ4OMiciwwFbje/8/GjhYHO0/pQOzMsLexjxmhqotF5EzsI04AZyST9kEQ9BxCqQRce23LAi0ReUJVL/XbvbNufdXXt3M9R1Uvww61DIKghxJKJQiCLkcxy8aD2hBzKkEQBEHZiJ5KEAQ9ksbJf+Xk0atiM3WZiZ5m88UxAAAgAElEQVRKEARBUDbaVSp+VPsCEXkqZTZURKaLyIv+O8TNRUTOF5GX/Jj3HVJ+Jrr7F/3gwSAIgqCbUUxPZRp2hlOaycB9qroV9m315PjvA4Ct/DoeO/IdP/H2dGBn7EM9p1f5myJBEARBFWhXqWh5via4P37YoKouwb4LnVVUQRAEQRen1DmVOGwwCLoJIjJLRJ4UkcdEZIabdXiIOwig/Ku/Kn7Y4PABhQ8MrJeD9url0L/2DlesFzmDmrOXqi5M3SdD3FNFZLLfn0rrIe6dsSHunastbFC/lKpUanbY4AVX38p5T+YXu14OCqyXQ//aO1xx2viBdSFnUHd06Hs6ychFEJSqVJLDBqfS9rDBE0TkOqz1sswVz93AOanJ+f2AH5YudhAEZUSBe0REgYu8YddqiFtE2hvibqVUOvN5g2J6z8V83qAYqj3y0RNGBtpVKiJyLdZiaRCROdgqrjhsMKgZ2SM62tvAVswzsvSwTW+7qepcVxzTReS5Am6LGsruzOcNiunldzS983Hy6FVVHfmolxGMStKuUlHVo/JYxWGDQdANUNW5/rtARG7Glv13dIg7CIDYUR8EPRoRGSgig5P/2ND0U3T8ezpBAMTZX0HQ0xkO3CwiYPXBNap6l4g8QgeGuIMgIZRKEPRgVPUVYPsc5ovo4BB3EEAolSAIgrzEgo6OE3MqQRAEQdkIpRIEQRCUjVAqQRAEQdkIpRIEQRCUjZioD4IctDdBCzFJGwS5iJ5KEARBUDaipxIEQd1RTE8xqE+ipxIEQRCUjeipBEGJxMa4IGhL9FSCIAiCshFKJQiCICgboVSCIAiCshFzKkEQBCUS+5naEj2VIAiCoGxETyUIKkS0YoOeSNV7KiIyXkSeF5GXRGRytcMPKk+kcfcm0jcoRFV7KiLSG7gQ2BeYAzwiIrep6jPVlCOoHJ1N49hJXd9EGQ7ao9rDXzsBL/knTBGR64CDgciQ3Ycem8Zzfvc1hh3wHQY0jinaTxfcQNnp9G3vnU8evYruNDKfft+TR69iUub96zCNO0W1U24k8Hrqfg6wc9qBiBwPHO+3zSLyfOYZDcDCfAHIuWWQsjAbAmsBr+WxHw3Mcjd92nFbTvp52DM74mmvc9vE52adlKMcaZxlNNAX0JTZa8DGwBPfaZ0ntgEW+f1GWPy/mueZs4AV7YSdphf2futhafsBsAyYB6wCRi/40086+syC5MnPBctAEXQmjdtNXygpjdfwnc6/X9FUM6x84VWozupsOS4dVa3aBRyOFbh3gGbgXeB94MvAnBzum4Dj/P8U4CpgRg53s4B9SpBnc+BD4LdlfMdZwD655CzgZxpWYX4+Y/4rN59UxDMa3W2fVNy96/G8ELgJGJHDX9FydiCNL0ndHwNcUI44zZiNS/JM+h1y5Zlin9mODP2AR4DpwLaYgtkAOA04sDP5MEdYAvQqYF/WNCs1ff193/er2a+iy3KBdHm+A/KM8zKchD8HuB74ZJ54fQV4Jh2XwNnAfRm3WwPLscbHJC9bv8y4OcTNp/n9p1NyJJcCh6XCnwu8gTVGmoBRqeetBVzm4c4HTkrZ7eJ5bzHwFvBnUuXZn30u1qBaBPwckJT9xcDzHleTKplHqj1RPwdr4X1OVQcBPwNOxyK6FkwAlgBHishaNZIh4QVgYnIjIn2wAvxyJ555gsfz1ljr+n87+gCXoyPMATZJ3W9M7dK3nEwANgUOVdVnVPVDVV2gqmeq6h0pd2NE5AkRWSYifxKR/gAiMkREbheRt0Rkif/fOPEkIk0icraIPAi8DWwhIpuLyAMiskJE7hWRC0XkqpSfXUTknyKyVEQeF5FxVYiHbPpeAZyuqoM8r9Uired62IOxyvc54O8isnfG3R5YQ2ALEflkyvwMYEMR+TqAiAjwB0yJPOluXga+lCkPE7ByC4Cq/j2JB5fns5hiucudHI71VD4NDAX+BVyZet4UYCusl7EX8AMRGe92QzDF0Oj2K4A/pvwejym57YGPe9jfSNk/DnwLeJQKU22l8gimVDYUkX7AkcBtVZYhzQTgJ9gwxufSFiIySkSmi8hiEXlTRH7k5lMyBfsYEXlNRBaJyI8zz8i63T1VCbwuIpNSzv8C7CYiQ/x+PPAE1mJJ/PcSkZ94eAtE5AoRWbe9l1TVxcCNwHb+nLVE5BciMhvYXkR+LyID3G6ciMwRkVNFZD6ecUXkYBF5TESWi8jLqcye5RFgK68Q6yGNy8U+wF2q2tyOuyOwtNscK9yT3LwXFpebYcrpHeA3Gb/HYJXDYGx47xrg38AwrMI5JnEoIiOBvwJnYRXUKcCNIrJ+KS/XAdakr9/vRZ2krxpzVPWnwCVYyz3NROBW4A5SDThVfQ/4GjDV4/V4rBI/O+V3PvAksD+AiAwFPkXhd58I3KCqK/1+c6BZVV9R1dXYyMu2KfcTgDNVdYmqPosptkku452q+mdVXa6qb2N5Z7dMWOf5+78BnEdL3kNVL1TV+7DRi4pSVaWiqquw7ttU4FngelV9uoOPubgcsojIp7FW9HVYd3lCym4wcC/WwtgI+AhwX45nbAv8DivsG2GFP2l9XpxxuylwJ3ABsD4wBngs5eRdLIMe6fcTsFZgmkl+7QVsAQyibcWU610bgMOA/7jRuVjvZQxwEjZO/tOUlw2ximoz4HgR2cll+T7W49kDG6Zog6fxCcDdlJ7GubjFlfFSEbklY1eWPNEOw7C5k/Y4X1XnuiL/CxbHqOoiVb1RVd9W1RVYhbVnxu80VX3a43AE8Engp6r6vqr+g5YK7GLgK8AdqnqH95qmY0M5B3b2RQuRSd+RwN/KlL5pyrEE8CZgBxEZCCAiawNfBK7260hv9FwMoKoPY8PQV2Bp8zVV/SDzzCtoqSeOxBTUe7kCT4V3ecr4OmCFiGwtIn0xRXCXux+C1SGPp9w/DozK8357AOl4H9UBvxWlFjvq38EqpmHA93NUEAVR1XJVIBOBO1V1CdYiPEBENnC7zwLzVfU8VX1XVVd4psvyReB2VX3AWzunYWOWueQ8GrhXVa9V1Q+8knks4+YKYIL3PvYEsnFzNNYlf8VbzD/ECke+IarzRWQplsHmASd51/7rwPdUdbGqXgCcQ4syw9/hdFV9T1XfAY4FLlPV6V6BvaGqz+UJE6/otlbVLVX17HzuOsghqrqeX4dgE+N9Pbx0XPfFep7lZhFW0bfH/NT/tzHFj4isLSIXeS9zOfAAsJ4v0U1IT4BvBCz2Vmkre3/fzYDDU4p2KbB7kTJ2iiR9sbmBIwoo+1K5o30n7TIXm2dYz++/gCmAe4DbsRGTgzJ55ydYA/JKVZ2R45k3A+O8fOZq9KU5DJvL/FvKbB5Wpp/H6sHDge+53SD/XZZyvwzrtbZCRD6ONQK/nzIelMPvIC/vVaVWx7TkrSAyVKSC8KGew7EWC6r6L2A2NskINmZczFzGRqQqAu/mLsrjtt1nemt0fSxz3+4Veja89Eqy17DCMTzPI7/jcTxSVY9W1bf8+WsDM1OV0V1unvCWqqa7ycXGRzWZDTSISFIYk7HwzajMart7gf2Tlm8JnIytTNtZVdfBWppgFV9CenXbPGCot3gT0nMZr2OV33qpa6CqTi1RvlKpaVkuwEgsPpf6/USs17zKG4A3kRoCA/Dy9iqtewBZ+79i5bNBVR8sEP5E4ApVTafp6VjvcxOgPzan/H+exsmw6jop9+uQWUkoIh/BRjz+W1X/nrJqzuG3ORN+VaiXs7+qXUEcikX6b0Vkvs8djKSla/s6sGURz5lHqqB75hiWx22xz7wKq4BytYLm0nqp4KZYIX6ziOcmLMRaSaNSlcG6PrGYkM2IxcpeNVR1NvAwcK6IDBJbaPF9LD4eSjntJSL9U1d6QUbfjF2hRQlXYvFwo4h81Oe3honIj0SkmCGnwVi8L/Xx+NPbeb/XsOGsKSLST0R2pfW831XA50RkfxHp7fKPk9Tkf42odlnOx6HAo6q60uPkM8BXUuX9i8CBPjTcEa7AyueV+RyIyCbYqrRsGd4e+JPPe6xS1WnY3M22PmIyz92k3a9RcCKyGda4OVNVs+E/XchvNakLpZKjgvgcVlEOx7r0CUkFsY6I/FnsmIiHsdZ6RyqIidjSvdHYmPcYbNJrjIiMxrrHG4rId31Se7CItFmLD9wAHCwis0XkJazFn43TLUTkLWwM/PM+Kd7HK6Rcu+TOx3YrP5DD7lrgez4JPggbtvqTj3PnRUQuE5vYf0pVP8QmAP83Ge4TkZEicou/w6W0bWleCnxVRPb2ynSkiHy0UJhV4nVsaG4JNhSzN7a8N93LOgqrzJMr3eO6I2M3JV9A3rrdB1tZNB1b9vlvbDVPrqHRLL8CBmBK/SFaVgQV4mhgV6z3exaWLz8jIs+6/2uAH2FLTF/HlGpNy3Q7yn6w2H6V7wDbZZW9iPwv1hu/SERe9J50fy8vq8UWijwmIjknx8UYKSKnA98EPiIiT2Fzni9gPcWkvG+NpfmzYqv1dkg9alcP/0URmZgJ5m9Y+bwgE/aaMubh/VNVX07ZHw2MBc4RkUdEZIyIHIOVtZtE5Emgt/8f4uXr69g8T7Iw4/+AC1X19zle/wpseHukiGyEKb5pqfD7ia1EFFrqysrkFa3+OvdZ5FjLj7X4/4yNSa/GKtXtsfmAbbECr5lrDjYXsDKH3Vl5wh+Jb1TLYXcH8Av/vx02Ob/EZZqsmTX2WCZ4E6vQFmEtjTeS93O3/wR+oy3r2B/GKqTXgYluPq2AvP/A15VjFcZP3e9bWGt1iNs10nafSrIvYA9gB+Apv++PKaRXXJbZ2I5owZYdvpdDjkOx1WgrgJeA/audd3LI1Oq9uvuFTQxf5P8HYxXltjWUp5iyvBCb1N8OU+hbAGfmKsupZ7Ypy9hQTi4ZxtGyT2Ul1pu/AVMqOwBPYQ2BEzP+DnTzGdgy5Ifd/B9etoZivYhXvEz8I0/4Z3n53SMT3rEZd5/CFsBciC1WWoUt7x3v79xA630qb9J6n8rpHhet9sGk7AXbm7LYr+w+laYc8TquIvmi1gUlRyLtCtyduv8h8MOMm7uBXf1/H8+4Ui0ZOyjrJFyp1DheG8lT+QIXAUel7p8nx0bJerwKvVdXv7Dx9y2xxsR4bIXgJ1L2twL71lrOIt+l3bKScf/P9LuRR6mUmjfy5XmsZ3tRPnelhpdxNwR4I3U/C5ujqXk6leOqi+GvDLmOgRiZz43a0M8y8s9lVJJiZAU4zLvYN/h4a71R7Ht0a3x+pDnHdWeNRNoQa2E2Y8Oi/6Wq/3FZG4FPUNzQWz1QdB7zuYPNseGehP4iMkNEHhKRQyooTzXKwrHYZHuCAveIyEyx4226NPV4aluuJXDZieN23YhtVvxRDnd/V9UDSpQtSzGy/gW4VlXfE5FvYuvWP1Om8MtFMe/R7VHVc7BhwbpAVf+C5Z9W+HzajcB3VXV51QUrjY7ksSOxTYOrYU1Zfg/4qD/nJhF5B3igE2U5nzwVLQsishemVNJzxbup6lyf45wuIs+paq451S5BPfZUijnmY40bn5BfFxtHXIOqnqOpIxNSV7kUSlGyqu1HSTZI/QHYsYzhl4vuerRKt0Ns09yNwNWqelOt5ekAHcljR2KLUoA1ZXmgl9+B2KT0xE6W5XzyVKwsiO0vuQQ4WFXXbD1Q1bn+uwDbC7NTOcKrFeJjenWDK4kXgL2HDRv2SmNjYyv7lStXMnBgqVsFyk93k2fmzJlLgRdVtSoZu6GhQbNpXAvqLR2hcjLNnDlzoapW+jiXNXQmjestXepJnkKyVDuNW1HrSZ08E1kHAi/suOOOmuX+++9vY1ZLups82C7wsVqltM6VxrWg3tJRtXIyUeVTjjuTxvWWLvUkTyFZqp3G6avdORURuQw7tmSBqiYHEg4F/oStdpgFHKGqS3yT069dKbyNLYV91P1MxHaigi2fTZ+Jk1V0dwB3jB07tk036sk3lrX5yE2a7vbBmxrwjOY+oqJbkf1QVPbjSZGPAoh8UgrFzKlMw5YzppmMfX9gK2wvR/Kd6gOwo5u3wk76/B2sUUKnYx/z2Qk4XVpO4w2CIAi6Ce0qFbVVCIszxgfTcvrm5dg5/on5Fd4Dewg7MG8Edlz0dLUDDJdgO5LzHZ0eBEEQdFFKXVI8XFXnAajqPGk53bfTa78l9RnS4cOH09TU1DrgAck3rHOTdV9pmpubqx5mIepNniAIehbl3qfS6bXfakdRXwwwduxYHTduXCv7C66+lfOezC/2rKPH5bWrBE1NTWRlrCX1Jk8QBD2LUvepvOnDWvjvAjev+trvIAiCoH4oVancRsu3CJJPdCbmE/y00F2AZT5Mdjewn5++OQTYz82CIAiCbkQxS4qvxU4CbRCROdgqrqnA9SJyLHbC7eHu/A5sOfFL2JLir4J9I11EzsS+bw1whtrnVoMgCIJuRLtKRVWPymO1dw63Cnw7z3Muw451DoIgCLop9XigZFBlvva1r3H77bezwQYbrDGr9AbXIKg12Y2NQXmoxwMlgyozadIk7rqrzYcIY4NrEAQdJpRKwB577MHQoUOzxrHBNQiCDhPDX0E+arbBtRpkN9BmN9VecPWtWS9tGD1y3bLLlSY2stY/xQyh9bTzwUKpBB2l4htcq0H2UNKTR68quKk2F5XeaBsbWYOuSLdTKu21HHpaq6ETvCkiI7yXUuwG13EZ86YqyBkEQR0RcypBPmKDaw9BRGaJyJMi8piIzHCzoSIyXURe9N8hbi4icr6IvCQiT4jIDrWVPqg3QqkEHHXUUey66648//zzAB/3Ta1TgX1F5EVgX78H2+D6CrbB9Q/At8A2uALJBtdHiA2uXY29VHWMqo71+w6t/guChG43/BV0nGuvXfM5cETkCVW91G9jg2vP5WBahjMvx4YyTyW1+g94SETWS4ZJayJlUHeEUgmCQIF7RESBi3whRUdX/7VSKuVa4VfJFXCFPqGRj/Y+vZGLSslfr6sDQ6kEQbCbqs51xTFdRJ4r4LaoVX7lWuFXyRVwhT5Lno96WiVYr6sDY04lCHo4qjrXfxcAN2MnInT08xZBAPTAnkpsVgqCFkRkINBLVVf4//2AM2hZ/TeVtqv/ThCR67AjeZbFfEqQpscplSAIWjEcuNnOCaUPcI2q3iUij9CBz1sEQUIolSDowajqK8D2OcwX0cHVf/VGnEJcG2JOJQiCICgboVSCIAiCshFKJQiCICgboVSCIAiCshFKJQiCICgbsforB3F8fhAEQWlETyUIgiAoG9FTCYIgqCA9beQjeipBEARB2QilEgRBEJSNGP4KghLpacMaQVAMoVRKIF2ZnDx6Vc7vMkSFUjvizKcgqB2hVIIg6HJEw6F+iTmVIAiCoGyEUgmCIAjKRtWHv0RkPPBroDdwiapOrbYM1aAnT+L2lDTuqUT6lpfuVldUVamISG/gQmBf7FvXj4jIbar6TDXlCCpHpHH3plrpm1S0+RbCBPVLtXsqOwEv+dfm8O9cHwz0uAqnmInGrtZCcSqexl1lkrabpnGn07erpF9QGmJfB61SYCJfBMar6nEiMgvYyK3e99/jsVbQy36/DfC8/y4CFgIfAVYDr+YIYjQwC1jRAbF6uRxDMCW7ClgJzMe+wQ2wI/Bhxt9c4E2gAWgGNgYGAeL+3/BfgH4uW/KMVcBbHkZCb6ARWMft3wAWu91gYBN/Dv5+s4EP/F6Azfwd0rIldpsDA93/C7SNn5HA+v7/fWCgfzYWEbkY2BPYCviaqk6jAJ7Gf8TicrX/9gImAT9X1Y1F5HgsrQHGYC3ehVg6rEX50ra3v9sQl+E9LF4WZdwNc3e9sTRagsX/arffCNgQSArL+26/1O8HA1v7fZJ3AQYA22L54/mU2ab++yGWD+a5XTafiNvNS90n6fwhln9KSedewC+AUzVTAYjIRGAa8HVVvSTjv1UZ9vtjgJ1V9YSMu3QaJ+W4o4zG8s/jtMRJAzCC1g3iXrQuny9icZ6LRmAoLWkJli+eoW38p+0A+gJbYHm0N5YPlmDp8CGWT9bD0nYeVg7TbIjFfx9gGZafk7ByyfWfPO+Q0ICVm1xspqrr57GrLKpatQs4HBuDBYvQqcAFKftxwJwc/pqA4/z/XOCqPM+fBezTAXnWAh4BpgPbYRllIPBFYErKnQIfyfOMJ7GMdTaWKQYD38Ey9a7uptGf0cfvx2IKZ9/Uc64F/oQppt2xTDfK7YYDG6Vk/jlwW8rv/wP+jlU2T2GZfLzb9QO+68+cB4zLyP8NrMBvjFU6zwDfTNl/G/tW+QxgUpFpvCJJB+AY4IIi03ZKGdO2n8t8B1bZ9gXGY5XwSSl3J7vZC+6m0f08AvTLJRewP/AOMDyVbxd4vA9Lufulx21TyuwZzyu9gS09TT6fJ5/MyLxTOp0/Vs50djdDgOc8Dx3XXhlOp2+F6otZWAPrRymz49Lx2V75zPHMacBZeexaxX/GbqjLswhodLNNsLmlj/v9ROAA4FZS9UfK7jn3M8jdXF6MXAXeZUZH3FfrqvbqrzkeqQkNtNXm1eQYrJAdoqpPqepqVV2pqjeo6pQin7ER8C9V/bGqLlbVFap6PnAlcG4uD6o6A3gaa6UjIgOBw4DTVLVZVf8B3Obyoapvqmo6nlZjPbaECcCZqroEeBf4A9YzQFXfV9Vf+TNX05aJwHmqOkdV3wDOS/y6/wtV9T5/bjHMoXUrcmNqk8bHYD2Cw1X1VVX9QFXvwhT+GSKyjoisA/wMOBFY7m5mAUdgPYKv5Hqwqt6NKc4tU8bvA7cAR8KauYcjgKsz3huBqz2vvQz8AxhV5DutSWdVfZYyprPz/4Dzyd/6hbZluNLpOx84RUTWq2AYxXASluaveh5BVV9X1f9W1Sf8/nJVvZPcvenPAZe6n2asbviSiKxdHfGrR7WVyiPAViKyud/vhVWetWIf4G5VXdmuy/ysA/w5h/n1wG65Mo2I7IL1jF5yo62B1ar6QsrZ46QqGxHZVESWYi3kU7DeCiIyBFNsj+fz2w6jOuE3F49gSmVDEemHVbK1SON9gTtzpO2NQH9gV+BT/v+mtAMv9Hf6M1ohxkFYzyA7j3AFVvGD9Waepm2F+ytggoj0FZFtXI57M25eE5E5QKOINHi4FU1nEdkJ60H/vp3nrCnDVUrflVhv9pQKhlEM+5DJJx1E/Erfr4UNKyd8S0QWi8hMETmsE2HVlKoqFVVdBZwA3I11wTcGHhSRpSJyS5GPmVlGkRpIzWuIyBiXZbmIZMeAH3W75NrfzXvRMuadZp7bDUmZLRSRd4B/Ab/FWrZg3eFlGf/LsKE0AFR1tqqu5zL/BOtKJ34T9wAXZ/22QzbsZcAgEZE87gviabwYq2DfwRTm2aU8q5M0kCNdXL6Fbt8ALHSzizNO57l9whGu1Fdileg5qro07UFV/wkMdWUxAYuDLLdjw6vvYGl4qao+4nYLgU9ivaQdgddo6elk0zn53+l09l7Vb4ETVTU7d9iKTBl+FrheVZ8uUoZS+CvwU+BEESnXHMEpmbJ8ecZ+YcouUWbDsDyRzSfFcidwnIg0isi6wKlunjQ6z8cUzAbAacA0EdmtnWeWKktFqfrmR1W9Q1W3xiY6D1LV9fw6BBs/7ZvDW19aJqXLqVQWYZN+iWyPecX9BawVkWaHlKzr+RAI2ETrCNoygpZJ34QGrHCfgo3DJ+/ajPV40qxDjm60qi4GLgduFZE+tExIruP2F+fzm4ds2OsAzeqDtiXyDrCfqvZW1QEdSNtyspAc6eJxlkxwLgQaRKSPx1uaEbQeBrre031tbNhrgoh8I0e4V2KV7l7AzZmwhwJ3AWdgPaRNgP1F5FtgPSRVnaGqq1T1TeAgYD8fpmuVzqn/5UjnbwFPqOq/inlQUoZVdUtVrXSD4Q5VfQpTxpPL9MxfZMryxIx9Q8ruF262CBiRI58Uy2XYvGkT1oO9383nAKjqo6q6yNP+Dqwx8YVCD+yELBWl3nbUz8YKedIqw1vMm2GttnJzH1ZoB3biGfdik5dZjsDmWt5OG/pY+nnYHMW33PgFoI+IpLvC22OZLxd9sBbNOj6PMs/dF+M3y9Od8NsRqp229wIH5Ejbw7AVPQ9hPcb3yBRe93MAlj/a4GPqd2Lj5FmuxNL1jmzaYyuHVqvqFV55zAGuAw7M8w6JYpcKp/PewKEiMl9E5mPDgueJyG+KfHY1OB34OjbCUQvuxeKopDpTVT9U1dNVtVFVN8bi/g2/cnqh9XBZl6GulIqqzgYeBs4VkUEishbwfayV+1DKaS8R6Z+60r2Kvhm7QntxrsAK6s0isp2I9BaR/tjYcrH8DPiUiJwtIkNFZLCInIgNf5xawN9U4Aci0t/H/W/CJpAHerf3YKyCQkS+ICLbiEgvHwL4JfAf77Uk7/ETERkiIh/FCt+0JCARWcvfC6Cfx4uk/J4kIiNFZCNsNVTabz/3K7TEbYfzTQ3S9kqsFfhnH3Lo60OW52Mrc5ap6jIs/S4QkfHuphGbI5vjz2iDiGyMrSRrU6Gr6qvYEuwf5/D6gnmXL3tabgh8CZ/rEJGdU+k8zGVtcjmhcuk8CVtNNsavGR4vud6hJqjqS9jqyO/USIRfYr27y0VkMwCPy1+KyMf9vq/Hfy+skdjfhxbxumFLH27c1p93RjLcKCJf9HLRS0T2wxaJ1HK+uXS0RsvOyLNEFBsS+DM217EQG7vdFivEz2Pj9Zq55qSembUruEwPWBebPH0NGy9/DZvM3SnlRrE9K6uwIa3V+LJGbKnhP93vKmyYoQnYPeW/kcxSRaySfhobx06ec4s/Zzbw5ZTbE7G9G8n+meuwdehgS1Mfcz/LseG417C1+n/CJpRzxUtjSo6fe7wu9v+SCrsph99x5UzblP2UMqftUOAibMnwOx7fx2XcjHd53sOG4d50P0Mycn3gaduMNUR+D6zt9uPIsVza7Votgep/Ek0AAAypSURBVAU+g012L/Nw/4CNpd+PtVrfd1nmeTr/zdNyOra0/DJP51ZLowvEUVHpnHlOUzaeqlgnPInl5xl+f6i/+4vAA1gPvynjr6NLit9PpWUzNq8GqXKK7a15LHUtx+Z2/oOV/9Uuy1WpfDAtR/xPcrutsfrrbax8ZtPu754nlmONjCM9rRcAT2XydBIf05N86ul7Prb45wlsuL42dXutAu5gZuuNbSrbAqskHydVGVVJhhFJQmGToy9gyu7nwGQ3nwycW2W5TgKuAW73++uBI/3/74H/qnX61etVD/nK5ajLvFWDeJiFzWekzWoeB55P5mNDtVOAU6oU7h7ADhmlkjM+sCHUO1257AI8XKt0rKvhrwKsORpCVd/HWnAHV1MAVZ2nqo/6/xXYypeRLkeyeuRy4JBqyeTDMAcBl/i9YC3hGzoij4hcJiILROSplNlQEZkuIi/675AkDBE5X0ReEpEnRGSHlJ+J7v5FsZ3Z9U7N8xXUZ96qI+ohDvYGXlbVSsz95UVVH6DlVI2EfPFxMHCFGg8B64lIrgVEFaerKJWRwOup+zkUOWEnIj8SkeYc152lCuPj7p/A5giGq+o8sMoBm0CvFr8CfkDLUQ/DgKVqyz6h+Hiahg0DpZkM3KeqW2ET1snKmwOw4ZqtsGM4fgdrVjadDuyMVdanJ4qoUpQhbUvOV5WijvJWLVDgHrF9GskRLx2OAxF5Ok++OLpEuY7EVm4lnOANqssqncdzkC8+6iYvdxWlkmsVRFFLXlX1HFUdlOM6oCRBbPXSjcB3VXV5Kc8oByLyWWCBqqaXWJcUT2VqEe0PTFc7VWAJNt6bVVRlpQxpW3K+qgT1krdqyG6qugPWcPm2iOxRykNUdVSefJE93aBdxDZ4fp6WDc6/w5aUj8Hmvc4rRcYKUDd5uaoHSnaUhoYGbWxsrLUYOVm5ciUDB3ZmJXL9sHLlSvr06cNLL73Eu+++u1BV1xeRpWp7dgAQkSWqOkREbgemqh0Hgojch61yGwf0V9Wz3Pw04B1tWedP6llrDhscMGDAjptssknWCQAffvghvXp1lXZP56nW+77wwgsLtYqHDWbLcVcqO11F1qycM2fOXA1skvRqqkldf6O+sbGRGTNm1FqMnDQ1NTFu3Lhai1EWmpqaaGxs5LOf/SxPP/10e+PG+VpERbeU1DZtXQwwduxYzZfG3SmOi6Fa7ysiVZ0byJbjrpSuXUXWrJwi8l4tFAp0neGvoPq8mUz0+e8CN893oGC1DxoMgiA/VW04pKnrnkqt6G6f9yyR27CTbaf6760p8xPEPs60M7BMVeeJyN3AOamJy/2AH1ZZ5rqim36kq9M8+caydr/m2BPjpcxkT3OoGqFUAs4880yeeeYZFi5cCPBxETkWUybX+//ZtBxFcwe2Jv4lLON+FexMMhE5E9vYB7ZbODv5HwRBNyeUSsBpp522ZjxWRJ5Q1Uvdau+sW7WVHd/O9RxVvQzbBdwjiM/iBkFb2lUqInIZkCxf3c7NhmJHgDRiu2CPUNUlvvnu11hL9m3siIJH3c9E7Mh2sOM1ssdNdxkaJ/+Vk0evKtiFj+57EAQ9kWIm6qfRBTfGBUEQBNWnXaXSVTfGBUEQBNWn1DmVVkcFiEh7RwUUfYRAemPc8OHDaWpqKlHE0jl59Kp23QwfUNhdLeQulebm5i4lbxAE9Uu5J+rLvjGuFhuP2lvuCKZQznsyf/TNOnpcGSWqLF1lg1cQBPVPqZsfY2NcEHQhXn/9dfbaay8+9rGPAYwSkf+GHnMadVBFSlUqycY4aLsxboJnyF3wjXHYx5j2E/ti3RBsY9zd2YcGQVAZ+vTpw3nnncezzz4LdrT+t/0LhLHoJigrxSwpvhY7LLBBROZgGSo2xgVBF2LEiBGMGLHm8xof0vqbLePc/HLsq4+nklp0AzwkIsmim3H4ohsAEUkW3aSPhg96MO0qFVU9Ko9VbIwLgq5JP/J8s6Vci24KLbhpb5EL1M9Cl66yiKWe5Iwd9UHQg2hubgb7Hsgxqrrc9ivnpFOLbgotuLng6lsLLnKB+lno0lUWsdSTnHFKcRD0ED744AMOO+wwgMWqepMbx6KboKyEUgmCHoCqcuyxxyarv95MWcWim6CsxPBXEPQAHnzwQa688kpGjx4NsK2IPAb8iFh0E5SZUCpBQURkFrACWA2sUtWxpRwoGtSW3XffneTT4SLyjKqOTVnHopugbIRSCYphL1VdmLpP9jZMFZHJfn8qrfc27Iztbdi52sKWgzjWPghKI+ZUglLo6IGiQRD0EKKnErSHAveIiAIX+VLRju5tmJd+YLGHhtZy7X0xh4qWg/T71dNegyAolVAqQXvspqpzXXFMF5HnCrjt9B6GNLVce1/MoaLlIL0fo572GgRBqcTwV1AQVZ3rvwuAm7Hznjq6tyEIgh5CKJUgLyIyUEQGJ/+xPQlP0fG9DUEQ9BBi+CsoxHDgZj/Kow9wjareJSKP0IG9DUEQ9BxCqQR5UdVXgO1zmC+ig3sbgiDoGcTwVxAEQVA2elxPJTa1BUEQVI7oqQRBEARlI5RKEARBUDZ63PBXENQT6eHYk0evarPpctbUg6otUhB0iuipBEEQBGUjeipBjyQWbARBZYieShAEQVA2QqkEQRAEZSOGvypEe8MrMQEbBEF3JHoqQRAEQdkIpRIEQRCUjVAqQRAEQdmIOZUgCII6ppjl79PGD6yCJMVRdaUiIuOBXwO9gUtUdWq1ZQgqS6Rx+SimQqn2oo9I36AQVVUqItIbuBDYF/v07P9v7/5CpCrjMI5/Hyy9rMigMKsNJPKiQKQkIrICswuXqGAhKqOQqPC6CAq687YixEqoLtSQoImKICK6EE0vTNzEmOiipaA/hhCBsfXr4hxldp0/Z3fe8294PjAwZ87szvN737Pn3XPmzDtHJXUi4rs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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(20,20))\n", + "data.hist()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Standardize data" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[ 7.69712416e-01 -1.12341031e+00 -1.90047029e-01 1.37605977e-01\n", + " -6.06718766e-01 -7.20629784e-01 -3.11684110e-01 -1.33070267e+00\n", + " -2.25681314e-02 -3.60971652e-01 -9.25122883e-01]\n", + " [ 5.07884366e-01 -4.10857567e-01 -3.76275096e-01 -2.43225309e-01\n", + " -1.18128598e+00 -9.24503172e-01 3.20837658e+00 -1.30322672e+00\n", + " -5.92370366e-01 9.02050407e-01 1.03699430e+00]\n", + " [ 9.00626442e-01 -4.10857567e-01 -9.16336490e-01 -8.65106417e-03\n", + " -1.05360437e+00 -4.63244125e-02 -3.11684110e-01 -1.30383154e+00\n", + " -4.59030969e-01 -1.40916462e+00 2.31808537e+00]\n", + " [ 7.69712416e-01 -5.74065761e-01 -7.11485617e-01 -8.70124978e-01\n", + " 1.59370848e-01 6.27395116e-01 -3.11684110e-01 -1.30201709e+00\n", + " -7.01486075e-01 -2.30020073e+00 6.98862456e-01]\n", + " [ 1.42428254e+00 2.04070778e-03 -3.66963693e-01 -1.04957427e+00\n", + " -4.79037163e-01 2.00315519e-01 -3.11684110e-01 -1.30184429e+00\n", + " -7.71259861e-02 -1.97723618e+00 1.44656245e+00]]\n" + ] + } + ], + "source": [ + "from sklearn.preprocessing import StandardScaler\n", + "array = data.values\n", + "#separate array into input and output components\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "scaler = StandardScaler().fit(X)\n", + "rescaledX = scaler.transform(X)\n", + "# summarize transformed data\n", + "#set_printoptions(precision=3)\n", + "print(rescaledX[0:5,:])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Feature selection\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Chose Recursive Feature Elimination because i dont have the library for my data in this case\n" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Num Features: 8\n", + "Selected Features: [ True False True False True True True True False True True]\n", + "Feature Ranking: [1 3 1 2 1 1 1 1 4 1 1]\n" + ] + } + ], + "source": [ + "from sklearn.feature_selection import RFE\n", + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "array1 = data.values\n", + "X = array1[:,0:11]\n", + "Y = array[:,11]\n", + "# feature extraction\n", + "model = LogisticRegression()\n", + "rfe = RFE(model,8)\n", + "fit = rfe.fit(X,Y)\n", + "print(\"Num Features:\", fit.n_features_)\n", + "print(\"Selected Features:\", fit.support_)\n", + "print(\"Feature Ranking:\", fit.ranking_)" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", + " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", + " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", + " 'CLASS'],\n", + " dtype='object')" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data.columns" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " FULL_Charge FULL_AURR980107 FULL_GEOR030101 FULL_OOBM850104 \\\n", + "0 4.0 0.873 0.987 -4.833 \n", + "1 4.0 0.892 0.931 -0.584 \n", + "2 2.0 0.901 1.039 -5.664 \n", + "3 4.5 0.869 0.982 -5.423 \n", + "4 -4.0 1.061 0.976 -2.002 \n", + ".. ... ... ... ... \n", + "753 -1.5 1.100 0.991 -1.987 \n", + "754 -1.0 1.085 1.027 -0.745 \n", + "755 -1.0 1.108 1.033 -1.789 \n", + "756 -1.0 0.955 1.023 1.141 \n", + "757 -7.0 1.078 1.009 -0.066 \n", + "\n", + " NT_EFC195 AS_MeanAmphiMoment AS_FUKS010112 CT_RACS820104 \n", + "0 0 0.382 7.225 1.234 \n", + "1 0 0.320 4.942 1.853 \n", + "2 0 0.164 5.969 1.174 \n", + "3 0 2.010 5.462 1.138 \n", + "4 0 2.758 5.582 1.453 \n", + ".. ... ... ... ... \n", + "753 0 15.185 7.053 1.325 \n", + "754 0 16.550 6.729 1.132 \n", + "755 0 16.112 6.036 1.219 \n", + "756 0 20.630 5.669 1.111 \n", + "757 0 17.168 6.688 1.305 \n", + "\n", + "[758 rows x 8 columns]" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "drop_test = test.drop(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'AS_DAYM780201'],axis=1)\n", + "drop_test" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "seleceted_train = X[:,fit.support_]\n", + "selected_test = test.values[:,fit.support_]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Evaluate the Performance of Machine Learning Algorithms with Resampling¶\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Split into Train and Test Sets" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 91.55701754385966\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "array = data.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "test_size = 0.30\n", + "seed = 7\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", + "random_state=seed)\n", + "model = LogisticRegression()\n", + "model.fit(X_train, Y_train)\n", + "result = model.score(X_test, Y_test)\n", + "print(\"Accuracy: \", (result*100.0))\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## K-fold Cross Validation" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: (83.5359128018065, 27.08521320979506)\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "\n", + "array = data.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "\n", + "num_folds = 10 #number of folds to use\n", + "seed = 7 #reproducibility\n", + "\n", + "kfold = KFold(n_splits=num_folds, random_state=seed)\n", + "model = LogisticRegression()\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "\n", + "print(f\"Accuracy:\", (results.mean()*100.0, results.std()*100.0))\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Leave One Out Cross Validation" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: (91.4417379855168, 27.974673416141517)\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import LeaveOneOut\n", + "from sklearn.model_selection import cross_val_score\n", + "\n", + "array = data.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "num_folds = 10\n", + "loocv = LeaveOneOut()\n", + "model = LogisticRegression()\n", + "results = cross_val_score(model, X, Y, cv=loocv)\n", + "print(\"Accuracy:\", (results.mean()*100.0, results.std()*100.0))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Repeated Random Test-Train Splits" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: (91.30482456140349, 0.5803122202806698)\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import ShuffleSplit\n", + "from sklearn.model_selection import cross_val_score\n", + "\n", + "array = data.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "n_splits = 10\n", + "test_size = 0.30\n", + "seed = 7\n", + "kfold = ShuffleSplit(n_splits=n_splits, test_size=test_size, random_state=seed)\n", + "model = LogisticRegression()\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(\"Accuracy: \" , (results.mean()*100.0, results.std()*100.0))\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Machine Learning Algorithm Performance Metrics" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Algorithms Overview\n", + "### linear machine learning algorithms:\n", + "\n", + " Logistic Regression.\n", + " Linear Discriminant Analysis.\n", + "### onlinear machine learning algorithms\n", + "\n", + " k-Nearest Neighbors.\n", + " Naive Bayes.\n", + " Classication and Regression Trees.\n", + " Support Vector Machines.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Linear Machine Learning Algorithms" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Logistic Regression" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.835359128018065\n", + "MCC: 0.8342865299822478\n", + "[False True]\n", + "False: 383\n", + "True: 375\n" + ] + } + ], + "source": [ + "# Logistic Regression Classification\n", + "from pandas import read_csv\n", + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "array = data.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "num_folds = 10\n", + "kfold = KFold(n_splits=10, random_state=7)\n", + "model = LogisticRegression()\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(results.mean())\n", + "\n", + "model.fit(X,Y)\n", + "output = model.predict(test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "my_report = pd.DataFrame(output)\n", + "my_report.columns = ['CLASS']\n", + "my_report.index.name = \"Index\"\n", + "my_report['CLASS']=my_report['CLASS'].map({0.0:False, 1.0:True})\n", + "my_report.to_csv(\"report_XGB.csv\")\n", + "\n", + "print(my_report['CLASS'].unique())\n", + "print('False: ',my_report.groupby('CLASS').size()[0].sum())\n", + "print('True: ',my_report.groupby('CLASS').size()[1].sum())" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " FULL_Charge FULL_AURR980107 FULL_GEOR030101 FULL_OOBM850104 \\\n", + "0 4.0 0.873 0.987 -4.833 \n", + "1 4.0 0.892 0.931 -0.584 \n", + "2 2.0 0.901 1.039 -5.664 \n", + "3 4.5 0.869 0.982 -5.423 \n", + "4 -4.0 1.061 0.976 -2.002 \n", + ".. ... ... ... ... \n", + "753 -1.5 1.100 0.991 -1.987 \n", + "754 -1.0 1.085 1.027 -0.745 \n", + "755 -1.0 1.108 1.033 -1.789 \n", + "756 -1.0 0.955 1.023 1.141 \n", + "757 -7.0 1.078 1.009 -0.066 \n", + "\n", + " NT_EFC195 AS_MeanAmphiMoment AS_FUKS010112 CT_RACS820104 \n", + "0 0 0.382 7.225 1.234 \n", + "1 0 0.320 4.942 1.853 \n", + "2 0 0.164 5.969 1.174 \n", + "3 0 2.010 5.462 1.138 \n", + "4 0 2.758 5.582 1.453 \n", + ".. ... ... ... ... \n", + "753 0 15.185 7.053 1.325 \n", + "754 0 16.550 6.729 1.132 \n", + "755 0 16.112 6.036 1.219 \n", + "756 0 20.630 5.669 1.111 \n", + "757 0 17.168 6.688 1.305 \n", + "\n", + "[758 rows x 8 columns]" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "drop_test" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Linear Discriminant Analysis¶\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", + "\n", + "\n", + "array = data.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "num_folds = 10\n", + "kfold = KFold(n_splits=10, random_state=7)\n", + "model = LinearDiscriminantAnalysis()\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(results.mean())\n", + "\n", + "\n", + "model.fit(X,Y)\n", + "output = model.predict(test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "lda_report = pd.DataFrame(output)\n", + "lda_report.columns = ['CLASS']\n", + "lda_report.index.name = \"Index\"\n", + "lda_report['CLASS']=lda_report['CLASS'].map({0.0:False, 1.0:True})\n", + "lda_report.to_csv(\"ldareport.csv\")\n", + "\n", + "print(lda_report['CLASS'].unique())\n", + "print('False: ',lda_report.groupby('CLASS').size()[0].sum())\n", + "print('True: ',lda_report.groupby('CLASS').size()[1].sum())\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Nonlinear Machine Learning Algorithms" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### k-Nearest Neighbors" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.8027933385443807\n", + "MCC: 0.8690586462107053\n", + "[False True]\n", + "False: 402\n", + "True: 356\n" + ] + } + ], + "source": [ + "from sklearn.neighbors import KNeighborsClassifier\n", + "\n", + "array = data.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "num_folds = 10\n", + "kfold = KFold(n_splits=10, random_state=7)\n", + "model = KNeighborsClassifier()\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(results.mean())\n", + "\n", + "\n", + "\n", + "model.fit(X,Y)\n", + "output = model.predict(test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "report_k = pd.DataFrame(output)\n", + "report_k.columns = ['CLASS']\n", + "report_k.index.name = \"Index\"\n", + "report_k['CLASS']=report_k['CLASS'].map({0.0:False, 1.0:True})\n", + "report_k.to_csv(\"report_k.csv\")\n", + "\n", + "\n", + "print(report_k['CLASS'].unique())\n", + "print('False: ',report_k.groupby('CLASS').size()[0].sum())\n", + "print('True: ',report_k.groupby('CLASS').size()[1].sum())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Naive Bayes" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.880815746048289\n", + "MCC: 0.8407203694376205\n", + "[ True False]\n", + "False: 370\n", + "True: 388\n" + ] + } + ], + "source": [ + "from sklearn.naive_bayes import GaussianNB\n", + "array = data.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "kfold = KFold(n_splits=10, random_state=7)\n", + "model = GaussianNB()\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(results.mean())\n", + "\n", + "\n", + "model.fit(X,Y)\n", + "output = model.predict(test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "report_bayes = pd.DataFrame(output)\n", + "report_bayes.columns = ['CLASS']\n", + "report_bayes.index.name = \"Index\"\n", + "report_bayes['CLASS']=report_bayes['CLASS'].map({0.0:False, 1.0:True})\n", + "report_bayes.to_csv(\"report_bayes.csv\")\n", + "\n", + "\n", + "print(report_bayes['CLASS'].unique())\n", + "print('False: ',report_bayes.groupby('CLASS').size()[0].sum())\n", + "print('True: ',report_bayes.groupby('CLASS').size()[1].sum())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Classiffication and Regression Trees" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.tree import DecisionTreeClassifier\n", + "array = data.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "kfold = KFold(n_splits=10, random_state=7)\n", + "model = DecisionTreeClassifier()\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(results.mean())\n", + "\n", + "\n", + "model.fit(X,Y)\n", + "output = model.predict(test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "report_tree = pd.DataFrame(output)\n", + "report_tree.columns = ['CLASS']\n", + "report_tree.index.name = \"Index\"\n", + "report_tree['CLASS']=report_tree['CLASS'].map({0.0:False, 1.0:True})\n", + "report_tree.to_csv(\"report_tree.csv\")\n", + "\n", + "\n", + "print(report_tree['CLASS'].unique())\n", + "print('False: ',report_tree.groupby('CLASS').size()[0].sum())\n", + "print('True: ',report_tree.groupby('CLASS').size()[1].sum())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Support Vector Machines " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.svm import SVC\n", + "\n", + "array = data.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "kfold = KFold(n_splits=10, random_state=7)\n", + "model = SVC()\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(results.mean())\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/Thur 20 Feb/ACE_ClassML Pipeline.ipynb b/Thur 20 Feb/ACE_ClassML Pipeline.ipynb index e55fe6d..c6ffee2 100644 --- a/Thur 20 Feb/ACE_ClassML Pipeline.ipynb +++ b/Thur 20 Feb/ACE_ClassML Pipeline.ipynb @@ -3865,7 +3865,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.7.3" }, "varInspector": { "cols": { diff --git a/kakooza trevor Starter Kernel.ipynb b/kakooza trevor Starter Kernel.ipynb new file mode 100644 index 0000000..1885d6f --- /dev/null +++ b/kakooza trevor Starter Kernel.ipynb @@ -0,0 +1 @@ +{"cells":[{"metadata":{},"cell_type":"markdown","source":" # KAKOOZA TREVOR\n## Kaggle assignment\n### started on the 28th /feb/2020"},{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n for filename in filenames:\n print(os.path.join(dirname, filename))\n\n# Any results you write to the current directory are saved as output.","execution_count":34,"outputs":[{"output_type":"stream","text":"/kaggle/input/amp-data-set/Test.csv\n/kaggle/input/amp-data-set/AMP_TrainSet.csv\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"# Import the necessary tools required to work on the datasets**"},{"metadata":{"trusted":true},"cell_type":"code","source":"#import the necessary libraries you are going to use\nimport warnings\nwarnings.filterwarnings('ignore')\n\n# -----> Put your code here below:\n\n\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns","execution_count":35,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"\n# This first session is about loading the give dataset and viewing them. \n\n* The two data set provided are\n1. test.csv\n2. AMP_TrainSet.csv \n\n### Now load the data set using.\n```\nTrain = pd.read_csv(\"../input/amp-data-set/AMP_TrainSet.csv\")\nTest = pd.read_csv(\"../input/amp-data-set/Test.csv\")\n```\n"},{"metadata":{"trusted":true},"cell_type":"code","source":"#using pandas we call the data set\nTest = pd.read_csv('/kaggle/input/amp-data-set/Test.csv')\nTrain = pd.read_csv(\"../input/amp-data-set/AMP_TrainSet.csv\")","execution_count":36,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Check the dataset info\n## View the first five raws of the datasets"},{"metadata":{"trusted":true},"cell_type":"code","source":"#head.() is ued to view the first five raws of the data set.\nTest.head()","execution_count":37,"outputs":[{"output_type":"execute_result","execution_count":37,"data":{"text/plain":" FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n0 4.0 3.704 0.873 73.519 \n1 4.0 4.444 0.892 62.444 \n2 2.0 0.000 0.901 47.000 \n3 4.5 0.000 0.869 69.222 \n4 -4.0 21.591 1.061 71.682 \n\n FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n0 0.987 -4.833 0 0.382 \n1 0.931 -0.584 0 0.320 \n2 1.039 -5.664 0 0.164 \n3 0.982 -5.423 0 2.010 \n4 0.976 -2.002 0 2.758 \n\n AS_DAYM780201 AS_FUKS010112 CT_RACS820104 \n0 74.556 7.225 1.234 \n1 56.056 4.942 1.853 \n2 47.000 5.969 1.174 \n3 69.222 5.462 1.138 \n4 66.000 5.582 1.453 ","text/html":"
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FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201FULL_GEOR030101FULL_OOBM850104NT_EFC195AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CT_RACS820104
04.03.7040.87373.5190.987-4.83300.38274.5567.2251.234
14.04.4440.89262.4440.931-0.58400.32056.0564.9421.853
22.00.0000.90147.0001.039-5.66400.16447.0005.9691.174
34.50.0000.86969.2220.982-5.42302.01069.2225.4621.138
4-4.021.5911.06171.6820.976-2.00202.75866.0005.5821.453
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"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"Train.head()","execution_count":38,"outputs":[{"output_type":"execute_result","execution_count":38,"data":{"text/plain":" FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n0 5.0 0.000 0.951 74.842 \n1 4.0 5.405 0.931 71.595 \n2 5.5 5.405 0.873 73.595 \n3 5.0 4.167 0.895 66.250 \n4 7.5 8.537 0.932 64.720 \n\n FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n0 0.975 -3.663 0 0.282 \n1 0.957 -4.011 1 0.600 \n2 0.961 -2.512 0 0.593 \n3 0.999 -1.362 0 0.614 \n4 0.979 -2.091 0 0.616 \n\n AS_DAYM780201 AS_FUKS010112 CT_RACS820104 CLASS \n0 73.444 5.661 1.041 1 \n1 68.222 6.537 1.453 1 \n2 69.444 4.934 1.722 1 \n3 67.222 4.316 1.382 1 \n4 72.944 4.540 1.539 1 ","text/html":"
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FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201FULL_GEOR030101FULL_OOBM850104NT_EFC195AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CT_RACS820104CLASS
05.00.0000.95174.8420.975-3.66300.28273.4445.6611.0411
14.05.4050.93171.5950.957-4.01110.60068.2226.5371.4531
25.55.4050.87373.5950.961-2.51200.59369.4444.9341.7221
35.04.1670.89566.2500.999-1.36200.61467.2224.3161.3821
47.58.5370.93264.7200.979-2.09100.61672.9444.5401.5391
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"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"## Shape function\n* This function helps to view the total raws and columns (dimension) of the dataset. "},{"metadata":{"trusted":true},"cell_type":"code","source":"# check the dimensions of your data\n\nTrain.shape, Test.shape\n","execution_count":39,"outputs":[{"output_type":"execute_result","execution_count":39,"data":{"text/plain":"((3038, 12), (758, 11))"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"# Data type\n* This returns a Series with the data type of each column.\n* The result’s index is the original DataFrame’s columns"},{"metadata":{"trusted":true},"cell_type":"code","source":"Test.dtypes","execution_count":40,"outputs":[{"output_type":"execute_result","execution_count":40,"data":{"text/plain":"FULL_Charge float64\nFULL_AcidicMolPerc float64\nFULL_AURR980107 float64\nFULL_DAYM780201 float64\nFULL_GEOR030101 float64\nFULL_OOBM850104 float64\nNT_EFC195 int64\nAS_MeanAmphiMoment float64\nAS_DAYM780201 float64\nAS_FUKS010112 float64\nCT_RACS820104 float64\ndtype: object"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"Train.dtypes","execution_count":41,"outputs":[{"output_type":"execute_result","execution_count":41,"data":{"text/plain":"FULL_Charge float64\nFULL_AcidicMolPerc float64\nFULL_AURR980107 float64\nFULL_DAYM780201 float64\nFULL_GEOR030101 float64\nFULL_OOBM850104 float64\nNT_EFC195 int64\nAS_MeanAmphiMoment float64\nAS_DAYM780201 float64\nAS_FUKS010112 float64\nCT_RACS820104 float64\nCLASS int64\ndtype: object"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"## isnull().sum\n* This function helps to see if the dataset has any missing values."},{"metadata":{"trusted":true},"cell_type":"code","source":"Train.isnull().sum","execution_count":42,"outputs":[{"output_type":"execute_result","execution_count":42,"data":{"text/plain":""},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"Test.isnull().sum()","execution_count":43,"outputs":[{"output_type":"execute_result","execution_count":43,"data":{"text/plain":"FULL_Charge 0\nFULL_AcidicMolPerc 0\nFULL_AURR980107 0\nFULL_DAYM780201 0\nFULL_GEOR030101 0\nFULL_OOBM850104 0\nNT_EFC195 0\nAS_MeanAmphiMoment 0\nAS_DAYM780201 0\nAS_FUKS010112 0\nCT_RACS820104 0\ndtype: int64"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"* When we look at the data ,it shows that both the test and train dataset does not have any missing values"},{"metadata":{},"cell_type":"markdown","source":""},{"metadata":{},"cell_type":"markdown","source":"## Then in column of class we check and find out,\n* How is the data divied into.\n* Here the unique function does that."},{"metadata":{"trusted":true},"cell_type":"code","source":"Train['CLASS'].unique()","execution_count":44,"outputs":[{"output_type":"execute_result","execution_count":44,"data":{"text/plain":"array([1, 0])"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"# Descriptive statistics of the data\n* Generate descriptive statistics that summarize the central tendency,\ndispersion and shape of a dataset's distribution, excluding\n``NaN`` values.\n\nAnalyzes both numeric and object series, as well\nas ``DataFrame`` column sets of mixed data types. The output\nwill vary depending on what is provided.\n\n### For example this function will provide the following summary\n* Count.\n* Mean.\n* Standard Deviation.\n* Minimum Value.\n* 25th Percentile.\n* 75th Percentile(Median).\n* Maximum Value.\n"},{"metadata":{"trusted":true},"cell_type":"code","source":"Train.describe()","execution_count":45,"outputs":[{"output_type":"execute_result","execution_count":45,"data":{"text/plain":" FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\ncount 3038.000000 3038.000000 3038.000000 3038.000000 \nmean 2.060237 8.521520 0.971410 73.668760 \nstd 3.819929 7.586652 0.107413 8.527489 \nmin -16.000000 0.000000 0.684000 42.750000 \n25% 0.000000 2.516000 0.895000 68.294000 \n50% 2.000000 7.143000 0.963000 74.059500 \n75% 4.000000 13.158000 1.041000 79.343750 \nmax 30.000000 46.667000 1.451000 101.682000 \n\n FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\ncount 3038.000000 3038.000000 3038.000000 3038.000000 \nmean 0.994007 -2.432927 0.088545 15.683233 \nstd 0.031333 1.707223 0.284133 11.575665 \nmin 0.866000 -10.432000 0.000000 0.041000 \n25% 0.974000 -3.606000 0.000000 5.587500 \n50% 0.994000 -2.296500 0.000000 14.988500 \n75% 1.011000 -1.283250 0.000000 26.807750 \nmax 1.196000 3.576000 1.000000 51.280000 \n\n AS_DAYM780201 AS_FUKS010112 CT_RACS820104 CLASS \ncount 3038.000000 3038.000000 3038.000000 3038.000000 \nmean 73.650828 5.911361 1.235255 0.500000 \nstd 9.166092 0.693689 0.210012 0.500082 \nmin 42.778000 3.533000 0.785000 0.000000 \n25% 67.556000 5.459250 1.082000 0.000000 \n50% 73.697000 5.925500 1.184000 0.500000 \n75% 79.778000 6.382000 1.351000 1.000000 \nmax 103.167000 8.662000 2.192000 1.000000 ","text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201FULL_GEOR030101FULL_OOBM850104NT_EFC195AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CT_RACS820104CLASS
count3038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.000000
mean2.0602378.5215200.97141073.6687600.994007-2.4329270.08854515.68323373.6508285.9113611.2352550.500000
std3.8199297.5866520.1074138.5274890.0313331.7072230.28413311.5756659.1660920.6936890.2100120.500082
min-16.0000000.0000000.68400042.7500000.866000-10.4320000.0000000.04100042.7780003.5330000.7850000.000000
25%0.0000002.5160000.89500068.2940000.974000-3.6060000.0000005.58750067.5560005.4592501.0820000.000000
50%2.0000007.1430000.96300074.0595000.994000-2.2965000.00000014.98850073.6970005.9255001.1840000.500000
75%4.00000013.1580001.04100079.3437501.011000-1.2832500.00000026.80775079.7780006.3820001.3510001.000000
max30.00000046.6670001.451000101.6820001.1960003.5760001.00000051.280000103.1670008.6620002.1920001.000000
\n
"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"## Class Distribution\n\nA groupby operation involves some combination of splitting the\nobject, applying a function, and combining the results. This can be\nused to group large amounts of data and compute operations on these\ngroups."},{"metadata":{"trusted":true},"cell_type":"code","source":"Train.groupby('CLASS').size().plot(kind='bar')","execution_count":46,"outputs":[{"output_type":"execute_result","execution_count":46,"data":{"text/plain":""},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
","image/png":"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Correlations Between Attributes\nIs the a mutual relationship or connection between two or more things.\n\nNote: Correlation refers to the relationship between two variables and how they may or may notchange together. The most common method for calculating correlation is Pearson's Correlation Coefficient, that assumes a normal distribution of the attributes involved.\n\nA correlation of -1 or 1 shows a full negative or positive correlation respectively. Whereas a value of 0 shows no correlation at all. "},{"metadata":{"trusted":true},"cell_type":"code","source":"Train.corr(method='pearson')","execution_count":47,"outputs":[{"output_type":"execute_result","execution_count":47,"data":{"text/plain":" FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 \\\nFULL_Charge 1.000000 -0.612996 -0.490977 \nFULL_AcidicMolPerc -0.612996 1.000000 0.794796 \nFULL_AURR980107 -0.490977 0.794796 1.000000 \nFULL_DAYM780201 -0.434603 0.541481 0.548253 \nFULL_GEOR030101 -0.058725 0.115201 0.346139 \nFULL_OOBM850104 -0.283758 0.513344 0.462712 \nNT_EFC195 0.088068 -0.143168 -0.169540 \nAS_MeanAmphiMoment 0.355477 -0.431590 -0.426097 \nAS_DAYM780201 -0.365374 0.449621 0.456260 \nAS_FUKS010112 -0.090570 0.002334 0.032958 \nCT_RACS820104 0.232929 -0.213543 -0.403599 \nCLASS 0.534602 -0.598816 -0.584111 \n\n FULL_DAYM780201 FULL_GEOR030101 FULL_OOBM850104 \\\nFULL_Charge -0.434603 -0.058725 -0.283758 \nFULL_AcidicMolPerc 0.541481 0.115201 0.513344 \nFULL_AURR980107 0.548253 0.346139 0.462712 \nFULL_DAYM780201 1.000000 0.010118 0.334778 \nFULL_GEOR030101 0.010118 1.000000 0.319157 \nFULL_OOBM850104 0.334778 0.319157 1.000000 \nNT_EFC195 -0.090058 -0.230417 -0.230561 \nAS_MeanAmphiMoment -0.408793 -0.160269 -0.336297 \nAS_DAYM780201 0.894191 -0.029085 0.275640 \nAS_FUKS010112 0.055915 0.040480 -0.452769 \nCT_RACS820104 -0.326792 -0.151935 0.155304 \nCLASS -0.554838 -0.260470 -0.453287 \n\n NT_EFC195 AS_MeanAmphiMoment AS_DAYM780201 \\\nFULL_Charge 0.088068 0.355477 -0.365374 \nFULL_AcidicMolPerc -0.143168 -0.431590 0.449621 \nFULL_AURR980107 -0.169540 -0.426097 0.456260 \nFULL_DAYM780201 -0.090058 -0.408793 0.894191 \nFULL_GEOR030101 -0.230417 -0.160269 -0.029085 \nFULL_OOBM850104 -0.230561 -0.336297 0.275640 \nNT_EFC195 1.000000 0.178683 -0.036844 \nAS_MeanAmphiMoment 0.178683 1.000000 -0.322378 \nAS_DAYM780201 -0.036844 -0.322378 1.000000 \nAS_FUKS010112 0.145924 0.025580 0.045562 \nCT_RACS820104 0.080898 0.171524 -0.256060 \nCLASS 0.260702 0.693552 -0.437168 \n\n AS_FUKS010112 CT_RACS820104 CLASS \nFULL_Charge -0.090570 0.232929 0.534602 \nFULL_AcidicMolPerc 0.002334 -0.213543 -0.598816 \nFULL_AURR980107 0.032958 -0.403599 -0.584111 \nFULL_DAYM780201 0.055915 -0.326792 -0.554838 \nFULL_GEOR030101 0.040480 -0.151935 -0.260470 \nFULL_OOBM850104 -0.452769 0.155304 -0.453287 \nNT_EFC195 0.145924 0.080898 0.260702 \nAS_MeanAmphiMoment 0.025580 0.171524 0.693552 \nAS_DAYM780201 0.045562 -0.256060 -0.437168 \nAS_FUKS010112 1.000000 -0.445284 0.033432 \nCT_RACS820104 -0.445284 1.000000 0.267652 \nCLASS 0.033432 0.267652 1.000000 ","text/html":"
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FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201FULL_GEOR030101FULL_OOBM850104NT_EFC195AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CT_RACS820104CLASS
FULL_Charge1.000000-0.612996-0.490977-0.434603-0.058725-0.2837580.0880680.355477-0.365374-0.0905700.2329290.534602
FULL_AcidicMolPerc-0.6129961.0000000.7947960.5414810.1152010.513344-0.143168-0.4315900.4496210.002334-0.213543-0.598816
FULL_AURR980107-0.4909770.7947961.0000000.5482530.3461390.462712-0.169540-0.4260970.4562600.032958-0.403599-0.584111
FULL_DAYM780201-0.4346030.5414810.5482531.0000000.0101180.334778-0.090058-0.4087930.8941910.055915-0.326792-0.554838
FULL_GEOR030101-0.0587250.1152010.3461390.0101181.0000000.319157-0.230417-0.160269-0.0290850.040480-0.151935-0.260470
FULL_OOBM850104-0.2837580.5133440.4627120.3347780.3191571.000000-0.230561-0.3362970.275640-0.4527690.155304-0.453287
NT_EFC1950.088068-0.143168-0.169540-0.090058-0.230417-0.2305611.0000000.178683-0.0368440.1459240.0808980.260702
AS_MeanAmphiMoment0.355477-0.431590-0.426097-0.408793-0.160269-0.3362970.1786831.000000-0.3223780.0255800.1715240.693552
AS_DAYM780201-0.3653740.4496210.4562600.894191-0.0290850.275640-0.036844-0.3223781.0000000.045562-0.256060-0.437168
AS_FUKS010112-0.0905700.0023340.0329580.0559150.040480-0.4527690.1459240.0255800.0455621.000000-0.4452840.033432
CT_RACS8201040.232929-0.213543-0.403599-0.326792-0.1519350.1553040.0808980.171524-0.256060-0.4452841.0000000.267652
CLASS0.534602-0.598816-0.584111-0.554838-0.260470-0.4532870.2607020.693552-0.4371680.0334320.2676521.000000
\n
"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"## Plotting to show the correlation\n\nplot a heat map to show us the correlation of the data.\n\nWith the help of ; seaborn\nthe we can use spearman or pearson method.\n"},{"metadata":{"trusted":true},"cell_type":"code","source":"import seaborn as sns","execution_count":48,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#The first step is to choose the figure size then use the heatmap to plot.\nplt.figure(figsize=(7,7))\nsns.heatmap(Train.corr(method='pearson'))","execution_count":49,"outputs":[{"output_type":"execute_result","execution_count":49,"data":{"text/plain":""},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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esB/YAPAkTEq5L+GbgBaAd+Sza6UOnH+Ii4WNKHgZ9L2g1QJ32ox8eB39SaaoiIccA4gG2H7N68f1vNzJpJE68laJTeHkko8gqwUVXZEODlnjac5vY/BZwjaQHwn8CRktbvYtyvA+8nW09wTVXdzwHbA/8DXFYpjIjbImLfiPgw8ATwVNp1IjAx1XkAWAfYhGzkYJtcu1vz7lRELYskbZHOcQvgpar9o/BUg5mZdVMzJgnTgf0lbQ6QrmoYyMpD8PU6BHgsIraJiKERsR3ZEPzREfEmsLCysDBdBXAE2QLHFSKiHfgxsFb+yoO07x2yBGI/SR9I7Wya/twI+CJwZar+HFCJ9QGyJOFPwCRglKSBkrYHhgEPd3Jek4AT0usTgFsrOyRtAPxtvszMzBrACxfLFxGLgNOByZJmAj8CRqcv54pZktrS9h+pbGyurE3S1gXNjwaq1z7cBHw2vT4eODvF/T/gO2ntQnUfA/ge8I2CfUuAi4EzUtGPJc0DfgNcEBFPpvKvASdLeozsV/7YyMwlG2GYB9wBnBoRywEkXU+2MHKndI4nprYuAA6V9BRwaHpfcQxwZ0T8peDzMDOzerVH47Ym1atrEiJicI3yW6nxyzcihtZobnwX4o0tKJtE9kuciJgHHNSVYyPiJtJCwIg4sGrfxbnXhZdZplj719h3PnB+QXmttl4hjUoU7BtPFz4bMzOzar29cNHMzGzN1AILF/tskiDpIbK1DHljImJ2b/THzMz6GCcJa66I2Le3+2BmZn1YCzwFsukWLpqZmVlz6LMjCWZmZquVpxvMzMysUBNfutgonm4wMzNbA0g6QtITkuZLOrNGnc9ImidprqT/6WlMjySYmZnVo8Q7JabHClxGdsO8NmC6pEnpnjuVOsOAs4D907ODNi1ureucJJiZmdWj3OmGfYD5EfEMgKQJwEiyu/NWnAxcFhGvAkRE9XN8us1Jgq1k/QHrlhJn+dS7SonTfs/UUuKs/ZULS4lz2zXnlBLn75a9UEqcTaKcf4IGqF8pcdb5euEIcMMNvHN8KXGG9F+vlDgD+w8oJU4zk3QKcEquaFx6Qm/FVqz8DKM2oPpS/x1TW78heyLxuRFxR0/65STBzMysDtHAqxtSQjCugyoqOqzqfX+yhwIeSPYE4fsk7RYRr9XbLycJZmZm9Sh3uqEN2Cb3fmvgxYI6D6YnEj8r6QmypGF6vUF9dYOZmVnzmw4Mk7S9pLWBUaSHE+b8kvSQQkmbkE0/PNOToB5JMDMzq0eJVzdExDJJpwFTyNYbXBURcyWdB8xITzSeAhwmaR6wHPh6ekpw3ZwkmJmZ1aPkmylFxGRgclXZObnXAXw1bQ3h6QYzMzMr5JEEMzOzevjZDWZmZlbIz24wMzOzVuWRBDMzs3qUeHVDb3GSYGZmVg9PN5iZmVmr8kiCmZlZHRr57IZm1WsjCZKWS5qZ24ZKGivp0qp60ySNSK8XpFtN5vevckwHMRdImp22eZK+J2lgVZ2vSPqrpA3S+00lPStp81ydyyWdKelASSHpxNy+vVLZGen9DblzXCBpZiofIOma1JfHJZ2Va+MISU9Imi/pzFz5dal8jqSrJA1I5ZJ0Sao/S9IHc8fcIek1Sb/qymdkZmZd1B6N25pUb043LImI4bltQUlxD4qI3cmezf0+Vn3q1miye2QfAyuex30h8AOA9AX8EeDiVH82cFzu+FHAY5U3EXFc5RyBm4Cb065PAwNTX/YGvpASpX7AZcCRwC7AaEm7pGOuA3YGdgcGASel8iPJHuIxjOxRoz/J9ef7wJiufjhmZmYVLbsmISLeBP4JOFrSEABJOwCDgbPJkoWKccAOkg4CLgVOS0/ZAngOWEfSZpIEHAHcXh0v7fsMcH2lC8B6kvqTfeG/DbxBlrzMj4hnIuJtYAIwMvV5ciTAw2RPASPtvzbtehDYUNIW6ZipwJ87+iwknSJphqQZry55qfMPz8zMPJKwmg3KDcPf0hsdiIg3gGfJfoFDlhhcD9wH7CRp01SvHfhnspGAJyPi3qqmbiQbGfgb4BFgaUG4A4BFEfFU7pi/AAvJEo0fRMRiYCvg+dxxbalshTTNMAa4IxV1ekxHImJcRIyIiBEbDdq0q4eZmbW2aG/c1qR6c+HikjQEn1crnVqdaZZyr0cBx0REu6Sbyb74LwOIiJmS5gCXF7QxEbiBbCrgerJkoVolAanYh+wpXVsCGwH3Sbq7qj8V1ed/OXBvRNxXcA61jjEzM+uWZru64RWyL8y8IcDLqyOYpPWBocCTkvYgG1G4K5sZYG2y53BfljukPW0riYg/SnoHOBQ4naokIU0pfJJs7UHFZ4E70rTFS5J+A4wgGxHYJldva+DFXFvfBt4LfCFXp62jY8zMbDVo4mmCRmm2NQnTgf0rVxKkqxoGsvJQekNIGkz2i/yXEfEq2S/9cyNiaNq2BLaStF0XmzwH+GZELC/Ydwjw+4hoy5U9B3wsXZmwHrAf8Huyz2CYpO0lrU02ujEp9fkk4HBgdJoCqZgEHJ/a2g94PSIWdrHfZmZWh2iPhm3NqqlGEiJikaTTgcmS1gLeZNUvxFmSKu8nArOAsZKOztXZr+oLOe+etIhwLeAW4LupfBTZVQJ5t6TyC7vQ9992sHsUK081QDZCcTUwh2y64OqImAUg6TRgCtAPuCoi5qZjrgD+ADyQRjtujojzyJ4vfhQwH3gL+IdKEEn3kU2DDJbUBpwYEVM6Ox8zM7NeSxIiYnCN8luBW2vsG1qjufFdjFnreCJi+4Kyr1a9P7Dq/TRgWsFx51a9H1tQ502yNQ9FfZlM9sVfXV743ytd7XBqjX0HFJWbmVkPNfEIQKM01UiCmZnZGqMF7rjYJ5MESQ+RrWXIGxMRs3ujP2ZmZmuiPpkkRMS+vd0HMzPr4zzdYGZmZoVaIElotksgzczMrEl4JMHMzKwO2YVlfZuTBDMzs3p4usHMzMxalUcSzMzM6tECIwlOEmwlY9YZ1nmlBrj/qmWlxBm+0x9LiXPbNeeUEmfszPNKifPHI08uJc58lpQS54B1ti4lzhVHXVNKnI1V9ODXxtu9X/Xz9laPDTfetZQ4jdbMz1xoFE83mJmZWSGPJJiZmdWjBUYSnCSYmZnVo+8/usHTDWZmZlbMIwlmZmZ1aIWFi04SzMzM6tECSYKnG8zMzKyQRxLMzMzq0QILF50kmJmZ1aEV1iR4usHMzMwKeSTBzMysHi0w3eCRBDMzszpEezRs6wpJR0h6QtJ8SWd2UO9YSSFpRE/P0UmCmZlZk5PUD7gMOBLYBRgtaZeCeusDXwYeakTcXk0SJC2XNDO3DZU0VtKlVfWmVTIiSQskbVK1f5VjOog5WNJPJD0t6VFJv5N0cto3VNKSqj4dn/ZtIOnadNzT6fUGBcfNS/sG5GKelTK/JyQdnsrWkfSwpMckzZX0nVz97SU9JOkpSTdIWjuVf1TSI5KWSTq26rxOSPWfknRCrvx8Sc9LerMrn4+ZmXVRewO3zu0DzI+IZyLibWACMLKg3neBi4C/1nlWK+ntkYQlETE8ty0oIeaVwKvAsIjYCzgCGJLb/3RVn65N5T8DnomIHSJiB+DZ1NZKxwG7A1sDnwFImd4oYNcU6/KUES4FPhYRewLDgSMk7ZfauhD4YUQMS309MZU/B4wF/id/QpKGAN8G9iX7i/RtSZVnvN6WyszMrIGivXGbpFMkzchtp1SF2wp4Pve+LZWtIGkvYJuI+FWjzrG3k4RSSdqB7Avz7IhoB4iIP0XEhZ0c935gb7IMreI8YERqc4WIWA48zLv/8UYCEyJiaUQ8C8wH9olM5df9gLSFJAEfA25M+64Bjk5tL4iIWayadx4O3BURiyPiVeAusoSEiHgwIhZ2cn4r/nI+/OZTHVU1M7OKBo4kRMS4iBiR28ZVRVNBD1YsZpC0FvBD4GuNO8HeTxIG5Yb1bykh3q7AY5UEoYYdqqYbDiCb/5mZEgBgRTIwM7W5gqR1yH7R35GKamZ/kvpJmgm8RPYl/xCwMfBaRCyrrt+BTjPMjuT/cu4zeFhXDzMzs/K0Advk3m8NvJh7vz6wGzBN0gJgP2BSTxcv9vYlkEvSEH1erWWeDb9rhaRvAZ8GNo2ILVPx09V9kjSyRnzlyndIX/jDgBvTL/5KnWoBKxKN4ZI2BG6RtBuwqFb9jk6ljmPMzKwHOvy52XjTgWGStgdeIJvG/uyKvkS8DqxYrydpGnBGRMzoSdDeHkko8gqwUVXZEODlBrQ9D9gzDcsQEeenhOA9nRw3F9irchysGNrZE3g8FVWSi/cD+0n6RCrvLPsjIl4DppFNEbwMbCipf636BTqNYWZmDVbiwsU0unwaMIXse2diRMyVdF7u+6bhmjFJmA7sL2lzgDRUMpCVh9PrEhHzgRnA99Liwcr0QNEv8erjHgXOzhWfDTyS9uXrLgTOBM5KRZOAUZIGpgxwGPCwpPemEQQkDQIOAX4fEQHcA1SuXjgBuLWTU5sCHCZpo7Rg8bBUZmZmfURETI6IHdMC+vNT2TkRMamg7oE9HUWAJkwSImIRcDowOQ3f/wgYXbWOYJaktrT9Ryobmytrk7R1jRAnkc37z5f0O+Bu4Ju5/dVrEr6cyk8EdkyXMj4N7Mi7Vx1U+yWwrqQDImIuMJFsFOMO4NQ0zbAFcI+kWWSJ0V25FanfBL4qaX7q688AJH1IUhvZFMl/SZqbPrPFZIsqp6ftvFSGpIvSMeumz+XcGn02M7NuaOTVDc2qV9ckRMTgGuW3UuPXc0QMrdHc+C7GfAP4Qo19C4BBNfa9Cny+g+N2y70PsqmIyvvzgfOrjpkF7FWjvWcouGwxIqaTTSUUHXMVcFVB+TeAbxQdY2Zm9WvmL/dGabqRBDMzM2sOvX11w2oj6SGytQx5YyJidm/0x8zM+pZWGEnos0lCROzb230wM7M+LDpc894neLrBzMzMCvXZkQQzM7PVydMNZmZmVijaPd1gZmZmLcojCWZmZnXwdIO1nAfitVLinDq6nGG69tfL+Sv+d8teKCXOH488uZQ4m9/+01LisPcZpYSZvWxxKXFO37CcwdkjF71SSpwr27cvJc5Jy9fMR82Er24wMzOzVuWRBDMzszp4usHMzMwK+eoGMzMza1keSTAzM6tDRG/3YPVzkmBmZlYHTzeYmZlZy/JIgpmZWR1aYSTBSYKZmVkdWmFNgqcbzMzMrJBHEszMzOrg6QYzMzMr5Gc3mJmZWcvySIKZmVkdWuHZDaWPJEhaLmlmbhsqaaykS6vqTZM0Ir1eIGmTqv2rHNNBzA0kXSvp6bRdK2mD3P5dJf2fpCclPSXp3yQpF+dPqa9zJd0oad2071xJIen9uba+ksoqfR8tabakWZLuqJxHOvaF3OdwVK6NsyTNl/SEpMNz5VdJeknSnKrzGyLprtT3uyRtVLX/Q+lzP7Yrn5eZmXWuPdSwrVn1xnTDkogYntsWlBDzZ8AzEbFDROwAPAtcCSBpEDAJuCAidgT2BP4G+GLu+BtSX3cF3gaOy+2bDYzKvT8WmJfa7g/8GDgoIvYAZgGn5er+MPc5TE7H7JLa2xU4ArhcUr9Uf3wqq3YmMDUihgFT03tSe/2AC4EpnX5KZmZmOX1+TUL6lb838N1c8XnACEk7AJ8FfhMRdwJExFtkX+RnFrTVH1gPeDVX/EtgZNr/PuB14E+VQ9K2XhqZeA/wYiddHglMiIilEfEsMB/YJ/XtXmBxjWOuSa+vAY7O7fsScBPwUq2Akk6RNEPSjAVvPtdJ98zMDLKFi43amlVvJAmDckPst5QQbxdgZkQsrxSk1zPJfq3vCvwuf0BEPA0MlvSeVHScpJnAC8AQ4LZc9TeA5yXtBowGbsi18w7wz2SjDS+mvvwsd+xpaRriqtwUwVbA87k6bamsI5tFxMIUcyGwKYCkrYBjgCs6OjgixkXEiIgYMXTwtp2EMjMzyC6BbNTWrHp7uuGYVFbrvlWNuJ+VarRTKa+1Px//hogYDmxO9oX/9ap6E8imCI4GViQ+kgaQJQl7AVuSTTeclXb/BNgBGA4sBC7O9atWP7rrR8A38wmSmZlZVzXLdMMrwEZVZUOAlxvQ9lxgL0krzjW93hN4PO0fkT8gTRu8GRF/zpdHRJBjB3uNAAAgAElEQVSNIny0KsZtwBjguYh4I1c+PB33dDp2Itl6ByJiUUQsj4h24KekKQWykYNtcm1sTedTFIskbZH6vgXvTi2MACZIWkC2VuJySUcXN2FmZt0R0bitWTVLkjAd2F/S5gDpyoCBrDzsXpeImA88CpydKz4beCTtuw74iKRDUuxBwCXARTWa/AjwdFWMJcA3gfOr6r4A7CLpven9oWSJSeXLvOIYoHLFwiRglKSBkrYHhgEPd3Kak4AT0usTgFtTv7aPiKERMRS4EfhiRPyyk7bMzKwLWmG6oSnukxARiySdDkxOv/LfBEanX9kVsyRV3k8kG7ofW/XLeL+IaCsIcSLwn5Lmkw3nP5DKiIglkkam/ZcB/YCfA/nLK4+T9BGypKoNGFtwDhMKyl6U9B3gXknvAH/IHXuRpOFkUwkLgC+kY+ZKmkh2hcQy4NTKdIGk64EDgU0ktQHfjoifARcAEyWdCDwHfLrgMzAzM+uW0pOEiBhco/xW0i/ggn1DazQ3vosxXwU+38H+2WRfvkX7xteKExHn1ig/MPf6CgoWDkbEmA76cz6rjkoQEaNr1H8FOLhWe6nO2I72m5lZ9zTz/Q0apSlGEszMzNY0zXzpYqP0qSRB0kNkaxnyxqSRAjMzM+uGPpUkRMS+vd0HMzNrDc18VUKj9KkkwczMrCytsCahWS6BNDMzsw5IOiI9+G++pKJHB3xV0rx0J9+pkrbraUwnCWZmZnUo89kN6WF9lwFHkt3if3R6IGDeo8CI9EDBG6l9v58uc5JgZmZWh5LvuLgPMD8inomIt8keBzBy5f7EPekhhQAPkt2xt0ecJJiZmfWy/NN403ZKVZXuPvzvROD2nvbLCxdtJf/49ns6r9QA3/5le+eVGuBt1i0lziZRzv+V5rOklDjsfUYpYa7+3Q9KifO7Pco5n0lvlPP3bdxa5fz/dDEDSolz28bv7bxSE2rkwsWIGAeM66BKlx/+J+nzZM/u+due9stJgpmZWR1KvplSlx7+l55D9C3gbyNiaU+DerrBzMys+U0HhknaXtLawCiyh/utIGkv4L+AT0TESwVtdJtHEszMzOpQ5n0SImKZpNOAKWQPIrwqPRDwPGBGREwCvg8MBn4hCeC5iPhET+I6STAzM6tD2TdcjIjJwOSqsnNyrw9pdEwnCWZmZnXwHRfNzMysZXkkwczMrA5+VLSZmZkVKuduL73L0w1mZmZWyCMJZmZmdYjCmyD2LU4SzMzM6tBe9jWQvcDTDWZmZlbIIwlmZmZ1aG+B6QaPJNQgKSRdnHt/hqRzJX1L0sy0Lc+9/nKNds6V9EKu3kxJG0o6UNLrubK7c8ccL2mOpLmS5kk6I5V/OpW1SxqRq7+2pKslzZb0mKQDc/umSXoiF2fT1fKBmZm1mEAN25qVRxJqWwp8UtK/R8TLlcKIOB84H0DSmxExvAtt/TAiVnombrqv9n0R8fdV5UcC/wIcFhEvSloHGJN2zwE+SfYAj7yTU992T0nA7ZI+FBGVK3Q+FxEzutBPMzOzFTySUNsysmd7f6XkuGcBZ0TEiwAR8deI+Gl6/XhEPFFwzC7A1FTnJeA1smeJd4mkUyTNkDRjylvze3wCZmatoL2BW7NyktCxy4DPSdqgh+18JTfcf0+u/IBc+bdS2W7A77rZ/mPASEn9JW0P7M3Kzx2/OsX4N6UhjLyIGBcRIyJixOHrvr+boc3MWpOnG1pcRLwh6Vrgy8CSHjS1ynRDssp0Q52uAj4AzAD+APyWbCQEsqmGFyStD9xENnVxbQNimplZH+eRhM79CDgRWK+keHPJRgK6LCKWRcRXImJ4RIwENgSeSvteSH/+GfgfYJ8G99fMrCV5usGIiMXARLJEoQz/DlwkaXMASQNrXTlRIWldSeul14cCyyJiXpp+2CSVDwD+nmzxo5mZ9VArJAmebuiai4HTenD8VyR9Pvf+6FoVI2KypM2Au9P6gSCbTkDSMcB/Au8F/lfSzIg4HNgUmCKpHXiBd6+GGJjKBwD9gLuBn/bgPMzMrIU4SaghIgbnXi8C1u2oTgftnAucW7BrATCtxjFXA1cXlN8C3FJQvgDYqaD8L3Rz6sLMzLqmmRccNoqTBDMzszq09/0cwUlCo6RLGD9dVfyLdPMlMzOzNY6ThAbJ34nRzMz6vlZ4doOTBDMzszq0wJOifQmkmZmZFfNIgpmZWR2a+f4GjeIkwczMrA7tqz4Kp8/xdIOZmZkV8kiCmZlZHVph4aKTBFvJfju/WEqcf328Jw/V7DqVdInSAPUrJc4B62xdSpzZyxaXEud3e5xRSpy9ZxU9hLXxztnri6XE2aj/JqXE2bG9nP+fbvuvw0uJ02itsCbB0w1mZmZWyCMJZmZmdfBtmc3MzKxQK9xx0dMNZmZmVsgjCWZmZnXw1Q1mZmZWqBXWJHi6wczMzAp5JMHMzKwOrXCfBCcJZmZmdWiFNQmebjAzM7NCThLMzMzq0K7GbV0h6QhJT0iaL+nMgv0DJd2Q9j8kaWhPz9FJgpmZWR3aG7h1RlI/4DLgSGAXYLSkXaqqnQi8GhHvB34IXNiD0wOcJJiZma0J9gHmR8QzEfE2MAEYWVVnJHBNen0jcLCkHl2o2aUkQdIxkkLSzun9WpIukTRH0mxJ0yVt38HxCyTdV1U2U9KcnnS+g3j9Jb0s6d8b3O6bNcr/SdLx6fV4SW9JWj+3/8fp8yvn0W2r9u9feyOumVlf1siRBEmnSJqR206pCrcV8HzufVsqK6wTEcuA14GNe3KOXR1JGA3cD4xK748DtgT2iIjdgWOA1zppY31J2wBI+kAdfe2Ow4AngM/0NIvqioi4IiKuzRXNJ2V4ktYCDgJeWN396ICTBDOzBgs1cIsYFxEjctu4qnBF32XVF1h0pU63dJokSBoM7E8211FJErYAFkZEO0BEtEXEq500NZEsuYAs6bg+F6OfpO+nEYlZkr5QiS1pqqRH0ohF5Yt3qKTHJf1U0lxJd0oalIs1Gvgx8BywXy7OAkn/T9IDKVP7oKQpkp6W9E+pzoGS7pV0i6R5kq5IX/SVNs6X9JikByVtlsrOlXRGLv71uXM9EPgNsCzXxlfTKMwcSf+SO6ffS7oylV8n6RBJv5H0lKR9Ur31JF2VPqtHc5/JWEk3S7oj1b8olV8ADEojN9cV/YfJZ7A/f/HFTv4zmplZL2gDtsm93xqo/gd7RR1J/YENgMU9CdqVkYSjgTsi4klgsaQPkn3hfzx98Vwsaa8utHMj8Mn0+uPAbbl9JwKvR8SHgA8BJ6fpi78Cx0TEB8l+jV+cGxkYBlwWEbuSjWJ8CiAlCwcDvyL7sh5d1Y/nI+LDwH3AeOBYskTivFydfYCvAbsDO+T6vR7wYETsCdwLnFzjXJ8C3itpoxR/QmWHpL2BfwD2TXFPzn1+7ydLbvYAdgY+C3wEOIN3RwO+Bfxf+qwOAr4vab20bzhZcrI7cJykbSLiTGBJRAyPiM8VdTafwY7Zcssap2RmZnllLlwEpgPDJG0vaW2yH+2TqupMAk5Ir48l+65YvSMJrPwlNwEYHRFtwE7AWWTnN1XSwZ20sxh4VdIo4HHgrdy+w4DjJc0EHiKbQxlGNnTy/yTNAu4mm2/ZLB3zbETMTK9/BwxNr/8euCci3gJuAo5Jq0IrKh/qbOChiPhzRPwJ+KukDdO+h9PikOVkicZHUvnbZMlHdcwiN5P9R9yXLCGp+AhwS0T8JSLeTPUOyJ3T7DRCMxeYmv4Dz87FOgw4M31W04B1gG3TvqkR8XpE/BWYB2zXQf/MzKwHykwS0hqD04ApZN+hEyNirqTzJH0iVfsZsLGk+cBXgVUuk+yuDu+4KGlj4GPAbpIC6AeEpG9ExFLgduB2SYvIRhymdhLvBrJLOMZWhwK+FBFTquKPBd4L7B0R70haQPalCLA0V3U5UJluGA3sn+pClnAcRJZk5I9rr2qjnXc/j+rMq/L+nVxWtpyOP78JwCPANRHRnlsa0dEaier+5PtaiSXgUxHxRP5ASfuy6mfiO2qamfURETEZmFxVdk7u9V+BTzcyZmcjCccC10bEdhExNCK2AZ4FPippS1ixMG8P4A9diHcLcBFZJpQ3BfhnSQNSmzumIfQNgJdSgnAQnfwylvQesl/q26b+DgVOZdUph87sk4Z01iIbvr+/m8cTEc+RTQ1cXrXrXuBoSeumczyGlUcaOjMF+FJl2qWLUz3vVD5bMzNrjGjg1qw6+6U5Grigquwmsrn8xZIGprKHgUs7CxYRfybd3KHqooMryYbTH0lffn8iG5m4DrhN0gxgJvD7TkJ8kmwOJv+L+lbgolxfu+IBsvPenexL/ZZuHLtCRPxXQdkjksaTfWYAV0bEo+r6nbG+C/wImJU+qwVkUywdGZfqP1JrXYKZmXVPKzwqWj1c09DnSDoQOCMiOvvi7ZMWHXhgKX8hPvb4kjLCoA5ndxpnwErLXlafA9bZupQ4s5f1aEF0l/17+/qdV2qAvWf9oJQ4f7fXF0uJ89n2cm65smN7Of8/3evCHUuJAzDo+H9v2D8KP9728w379/L05/67KVMOz1mbmZnVwY+K7iZJDwHVw/pjImJ2I+OsThExjeyqATMzs5qcJHRTROzbyPbMzMys93i6wczMrA6tsKLPSYKZmVkdWuHqBicJZmZmdWiFNQldfQqkmZmZtRiPJJiZmdXBaxKs5XzyqXIGl3572OBS4pQ1VrbO13v8HJUuueKoa0qJc/qG5Xxwk95Yt5Q455R0k6P/fbT6Luyrx8Q9zum8UgP8cO1lnVdqgDlndPbYn8Z5/PjGtdXeAmmCpxvMzMyskEcSzMzM6tAKCxedJJiZmdWh7082eLrBzMzMavBIgpmZWR083WBmZmaFWuGOi55uMDMzs0IeSTAzM6tDK9wnwUmCmZlZHfp+iuDpBjMzM6vBIwlmZmZ18NUNZmZmVqgV1iR4usHMzMwKeSTBzMysDn1/HGENGkmQdIykkLRzer+WpEskzZE0W9J0Sdt3cPyCVG+2pHmSvidpYFWdr0j6q6QN0vtNJT0rafNcncslnSnpwNSfE3P79kplZ6T3N0iambYFkmam8gGSrkl9eVzSWbk2jpD0hKT5ks7MlV+XyudIukrSgFSu9DnMlzRL0gdzx9wh6TVJv6r/kzczsyLtDdya1RqTJACjgfuBUen9ccCWwB4RsTtwDPBaJ20clOruA7wPGFcQY3pqi4h4CbgQ+AFA+gL+CHBxqj879aNiFPBY5U1EHBcRwyNiOHATcHPa9WlgYOrL3sAXJA2V1A+4DDgS2AUYLWmXdMx1wM7A7sAg4KRUfiQwLG2nAD/J9ef7wJhOPhMzM7NCa0SSIGkwsD9wIu8mCVsACyOiHSAi2iLi1a60FxFvAv8EHC1pSIqxAzAYOJssWagYB+wg6SDgUuC0iHgn7XsOWEfSZpIEHAHcXtB/AZ8Brq90AVhPUn+yL/y3gTfIkpf5EfFMRLwNTABGpj5PjgR4GNg6tTUSuDbtehDYUNIW6ZipwJ87+zwknSJphqQZf/zLi51VNzMzsoWLjdqa1RqRJABHA3dExJPA4vSLfiLw8TSUf7GkvbrTYES8ATxL9gscssTgeuA+YCdJm6Z67cA/k40EPBkR91Y1dSPZyMDfAI8ASwvCHQAsioincsf8BVhIlmj8ICIWA1sBz+eOa0tlK6RphjHAHamo02M6ExHjImJERIzYfL0tu3OomVnLigZuzWpNSRJGk/2qJv05OiLagJ2As8imdKZKOrib7eYfzzEKmJCSgpvJvvgBiIiZwBzg8oI2Jqa6lSSjVv/z+/YBlpNNl2wPfE3S+6r6syJ81fvLgXsj4r6Cc6h1jJmZWbc1/dUNkjYGPgbsJimAfkBI+kZELCUb3r9d0iKyEYepXWx3fWAo8KSkPchGFO7KZgZYG3iGbH1AReH6koj4o6R3gEOB08lGFPJx+gOfJFt7UPFZspGRd4CXJP0GGEE2IrBNrt7WwIu5tr4NvBf4Qq5OW0fHmJnZ6tHMCw4bZU0YSTiWbM59u4gYGhHbkE0TfFTSlpBd6QDsAfyhKw2mNQ6XA79M6xhGA+em9odGxJbAVpK262IfzwG+GRHLC/YdAvw+jXxUPAd8LF2ZsB6wH/B7skWTwyRtL2ltstGNSanPJwGHk42i5P9uTgKOT23tB7weEQu72G8zM6tTNPB/zarpRxLIvsAvqCq7CRhPtj6hchnjw2QLCztyT1pEuBZwC/DdVD6K7CqBvFtS+YWddTAiftvB7lGsOg1xGXA12RSGgKsjYhaApNOAKWQjJldFxNx0zBVkSdADabTj5og4D5gMHAXMB94C/qESRNJ9ZFdEDJbUBpwYEVM6Ox8zMzNYA5KEiDiwoOwS4JJutjO0g32r3F8hIr7aUT8iYhowreC4c6vejy2o8ya5NQ9V+yaTffFXlxf+t0pXO5xaY98BReVmZtZzrTDd0PRJgpmZWTNq5ksXG6XPJQmSHgIGVhWPiYjZvdEfMzOzNVWfSxIiYt/e7oOZmfV9fX8cYc24usHMzKzpNMsdFyUNkXSXpKfSnxsV1Bku6QFJc9Nzfo4raquakwQzM7M125nA1IgYRnavoDML6rwFHB8Ru5I9QuBHkjbsrGEnCWZmZnVooqdAjgSuSa+vIbux4Eoi4snKowEi4kXgJbKb83XISYKZmVkdGnkzpfyD9tJ2Sje6slnlJnrpz007qixpH7I7Cz/dWcN9buGimZnZmiYixpE9dbiQpLuBzQt2fas7cdJTgn8OnFB1995CThJsJYf236KUOBPuKXouVeMNKmn58cA7x5cSZ2OV87kdueiVUuKMW+s9pcTZqP8mpcSZuMc5pcT5zKzzSonz3V26tLatx/51wE6lxGm0Mm+mFBGH1NonaZGkLSJiYUoCXqpR7z3A/wJnR8SDXYnr6QYzM7M6NNGzGyYBJ6TXJwC3VldIzwO6hexZSL/oasNOEszMzNZsFwCHSnqK7InEFwBIGiHpylTnM8BHgbGSZqZteGcNe7rBzMysDs3y7IaIeAU4uKB8BnBSev3fwH93t20nCWZmZnVoj75/z0VPN5iZmVkhjySYmZnVoe+PIzhJMDMzq0srPCra0w1mZmZWyCMJZmZmdWjA/Q2anpMEMzOzOjTLJZCrk6cbzMzMrJBHEszMzOrQCgsXnSSYmZnVoRXWJKyR0w2SjpEUknZO79eSdImkOZJmS5ouafsOjl+Q6lXuX/03kg6U9KuqeuMlHZteT5M0Ir0eKukpSYdLWlfSdam9OZLulzQ41TtC0hOS5ks6M9fuaaksJG2SK1c6j/mSZkn6YG7fHZJeK+hjrbY+l9qYJem3kvas9/M2M7PWtKaOJIwG7gdGAecCxwFbAntERLukrYG/dNLGQRHxcuWNpAO7Eji1PQX4WkRMkXQWsCgidk/7dwLekdQPuIzsYRttwHRJkyJiHvAb4FfAtKrmjwSGpW1f4CfpT4DvA+sCX6g6plZbzwJ/GxGvSjqS7Dnl+2JmZg3hhYtNKP1K3x84kSxJANgCWBgR7QAR0RYRr66G8JsDd5I9i3tSLvYLlQoR8URELAX2AeZHxDMR8TYwARiZ6jwaEQsK2h9J9hjPSM/63jA9G5yImAr8ufqAWm1FxG9zn8GDwNb1nLCZmRWLiIZtzWqNSxKAo4E7IuJJYHEakp8IfDxNHVwsaa8utHNPqv9QN2JfC1xa9Szuq4BvSnpA0vckDUvlWwHP5+q1pbKO1HNMV5wI3F5rp6RTJM2QNON3b85vQDgzM+sL1sQkYTTZr3LSn6Mjog3YCTiLbARoqqRVHptZ5aCIGB4RlSH4WqlcvvxuYIykdVfsjJgJvI9sOmAI2bTCBwB10laReo7puEHpILIk4Zu16kTEuIgYEREj9h78/p6EMzNrGe1Ew7ZmtUatSZC0MfAxYDdJAfQDQtI30hD/7cDtkhaRjThM7UbzrwAbVZUNAV7Ovb8I+DzwC0kjI2IZQES8CdwM3CypHTgK+C2wTe7YrYEXO+lDWx3H1CRpD+BK4Mj0vHEzM2sQr0loPseSzdlvFxFDI2IbsgV6H5W0JWRXOgB7AH/oZttPAVumUQAkbQfsCcysqvcV4A3gZ+lqhP0lbZSOWRvYJcWeDgyTtH0qHwVMomOTgONTu/sBr0fEwm6eB6kv25IlLmPS1IyZmTVQNPB/zWpNSxJGA7dUld0EjAdukzQHmAUsAy7tTsNpJOLzwNWSZgI3AidFxOtV9QI4gWzB4kXADsCvJc0GHgVmADelUYbTyK6EeByYGBFzASR9WVIb2UjBLElXpuYnA88A84GfAl+sxJV0H/AL4GBJbZIO76Stc4CNgcvT2osZ3fk8zMzM1qjphog4sKDsEuCSbrYztEb5b4D9OoudrlY4LLf72hrHTCb74q8uL+xzSkBOrdHWATXKa7V1EnBS0TFmZtZzzbyWoFHWqCTBzMysWTTzpYuN0qeThHR548Cq4jERMbs3+mNmZrYm6dNJQu7yRjMzs4Zqhasb+nSSYGZmtro081UJjbKmXd1gZmZmJfFIgpmZWR18dYOZmZkVaoWrGzzdYGZmZoU8kmBmZlYHTzdYyzm23+udV2qAi1V9+4rV47Gli0qJM6T/eqXE2b1f9TPIVo8r27cvJc5iBpQSZ8f2JaXE+eHay0qJ891djislzux5N5QS59kDvth5pSbkqxvMzMysZXkkwczMrA7tLbBw0UmCmZlZHfp+iuDpBjMzM6vBIwlmZmZ18NUNZmZmVqgVkgRPN5iZmVkhjySYmZnVoRVuy+wkwczMrA6ebjAzM7OmJmmIpLskPZX+rHlrVknvkfSCpEu70raTBDMzszpEA//XQ2cCUyNiGDA1va/lu8Cvu9qwkwQzM7M6RETDth4aCVyTXl8DHF1USdLewGbAnV1t2EmCmZnZmm2ziFgIkP7ctLqCpLWAi4Gvd6fhNS5JkLS5pAmSnpY0T9I9kt6SNFPSYknPptd31zh+qKQlqc48SddKGlBV58dpzmatqvIjJc2Q9Lik30v6QSrfSdK01Objksal8gGSrpE0O5Wflcq3Sf1+XNJcSafnYhTOLUnaWdIDkpZKOqOqX0dIekLSfEmrDDNJ+k9Jb9b3iZuZWZF2omGbpFPS90tlOyUfS9LdkuYUbCO72N0vApMj4vnunOMadXWDJAG3ANdExKhUNhxYPyLukzQe+FVE3NhJU09HxHBJ/YC7gM8A16X21gKOAZ4HPgpMS+W7AZcCfxcRv5fUH6j8R7wE+GFE3Jrq7p7KPw0MjIjdJa0LzJN0PbAU+FpEPCJpfeB3ku6KiHm8O7d0QfrCPxP4JrAY+DJVw0jpHC4DDgXagOmSJqW2kDQC2LBLH7CZmXVZIy+BjIhxwLgO9h9Sa5+kRZK2iIiFkrYAXiqo9mHgAElfBAYDa0t6MyI6Wr+wxo0kHAS8ExFXVAoiYmZE3FdPYxGxHHgY2KoqxhzgJ8DoXPk3gPMj4vfp2P/f3nnHyVmVbfi6CT1ICdIhBKSoIEUi8FGkCaKCUqQEUVSKfihSRAUEUVFEARWQ8tEUUUB6U4oCIqCUAIEQAoQuTZDeW+7vj3OGTCYzu9nZM+/sZp8rv/1l5ryz537fmbPzPuecp7xj+7h8bBHSDbrW7/jaQ2B4NijmAN4CXrL9pO3b8mtfBibWnUPTvSXbT9u+BXi74TJWB+63/aDtt4Czch81A+LwfO4tqbdgz3np0Z5eGgRBEAw8LgZ2yo93Ai5qfIHtL9geaXsUsC/w+94MBBh8RsKKwK2lOpM0O7AGcHld8xjgTNKKxWZ1WxE9af8KuFrSZZL2llSbuZ8LvAo8CTwKHGH7uYZzGAWsCtyUm3rdW2pgMdKqR43HmGJwfBO4uNZfK2yfaHu07dHbzD2yF7kgCIIAym439JPDgI0lTSKtKh8GaSVZ0sn96XiwGQml+ICkccCzwKO27wSQNCvwaeBC2y+Rbtyb9NaZ7d8CHwLOAdYHbpQ0G2mW/y6wKLAU8G1JS9d+T9JcwHnAXlmvHdTslCQtStruOKbNfoMgCIIeGCghkLaftb2R7WXz/8/l9rG2d2ny+t/Z/ub09D3YjIQJwGoF+nnA9irAMsCakj6b2zcF5gHGS3oYWIcpWw49att+wvaptj8HvENaedgBuNz227afBm4ARkNyaiQZCH+0fX5dV//Je0r0sLdUz2PAEnXPFweeIK1OLAPcn69lTkn399JXEARBELzHYDMSrgZmk7RrrUHSxySt105neRl+P2D/3DQG2MX2qLxvsxSwSXY6PBw4QNJyWXcmSfvkx5vWtiUkLQzMDzxO2mLYUInhwJrAPdkB8xRgou1fNpxWr3tLDdwCLCtpqbwSsj1pi+HPtheuu5bXbC/T5zcpCIIgaMpku9jPQGVQGQlOrqRbkvZeHpA0AfghaebcLheSZtnrAZ8E/lyn9ypwPbB53pLYCzhT0kSSc+Mi+aWbAHdJugO4AviO7adIUQdz5dfeAvw297M28EWSATEu/3w699Vqb2lhSY8B+wAHSnpM0ty23yH5HlxBcoA82/aEfrwfQRAEwXQwULYbOsmgCoGEtKxPCllsduzL0/H7D5O2AmrPDaycn45o8vqt6h5fClza5DX7kG7eje2vkPwCGtuvp7kvAbafBTZq0v4UaSuh2e/8BfhLs2N1r5mrp+NBEARB0MigMxKCIAiCYCAwkLcJSjHDGgk5odHpDc1v2l6jG+cTBEEQzFgM5G2CUsywRkJOaLRKt88jCIIgCAYrM6yREARBEASdJLYbgiAIgiBoylDYbhhUIZBBEARBEFRHrCQEQRAEQRvEdkMQBEEQBE2J7YYgCIIgCIYssZIQTMWobWatROePv76p9xcVYCZVYwfPNvMsvb+oAPPOv0IlOru8259M59PPJfMvUInOyAOqiYa+a9+rKtE5YJblK9F5aEsCBfUAACAASURBVN3dK9FZ6rrjKtEpjT2526fQccJICIIgCII2mBzbDUEQBEEQDFViJSEIgiAI2sAR3RAEQRAEQTNiuyEIgiAIgiFLrCQEQRAEQRvEdkMQBEEQBE0ZChkXY7shCIIgCIKmxEpCEARBELTBUEjLHEZCEARBELRB+CQEQRAEQdCUCIEMgiAIgmDIEkZCF5G0sKSzJD0g6W5Jf5G0nKS7Wrx+Zkn/lfSzhvbNJN0u6Y7cz9dy+/KS/i5pnKSJkk6s4rqCIAiGAraL/QxUYruhS0gScAFwmu3tc9sqwEI9/NomwL3AtpIOsG1JswAnAqvbfkzSbMCo/PqjgV/Zvij3/5HOXE0QBMHQI0Igg06yAfC27RNqDbbHAf/u4XfGAEcBjwJr5rb3kYy9Z3Mfb9q+Nx9bBHisrv/xxc4+CIIgmOEJI6F7rAjcOr0vljQHsBFwKXAmyWDA9nPAxcAjks6U9AVJtc/1V8DVki6TtLekeVv0vZuksZLGnjruoX5cUhAEwdBhKGw3hJEweNgMuMb2a8B5wJaShgHY3oVkQNwM7Aucmtt/C3wIOAdYH7gxb0dMhe0TbY+2PfqrqyxVxbUEQRAMeibjYj8DlTASuscEYLU+vH4M8AlJD5NWIOYnbVkAaSvB9q+AjYGt69qfsH2q7c8B75BWMIIgCIKgV8JI6B5XA7NJ2rXWIOljwJKNL5Q0N7AOMNL2KNujgG8AYyTNJWn9upevAjySf2/T7NiIpIVJhsXjnbmcIAiCocVQ2G6I6IYukSMTtgR+LWk/4A3gYWAvYHlJj9W9/Cjgattv1rVdBPwC2Af4rqT/A14HXgW+nF+zCXCUpDfy8+/YfqpDlxQEQTCkGArRDWEkdBHbTwDbNjk0y3T87nPAAvnpp1u8Zh+SEREEQRAEfSaMhCAIgiBogyjwFARBEARBU4bCdkM4LgZBEARB0JRYSQiCIAiCNhjIUQmliJWEIAiCIGgDF/zXHySNkPRXSZPy//O1eN1ISVfmgn93SxrVW99hJARBEATB4GY/4CrbywJX5efN+D1wuO0PAasDT/fWcRgJQRAEQdAGAyiZ0ueA0/Lj04AtGl8g6cPAzLb/ms/9lZzmv0fCSAiCIAiCNihpJNQX2ss/u/XhVBay/WQ+pyeBBZu8ZjngBUnnS7pd0uG1+j89EY6LQRAEQdBlbJ8InNjquKS/AQs3OfT96ZSYGVgXWBV4FPgTKTvvKb39UhAEQRAEfaTK2Abbn2h1TNJ/JC1i+0lJi9Dc1+Ax4HbbD+bfuRBYk16MBA2FEI6gs0jaLVvBoRM6M4xOlVqhM7B1BjqSDgeetX1YrgU0wvZ3G14zDLgN+ITtZyT9Fhhr+9ie+g6fhKAEfdk7C53QGSw6VWqFzsDWGegcBmwsaRKwcX6OpNGSTgaw/S6wL3CVpPGAgJN66zi2G4IgCIJgEGP7WWCjJu1jgV3qnv8VWKkvfcdKQhAEQRAETQkjIShBVXuCoRM6VepUqRU6A1tnyBKOi0EQBEEQNCVWEoIgCIIgaEoYCUEQBEEQNCWMhCAIgiAImhJGQhAEQTCokDSLpFUlNatREBQkjISgbZTYUdIP8vORklbvgM6hkuatez6fpJ8U7H/e3l/VWSRtXJHODzrc/2c70Of7G57vKOnoXBBHhbVOn562TlDVGKgCSfcV7u8ESSvkx/MAd5DKHt8uaUxJrWBqIrohaBtJxwOTgQ1tf0jSfMCVtj9WWOd226s2tN1m+6OF+n8H+DtwJnCe7RdK9NvHc3jU9sjBpCNpq8Ym4FhgdwDb5xfSee+zlnQgqUjNGcBmwGO29y6h06iVnw8Dxtv+cCmNHrRLfjYfIWXTWwy4DPie7efzsZttFzPmJb3MlDIGNaNtTuA1wLbnLqAxwXbNSNgLWN/2FpIWBi5r/H4IyhEZF4P+sIbtj0q6HcD285Jm7YDOMEmz2X4TQNIcwGwF+58I/BoYA/xC0vUkg+Ei26+XEpF0catDwPwFdV7qQWeOUjrA2cDlpGIytZvDcGBz0k2jiJFQ1zfAVsC6tl+VdAYpF33/BaT9gQOAOerePwFvUTAWv6oxABwP/BC4kZRx73pJn7X9ADBLQR2A3wHzAN+x/R8ASQ/ZXqqgxlt1jzcGzgGw/VThxaSggTASgv7wdp5pGUDSAqSVhdL8gZRv/LdZ66vAaQX7f9v2pcCl2QDZHNgeOFbSFbZ3KKSzLrAj8EpDu4CS2zQvAB+rfWFPJST9u6DO/5ByxN8CnGDbkta3/ZWCGpBu3KuStkeH2X4VwPbbkt4tIWD7Z8DPJP3M9v4l+mxBVWNgLtuX58dHSLoVuFzSFylcvND2HpJWA87MlQV/U1oDeEHSZsDjwNrAzgCSZqas4Rs0EEZC0B+OBi4AFpT0U+DzwIGlRWz/QtKdwCdIX6aH2L6ioMR7U5G8cnA2cHbe+9yioM6NwGu2r53mBKR7C+r8HlgSmMZIIC3TF8H2LXkffQ/gaknfozPVc58EfpkfP1dXEnd+4J2SQrb3l7QY6f2bua79H4UkqhoDkjSP7RcBbF8jaWvgPGBEQR1y/7dK+gTwTeBaYPbCEl8jfd8sDOxl+6ncvhHw58JaQR3hkxD0C0kfJP2hCrjK9sTC/Q8DruiplnoBjX1tH9Gp/ocC+cb6K2C07aUr0hwGzGb7tYJ9HkZaRbobqK1S2HZxh8xOImkH4EHbNza0jwQOsr1rB7UXAVa1/ZdOaQTVEUZC0DaSms1IXrb9dmGdi4Ev1mZFgx1JC5Ecygw80WxboIDGPMCm9TokY6typ8xSSBoNLEFaPZhk+54OaNwLrFTzf+kUVYyBKsmThc8x9Xi7uNSkQdKuwN9tT8oRLacCWwMPAzvZvr2ETjAtsd0Q9IfbSF/az5NWEuYFnpT0NLCr7VsL6bwBjJf0V+DVWqPtb5XoPN9Q9ydtLSyQm58GLgIOK3Vjzfvqx5OcvB7PzYtLegHY3XYpJ7wvAQcDV9bpbAAcKulHtn9fSKeq92094EiSr8VqwA3AfJLeJhmPJf0sHiQ59nXESKhqDPRyDifa3q1gf98jOf2eBdycmxcn+SicZfuwAjJ7khwkyVorAUsBq5K2IdYtoBE0IVYSgraRdAJwQc0/QNImpNnr2cBRttcopLNTs3bbRZwXJV0BXA2cVtvrzKFVOwGfsF0kfl3SOOBrtm9qaF8T+D/bKxfSuZcUefJCQ/t8wE22lyukU9X7djuwie1nJC0F/NL2ltkf4ju2Nymhk7XOA1YGrqLOUChokFY1Blr5HQi4w/biJXSy1n3ACo0riDnSaYLtZQtojLO9Sn58BmkcH5WfFwuHDqYljISgbSSNtT26WVv9H3UhrTmAkbZLOnfV+r7X9vJ9PdaGzqRWX5iS7re9TCGd+0jRDS82tM8DjC3xpZ37q+p9u9P2SvnxMOCWurwJ78XPF9LqtEFa1Rh4F3iEqcNHnZ8vZrtYqLKke4BP2n6koX1JUt6Ufo8DSbcBnyGtWj5Cys0yIR+baPtD/dUImhPbDUF/eC4vNZ6Vn28HPJ+/yIuFQkraHDgCmBVYStIqwI8LOpM9Ium7pBlxLc57IeDLQMml7Msk/ZkUfVDrdwngS6R8A6X4KXCbpCvrdEaS4ssPKahT1fs2VtIppNn950iJr5A0JzCsoA62T+ukQUp1Y+BBYCPbjzYeKBwGC7AXKUR5ElOPt2VI0Q4l+AEwlvR5X1xnIKxHutagQ8RKQtA2SulyDwbWyU3XAz8GXiR9yd5fSOdWYEOS49KquW287Y8U6n8+YD/SDaiWC/4/wMXAz20/V0Ina32KKQ5eAh4jfekV9QTP1/TJBp0rnLPuFdTo+PsmaRZgV+DDpHS8p9p+N9/MF2ycwfZT6z2D1HYnDNJKxoCkbwDX276jybE9bB9TSiv3ORMpz0P9Nd1iu0gei6wxM/C++jFcMxRtv1xKJ5iaMBKCtsirBYfZ/k4FWjfZXkN16Znrl6CDoBSdNkiHGpLmst2YOKpEvyI54+4AbG57odIaQSIKPAVtkWcIq1Ukd1eO+x4maVlJxwD/rEJYUrHsgZKGSfqapEMkrdVwrHgSqhbnML4indJZF1vpXFa4y3eahNoWm0kNkDFQZSGpu0t2JmkNSUeR/BIuBq4DPlhSI5iaWEkI2kbSkcCypDzq9aGJpXL213TmBL4P1LzYrwB+YvuNkjottEsW3TmZVPjmZuCLwLW298nHShasaiy89N4hUvrkBVocL0bh963V+yLgUtuLlNDJWjXfh/1IcfjfAmax/fVC/VcyBno5h6LFxCTt0+oQ8H3b/c7wqJTRdVvgUVJdlQtITrgl60METQgjIWgbpVoKjdj2VwtqLEBKkXt/pxIBKaV8bnoIWM52kWJSDV76MwPHAe8nxX3f6EKV7JTyB/yR5jPgz9t+XyGdqt63d0mpfptV8lnTdrHc/Q0GqUgG6SGlDNIKx0BPhaQ2tD28hE7WegM4nOYpsve23e9S7JKeAe4lFWK71PYbkh50Rdk9hzJhJAQDFkm7AIcCD5ASp+xmu9WXX390/kNy8mt06hPwT9uLFtK5x/YHG9p+kLUXLBiaeCspC91dTY792/YShXSqet/uAra0PanJsWLXUwUVjoHnaV1I6k8l9/Al/RPYw02Sp5X6fLIP1CYkY2pD4BpSLZclbBet3xFMTYRABm0jaXZSNbYVqCvoUnAlYS9SkpZnJC1Nmh0XNxKAS0lV88Y1HpD094I6YyVt6inV+bD9Y0lPkLLwlWIvoFW56C0L6lT1vv2Q1v5TexTUQSn18wHAKKYu8FTKSbaqMVBVISmArwCtIllGt2jvE9kH6jJSCOnswGakbZvHJV3lcpVagwZiJSFoG0nnAPeQPIx/DHwBmGh7z0L9T7VHW9WebTB0yTfQ7wDjqcv1UTLMMiiHpLlJKeCP7Pa5zKiEkRC0TS0ksbbPmuPZr7C9YaH+n2ZKoiZI1fnee+5CqXKzlpgS510rUHOzC/+BqMOFcLLGzKQVni2BRet0LgJOccECXFW8b9kx7kXbpzS070GKkf91Qa3rba/T+yv7pdHxMVCnVVUxsY7X8OhBv6gjZjA1YSQEbSPpZturS/oHsDvwFOkGUcSZSC1S5NZwuVS5m5AcyCZRV3SHlDFud9tXFtKpL4TzWJ3O9kCpQjhIOpNUDOm0Bp2dgBG2tyukU9X7dhfwUdtvNbTPRkrYUyxfhqSNSJ9RY+2GIhE7FY6BpoWkSOOiaCEpVVTDowf9QeWXMtgIIyFom+xYeB6pIttvgbmAH9g+oasn1kckTQQ+ZfvhhvalgL+4UF54VVAIJ/fXU02F+1yuwFNV71vLZEalEx1J+gMp7n4CU7YbikXsVDgGKikklfuspIZHD/qxktBBwnExaBvbJ+eH1wLFQ5EkXUIPiWxcLlXuzEyZ1dXzOKlscCkmk5b/G/e3F6FgrQtS/YxtgPNsTwZqaXO3YdpIhP5Q1fuGpIUal8rzUnppVi5pdDShqjEwvNFAALB9o6Ri4Y+ZR9ThGh5KScCafRcIiGyLHSSMhKBt8nLv1kzrCf7jQhJHFOqnN04FbpF0FlMXqNkOOKXlb/WdKgrhQFq6/jlwXA6FEzAvaUl4+4I6zd63JbJGyfftcODPkr4N1JbJVwN+QfkxcqOkD9sumimwjqrGQFWFpCD9newHXCupsYbHtoU0tiIZA41Gx5Ikn46gQ8R2Q9A2ki4nFXO6FXivkEsnPI3zcmxtmfzeks53uf8PA59l2qI7pdPKdrwQToPe/KS/8/92qP8P0bxYUen37VOkG9GKpBnlBJJTXNG0zHkL5QPAQySfBJG2G0r6PVQyBlRRMbEqkHQpcIDtOxvaRwMH2968O2c24xNGQtA2ku6yvWIFOuuTnPAeJn3ZLUFKFvSPDmq+vxM3VkkjgZdsvyBpFCmOfKJz6duCOquTbm63ZANo06xTutbBDIWkJZu1lwyBrGoMVEmO2FiMlDXy1br2qXJC9KP/lt81pf1SgqmJAk9Bf/inpCr+OI8ENrG9nu2Pk7LT/apU55I+JekhSddLWlXSBOAmSY9lb/dSOvuR/DduzE6flwOfAs5W6/z37egcDBwNHC/pZ8BvSE6l+0v6fkGdTesezyPpZEl3SjqjpL+ApCvrHu9fqt9mZGNgXmDz/DNvYQOhkjHQyzmcWLi/b5HCHfcAJkj6XN3hQwvJzN7DsWJpuYNpiZWEoM/UORHNTCrw9CAdWprNetOUhW7W1o/+x5HC0uYlZRH8THbw+hDwx1IJnLLxMZqUKe5hYOmcTXI4cFOpVZn8+awCzEYKS13c9kuS5sg6pd6395JbKRUuego4ibR/vJ7tLQrp1JcI72hCLUl7ArsCtZDHLYETbR9TqP+qxkCrokoC7rC9eAmdrDUe+B/br+SVkXOB020fVf/Z9VPjTOBq2yc1tO9MmkAUCesNpiUcF4N22KxivbFK1flOz8+/QPKDKMXkWiIbSa/ZvhHA9sS8f1yKd22/Lukt4HXg2azzqtSsdlHbvJP3t1+T9IDtl7LO65JKetDXM9r2Kvnxr9RLjos+UuVMZmdgjdqSuaSfA/8CihgJVDcGniFFUNR36vx8waa/0T7DbL8CYPvhvD14bt66KXVRewEXSKr/2x8NzErZVONBA2EkBO2wIPD+xv1tSZuTPI1Lp7D9X+AbpLK9Av5BSuJTihckfQ2YmxQ+uDdwNqmATGOBnP5wm6QzgOGkZD2nZefPDYGSjn5vSZrT9mukKADgvcx4JY2EBfMSuYC5JclTliZLGldLK1U1VN3j9ygYCkvWqHcgfJdyNzqobgw8CGxk+9HGA5KKhCXW8ZSkVZxreOQVhc1I0S9FtiNzaOVakjYgOa8C/Nn21SX6D1oT2w1Bn1Eq3vPlJkl0liEtzRZJy1wVkpYADiTNtH5I2nrYmWTs7OtC6XKV0iVvk3XOJXm47wA8Chxb7/DVT53ZbL/ZpP39wCK2xxfSObih6bi8dL4w8AvbXyqks15Px92kiFE/tPYhZQq8IDdtAfzOhVI/VzgGvgFcb/uOJsf2KLV9kvtbnLR69VSTY2vbvqGUVlA9YSQEfaYnb2JJd5TK5ibpzp6Ol/Z9mJGQqqlFUQWS5q5tmTQ5NrLZbLmfeh8F1iGvWtm+vWT/MyItIjbucZNy5cHgIrYbgnboyZu4ZDa3yaQb3BnAJaQ93I6QlzG3JoVXvkOqR3CS7QcKatxGcog7s2S/TXRa1lSQVLKmwghSAqAnSMmTDgD+B5gIHGq7VHbHvwM1B8mrbNdHnFxYO9YfGhz9Hs4/7x2z3aoUcl91KhkDWauSQlI5YuNrwJuSjgD2BW4AfiTpFNu/LKkXVEsYCUE7/E3ST4ED62emkn5EyupXBNur5C+6MSRD4e78/5W23ymlI+kwUja3q4CFSYl0HiA5Xx1q+5xCUvORIiiukfQUcCbwJ9ulM8YdRSqs83B9o3JNBaBITQXgD6SSyqsBO+bHPwc2Bn5HukGVoN4noNFrv5S/wH9JyYZq46rR4a9U2vFKxoCmLiR1c25eHDhTUrFCUpkvAh+mRcQGEEbCYMZ2/MRPn35IqwVnkm6k5+Wf+0lfSHN1UHc70pf5dwr3O77u8czADfnxfMBdBXVuq3u8Lmm2/xRwDbBbQZ1JwMxN2mcF7i+oMy7/L+DxZsc68L7d1upYPzWOAu7In8m65K3Y0j8VjoH7gFlajIFJha/pzvz/MFKJ6JnqjhX7+4mf7vzESkLQZ5ycq8ZIWhpYITdPsP1g/eskreB+ZpGTtBipFsCWpOJEezPFqawUk+uWlBclfdlh+3kVjkurYfs64DpJe5Bm3tsBpZLcVFVTYSZJ8wHvA+aSNMopBG5+0s2oFPVRFLXH5OcLlBCwvWf+rNcnzYyPUUridLzth0poNNHs5BioqpAUtI7Y2IiyERtBFwjHxaBj9DfxjaRrSTegs0me4FPtC7vcPvF2pGJB95LKBP+v7T9LWgA4yvYOhXTOsl2ywFJPWh2vqSBpDFDz+t+dFKpq0tLzj2wXueE1iaKYCts/KqFTpzcvyaA6hFQv4KRefqUvfVcyBpSyYf6GtKo0TSEpF0iVXKfVGLGxBmmro2jERtAdwkgIOkZ/s61JepgpiXTqB2ots2Ox8tTZcW1p0nL8C6X6HWiUDkmTNIz0PfJOvlmsQtp6eLKURh/OZX/bP2vzd4eTjKrtSKsT55N8BUrnFKgMVVxMrE53FlIug8dtP91JraDzhJEQdIz+riR0G0nLk/Ik7Fqovx5z87uQF3i+cW9LujlcbvuunNzmAGCO/hhuDTo9fra2b+vpeGn6M94kvUqadZ9J8q+Z6ovR9vnNfq8NnarGwJzA287VUvNY/jTwsO2i23WSTgCOsT0hJ+z6FykJ1QjS38+ZJfWCagmfhGDAI2lLUt72F/PzeYH1bV9YqP+VgCNIe7gXklLwHkdaNi1Z9voIYBxwGVNqXXSCU0g+CDcDR0t6hBSauF+p9ywzllSy+Zn8vDEioOqkWv15P88hnfMH8089Zkoth/5S1Ri4nJQQbFJOcvYv4I/AZpJWt12yUNa6tr+eH38FuM/2Fjmp1mUkwysYpISREBRF0qKeEs71VqFuD66f/TglbDmYdEMvwUnA8aQv0k2B20ihll+w/UYhDUjx/NsDnyHlnz8TuMrll/NGAyvZnixpdlJEyDJukhGvn3yblFvidVJkywXOOfy7RNvvo+0vFzyPnqhqDMxne1J+vBMpL8MekmbNuiWNhPq/841JBhe2n+qQ329QIbHdEBRF0qO2Rxbus1kVyGI15CWN85TiRLXc9qM6uXcraS2Sc9cngO/ZvriXX+lL31Mtu3d62yfnXxhD2tN/hJRIaVyn9Ho4j7Z9YCTtaPsPrbYDSm0DNGh2cgy89zcj6Qbg8NoqUsmsqLm/a0grbo+TQjk/mA2EmUkhkI0rM8EgIlYSgtJ0YuowVtIvgWNJs8U9KFsFcnZJqzLl3F8BVqqFP5beW89RE6uSit88RootL8kH61JaC/hAft6RUt62H5J0ESkT5xeB5UhL6kWQ9E3bv5mOl/Yn6VUtU+j7+tHHdFPBGLgzZz98nBTRcGXWnbewDqRsi0eTEpHtVbditRHw5w7oBRUSKwlBUTq0kjAcOIg04xLpC+8npUKr8kyoFXahglWSvkLynp+dFCp2die8v5VK9LbEdpEqnTlPxvakFYR/k7YcLi28RTPoHWDrqXAMzAHsScqLcKpzoae8evEB26f39PtBUCOMhKDPSDqG5vu/AnayPXfFpzQokDSZlLq4VpCo0YO+ZMnj2jbACllnYmOyqwL9TwbuBC4CXmLa6ynlqV+ZkZBn+LsCo6hbabX91UL9VzIGJG1s+68tjv3c9vdK6OT+fgE8aPuEhva9gYVLagXVE9sNQTuMbfNYn5D0a9t7SbqEJkZJ6ZtqE/2Nge/a3rhQlxsU6qdHJM0NnExyYBxHMt5WlnQrsLNbVFRsgx8z5XOZq1CfzVhJUrNzrm2flDRKLwKuA/5GCuMrTSVjADhW0t6231vuz3kTTiVtC5RkM1JehEaOIhmRYSQMYsJICPqM7dNaHcv7oKWoLYmW7HMaJG0InMCUEMhDgd+TbkI/LSi1BnBkp5PZkPaH7wa2tz0ZqJWOPoiUhe9LJURs/7BEP9PB+FK5HaaDOTs8861qDGwCXC5pNtvn5yiXc0krPpsX1nJtnDU0Tu5UWvOgOmbq9gkEMxzblurI9q35/2ub/ZTSIXlm7wbMT/oivRE43fZqpZLoZJYEbpW0dsE+m7G27R/Wf3E78WNSvoQiSJpd0k6SPqvEdyVdKukoSe8vpVMxl0r6dAf7r2QMOFUA/QRwiKSvk2oq3Gd7h1qCpYK8JmnZxsbc1rHy7kE1hE9CUBRJ/7a9RKG+xtND7HspL/0mIYMP2P5Aib6baH2UlKzpHlJuhvobeZEoCkn3216mxbFJtqf5Qm9T52zgbVJkwHzAXcAlwDrAKrY3K6RzgO1DS/TVg8bLpLEm0vW8Rbo2KLylUdEYqI3nRUirYn8l1ScpqpO1PkW6np8wJepoNCkXw162/1JKK6ieMBKCPqNU56DpIeAO24sX0ql56X8j/1/bfvgC8FqeGZfQeRDYt67piPrnhVcTkLQ+qbx2vRFUMoriNFIZ70Pqk/RIOghYzvYXC+ncZXvFHA//mO2F644Vi8XPibNafVHZ9iEldKqkgjFQScROnd6KwHeY4pswgZSbYXxJnaB6wkgI+oykh5gy62rELlh4KevdYHvt3tr60f9vezjsgp7tC5K2NpYGdq+FpZUmOy6eQsruN470Wa0K3A7s4kIFrOpXYDqZwEnSt5s0zwnsAsxvu6jTpKStSKshBq5zwVTWVY2BgUD2g9jcdn/yVwRdJoyEYMAjaRypvO31+flawHGuy5I4GMgrFocBJ7mCPzxJHyCVbRYwwfYDhft/mpQbQaTY/7Nqh4BtbS9UUi9rvo8U/78zqYT4kSXzDEg6jpR8qFZvYDvgAdvfaP1bfeq/kjGQDZ16TErPPc72yx3UHUZymhwDfJJkZH2+U3pB5wkjIegzmrb6n4H/ukNldSWtRgrdmic3vQB8teD+bWMq3toX6vW2HyqhkXUWsP1Mk/YlSJEIhxfS2dH2H/LjqUpD9yF74fTo7NTT8Z6iYNrQGgHsQ9pqOg04yvbzpfqv05kArFi7geewwfG2VyjUf1VjoNnq2AhgJVIY7NUldOr0Pg7sQKpJcTOwNrC07ddK6gTVE0ZC0Gda7HeOAGYFxrhDefvzMrqcq0EW7PfgJs0jSDOhH9o+q8nx/mq+H9iGNONajFQcad+ef2u6+65kG6BBcy7S1kyRLJgNfR8ObAWcCBzrDhaRknQ+sLdzVsrsF3OY7TEd0OrYGOhBc0lSlsc1Cvb5GCk51PHAhbZflvSQ7aVKaQTdI/IkBH3GdtOEMJJGS/5stwAADqBJREFUk2L0P15CRy2K7tRCr10oo5/tH7XQH0FKqlPESMhL5VuSZlzLAReQZltFHD3rpVo8bva8f0LS/5K82Ifn568AP7d9XEGZb5PKKh8IfL8u9L4TyZTmByZKujk//xjwL0kXQ/8TeFU4Bppi+xFJsxTu9jxgC9LWzLtKdTxi9jmDEEZCUAzbY/OMshSVFt1pxPZzhZPBPE1aij2QtJVhSVsW7L+GWzxu9rxtJB0IrAWs75zyWamew1GSRtj+SQkd21Xmc/lBh/uvagw0RdLyJIOrGLb3lLQXKZvkGOBwYG5J2wJ/6eTKT9B5YrshKIakhUhfCqt1+1xKoJSJ8cCCYWl7kwoiDQfOAP4E/LUD0SCvAfeTZtofyI/Jz5e2PbzV7/ZR515gZTcUdFIqLnSH7eVK6HSDvLVVX7vhuUL9VjUGmqUyH0HKm7Cj7X+V1GvQngXYlGQwbGJ7sCbWCggjIWgDNS/wNII0q9zT9iWF9U7L/b6Qn89H8movFZrYLGnTCOAJUsGqiSV06vSWJn2Bbg8sCxxM2o++r1D/VVWBvNf28i2O3WP7gyV0qkTSbsAhpEyBk5mypVH6Jt7pMbBeQ5OBZ4FJtt8qoTGd5/Fx2/+oSi8oTxgJQZ9p4tVe+wK6pWQ4Wp3e7W7I3d+srR/9N95UDTzbCSe8JtofIe1Pb+sOZXnsFJKuAg61fVVD+4bAQa18VwYykiYB/2P7vxVqFh8Dkta0fWOJvqZDaxgpHftiwOW275K0GXAAMEepv9OgO4SREPQZSSNtP9r7K4vp3UHa934+Px8BXGv7Ix3UHE5yxtrB9mcK9z0vafYIKZ9+6WiNnYERtXA6SY+T/DpEqmp5fCGdFUhVE68npeM1ydFvbeBztieU0KkSSZcDW3U6dK+CMVAf4fIv28VqdjTR+h2wBMnXYg3gEVKNkP1KJqIKukM4LgbtcCEpmx+SzrO9dYf1jgT+Kelc0o1oW1KlxqJImhX4NGlWtynJa/uEwv2fSDI+HiLdtJeUdAHw9YLLwF8nnX+Np20vljPgXUkKVes3ticopePdAViBdD3/AL7W6KcwiNifNNZuos7Bz/a3SnRe4Riod7idvVCfrRgNrORU9XF2Uo6RZWw/1WHdoALCSAjaof4LqOhebTNs/17SWGDDrL2V7btL9S9pY6ZkiLuGVCNiddtfKaWRORCYBViilvUuh8QdSyrjfFAhnZlsP1v3/BwA229kp8Ji5D6vIXntG5g4iA0EgP8DribVVJim/HEBKhsD2XdnprrH7/3dlnLEzLzlXHE0j4f7wkCYcYjthqDP9JSspwLt4aQ48zGltgEkTQauA77snGFR0oMdcFa7i2R8vNbQPhdwo+0Vm/9mn3WaVoHM2QPvL3VdOQLgZGA1Uo2ImYCVSVsPO9t+qYROlUj6p+21Oth/VWPgYaY4XjZS1BGzLpoGpo6oqTl9FqnWGnSHWEkI2mFlSS+RvgTmyI+hM8ltOr4NQLrJbQ/8TSm3/lnAsIL915jcbK/b9iuSSlrrV0r6ie0DG9p/TNpuKMXRwN2kdMKTAXJeiYOA3wBfKqhVFdfkCIdLmHq7odTMu5IxYHvU9LxO0goFfEc+1M/fDwYwsZIQDFiabAP8CThmer8A29RcO2tuTZodX2D7xEJ93wGsT/PZ3TUuV1p5OGmG/zGgVmVwZWAsqQpkkeQ2kibZXravxwYyShVOGyk2865qDPThfCpbCey0A2XQGcJICAYsVW0DtNCeCdiYNEv+Sm7r16yryiXgrLc0yaEQ4G43VIEscD1NtzXysUFpJDRD0qylHAqrHgPTcT7FQokHklZQjthuCAYyVW0DTENePr8i/9Q4nRzV0Wafo6bndYWWgHFKlfxgDy/p1/UAN0j6AXCI62Ybkg4CKonR7xR522QD0hbX5kCRstdVj4HpoMpZYsxIByFV5kQPgj5h+3bb38sJZn4IrArMKumyvG9cNUWLI/XA6RXp9Pd69gA+Atwv6TxJ50p6gLS18c1+n10XkLSGpKNIsf4Xk1ayupE5sqoxEAQ9EkZCMCiwfYPtb5Kyuv2alKwFeC+pTyWnUZFOVcZIv67H9ku2twE2AX4H/J6Uq//z9cmBKvx82kbST3O2xUNJ4Y+rAs/YPq2WxKvqU6pIp7IUzVR3TUFBYrshGFR0YhtgADKolmWzr8MDPbxkMHw+uwH3khJNXZrj/bv5OfRLO6caf6FmrEnagJTA6RHgNzUfC9tr9vdEJV1pe5PpeOkX+6sVVE+sJAQzAh2boUhatO5plbOujtCl6xkMM8iFgZ8CnyVtn5xOCu8drBOps8ml1iWtQkqo9ShpK+i4wloLTM+LbN9VWDeogMH6BxAE9XRyxncjMBLKzLpaIWlR20/kp528eVdyPQ0M+JUR2+8ClwGX5dTCmwFzAo9Lusr2DhWfUn/HwBx142lH4FTbR+aonXH97LuReSRt1eqg7fML6wUVEkZCEPRMVbPgqm7eg2FW31VyWulzgXNzyuSWN8C+UuE2QP3nvCGpJgW5vkLpMTAPyahqGtYJhJEwiAkjIRiUVDjzDmfFNqjw8ymKpNlIibRG0Znvx7NJacVfrNsG+BlTtgF2KaRztaSzgSeB+Uj1KJC0CFC6tsYjtr9auM9ggBBGQjBYKTbzlnQMzW+eAubtT999oNjNe4BcTze2NUpwEfAiqf7Em728th2q2gbYC9gOWARYx/bbuX1ZYERBHYDlJa1t+4b6RknrAk80JvEKBhdhJASDlZIz77FtHusTFd68K7meXhis2xqL296095e1TSXbADm51VmQHBcl7Ukqsf4QKYS4JDcBLzdpfz1rbV5YL6iQMBKCwUrJYjintTom6YhSOlR0867weno8jYp0SvNPSR+xPb5D/VeyDSBpOVK20jHAs6S6J7K9QSmNOha0fWdjo+2xkkZ1QC+okDASggHLAFk23xbYt0RHA+TmXex6BsjnU5p1gC/nQk9vUr7ccVXbAPeQskVubvt+AEl7F+y/ntl7ODZHhzSDiggjIRjIDKVl82I3714YdNs0FfOpTnZe4TbA1qSVhGskXZ41OzWWb5G0q+2T6hsl7Uzy7QgGMWEkBAOWqmbeklrN4ER1RkIxnaquZ4CsjBTF9iMAkhak5xlyW1S1DWD7AuCCXDZ8C2BvYCFJx5PKn19ZUG6vrPUFphgFo4FZSZEcwSAmSkUHgxJJj9oeWaivh0jL5h0t39vLzfsO24sX0qnkeno5h2KfT5VI+ixwJLAo8DSwJDDRdpH6E3Xlz3eu2waoqvz5CGAbYDvbG3ag/w2AFfPTCbavLq0RVE8YCcGgRNK/bS/R7fPoCwPh5l0Vg/HzAZB0Bynq4G+2V803vjG2i1QdlbQlaSVhLaC2DXCy7aVK9B8EpYnthmDAUtWyuaTG4kMG/mv736U0AKq6EVR1PQNkm6Y0b9t+VtJMkmayfY2kn5fqvOJtgCDoN7GSEAxYKtwGuKZJ8wjSnuoY20WS3FR4867qema4lRFJfyPdvA8D5idtOXzM9lod1OzoNkAQ9IcwEoKgBZJGA7+0/fFC/VVy8+5Bv+j1zIjkGf7rpAq5XyDVJfij7We7emJB0CXCSAgGLFXNvHs5h9tsN55HaY3Kbt4lr2cgfD6dIBdhWtb23yTNCQyz3SyjYBDM8IRPQjCQObJJ2whJVc28F6KCzIE5M91cndbpwPV09fPpBJJ2BXYjrfB8AFgMOAHYqJvnFQTdIoyEYMDSKnY8z7yPBkptAzTLHDiC5IG+ZwmNXvSL3ryrup6qPp+K+QawOqkeAbYn5ZwJQTAkCSMhGHR0YObdmB3QpEQ3+9h+upRIhcZIJdfTiqpWRjrEm7bfqtVakjQzg7cORRD0mzASgkFHB5bNr7H9aMH+WlHVzbuq62lKVds0HeJaSQcAc0jaGNgduKTL5xQEXSMcF4MBS28zb9tFvrzrnfkknWd76xL9NtEZWcXNu8LrqeTzqRJJMwE7A5uQQjuvICU7ii/KYEgSKwnBQKaqmXd9nH8nY/svBDp+86a66+nqtkYnsD0ZOCn/BMGQJ4yEYCBT1bK5WzwuTVU376qup6vbGiWRdGdPxwuWig6CQUUYCcFApqqZ98qSXiLdxOfIj8nPbXvuQjpV3byrup6qPp8qmEz6TM4g+SC83t3TCYKBQRgJwUCmkpm37WGd6ruBSm7eFV5PVSsjHcf2KpI+SCrhfAZwd/7/StvvdPXkgqCLzNTtEwiCHqhq5l0JtofZntv2+2zPnB/Xnpea3VfJjPb53GP74Oz0eQnwe1IBpiAYskR0QzBgkfQu8Cp55g28VjtE2WXzoA1mtM9H0mKkMs5bAs8DZ5MqM77S1RMLgi4SRkIQBEMeSdcC7yMZBucCz9Uft/1cs98LghmdMBKCIBjySHqYKVsm9V+KtVWRQe1zEQTtEkZCEATBdCJpBdsTun0eQVAV4bgYBEEw/Zze7RMIgioJIyEIgmD6Ue8vCYIZhzASgiAIpp/Ynw2GFGEkBEEQBEHQlDASgiAIpp+3un0CQVAlEd0QBMGQR9KSwAu2X8zPNwC2AB4BfmM7jINgSBIrCUEQBCmJ0nAASasA5wCPAisDx3XxvIKgq0SBpyAIApjD9hP58Y7AqbaPlDQTMK6L5xUEXSVWEoIgCKYObdwQuArA9mQi7DEYwsRKQhAEAVwt6WzgSWA+4GoASYsAb3TzxIKgm4SREARBAHsB2wGLAOvYfju3LwuM6NpZBUGXieiGIAiCOrLj4g7AtsBDwPm2j+nuWQVBd4iVhCAIhjySlgO2B8YAzwJ/Ik2iNujqiQVBl4mVhCAIhjySJgPXATvbvj+3PRglooOhTkQ3BEEQwNbAU8A1kk6StBER1RAEsZIQBEFQQ9JwUqbFMaRQyNOAC2xf2dUTC4IuEUZCEARBEySNALYBtrO9YbfPJwi6QRgJQRAEQRA0JXwSgiAIgiBoShgJQRAEQRA0JYyEIAiCIAiaEkZCEARBEARN+X+WQJXR0cjCMwAAAABJRU5ErkJggg==\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"## we can also check the correlation in regards to the CLASS"},{"metadata":{"trusted":true},"cell_type":"code","source":"Train.corr(method='pearson')['CLASS']","execution_count":50,"outputs":[{"output_type":"execute_result","execution_count":50,"data":{"text/plain":"FULL_Charge 0.534602\nFULL_AcidicMolPerc -0.598816\nFULL_AURR980107 -0.584111\nFULL_DAYM780201 -0.554838\nFULL_GEOR030101 -0.260470\nFULL_OOBM850104 -0.453287\nNT_EFC195 0.260702\nAS_MeanAmphiMoment 0.693552\nAS_DAYM780201 -0.437168\nAS_FUKS010112 0.033432\nCT_RACS820104 0.267652\nCLASS 1.000000\nName: CLASS, dtype: float64"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"# Skew of Univariate Distributions\n### Definition of skew.\n* Is the suddenly change direction or position.\n* or Skew refers to a distribution that is assumed Gaussian (normal or bell curve) that is shifted or squashed in one direction or another. \n\n\nYou can calculate the skew of each attribute using the skew() function on the Pandas DataFrame.\n\n#### NOTE: If skewness value lies above +1 or below -1, data is highly skewed. If it lies between +0.5 to -0.5, it is moderately skewed. If the value is 0, then the data is symmetric\n\n### Positively skewed data:\nIf tail is on the right as that of the second image in the figure, it is right skewed data. It is also called positive skewed data. Common transformations of this data include square root, cube root, and log.\n\n### Cube root transformation:\nThe cube root transformation involves converting x to 𝑥(1/3) . This is a fairly strong transformation with a substantial effect on distribution shape: but is weaker than the logarithm. It can be applied to negative and zero values too. Negatively skewed data.\n\n### Square root transformation:\nApplied to positive values only. Hence, observe the values of column before applying.\n\n### Logarithm transformation:\nThe logarithm, x to log base 10 of x, or x to log base e of x (ln x), or x to log base 2 of x, is a strong transformation and can be used to reduce right skewness.\n\n### Negatively skewed data:\nIf the tail is to the left of data, then it is called left skewed data. It is also called negatively skewed data. Common transformations include square , cube root and logarithmic. We will discuss what square transformation is as others are already discussed."},{"metadata":{"trusted":true},"cell_type":"code","source":"Train.skew().plot(kind='bar')\n#When we look to the data its highly positively skewed","execution_count":51,"outputs":[{"output_type":"execute_result","execution_count":51,"data":{"text/plain":""},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"# Data visualization\n## Understand Your Data With Visualization\nYou must understand your data in order to get the best results from machine learning algorithms. The fastest way to learn more about your data is to use data visualization.\n\n### Univariate Plots\nIn this section we will look at three techniques that you can use to understand each attribute of your dataset independently.\n\nHistograms.\nDensity Plots.\nBox and Whisker Plots.\n\n\n# Histograms"},{"metadata":{"trusted":true},"cell_type":"code","source":"plt.figure(figsize=(16,16))\nTrain.hist()\nplt.show()","execution_count":52,"outputs":[{"output_type":"display_data","data":{"text/plain":"
"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"## Density Plots\nDensity plots are another way of getting a quick idea of the distribution of each attribute. The plots look like an abstracted histogram with a smooth curve drawn through the top of each bin, much like your eye tried to do with the histograms.\n\n"},{"metadata":{"trusted":true},"cell_type":"code","source":"Train.plot(kind='density', subplots=True, layout=(3,4), sharex=False)\nplt.show","execution_count":53,"outputs":[{"output_type":"execute_result","execution_count":53,"data":{"text/plain":""},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"## Box and Whisker Plots\nAnother useful way to review the distribution of each attribute is to use Box and Whisker Plots or boxplots for short."},{"metadata":{"trusted":true},"cell_type":"code","source":"#boxplots help to represent outlies\nTrain.plot(kind='box', subplots=True, layout=(3,4), sharex=False, sharey=False)\nplt.show()","execution_count":54,"outputs":[{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"## Multivariate Plots\nThis section provides examples of two plots that show the interactions between multiple variables in your dataset.\n\n* Correlation Matrix Plot.\n* Scatter Plot Matrix.\n* Correlation Matrix Plot\n\nCorrelation gives an indication of how related the changes are between two variables. If two variables change in the same direction they are positively correlated. If they change in opposite directions together (one goes up, one goes down), then they are negatively correlated. You can calculate the correlation between each pair of attributes. This is called a correlation matrix. You can then plot the correlation matrix and get an idea of which variables have a high correlation with each other. This is useful to know, because some machine learning algorithms like linear and logistic regression can have poor performance if there are highly correlated input variables in your data."},{"metadata":{"trusted":true},"cell_type":"code","source":"Train.columns","execution_count":55,"outputs":[{"output_type":"execute_result","execution_count":55,"data":{"text/plain":"Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n 'CLASS'],\n dtype='object')"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"correlations = Train.corr()\n# plot correlation matrix\nfig = plt.figure()\nax = fig.add_subplot(111)\ncax = ax.matshow(correlations, vmin=-1, vmax=1)\nfig.colorbar(cax)\nticks = np.arange(0,9,1)\nax.set_xticks(ticks)\nax.set_yticks(ticks)\nax.set_xticklabels(Train.columns)\nax.set_yticklabels(Train.columns)\nplt.show()","execution_count":56,"outputs":[{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"# Scatter Plot Matrix\n\nA scatter plot shows the relationship between two variables as dots in two dimensions, one axis for each attribute. You can create a scatter plot for each pair of attributes in your data. Drawing all these scatter plots together is called a scatter plot matrix. Scatter plots are useful for spotting structured relationships between variables, like whether you could summarize the relationship between two variables with a line. Attributes with structured relationships may also be correlated and good candidates for removal from your dataset."},{"metadata":{"trusted":true},"cell_type":"code","source":"#you can use vars to compare two variable and hue to put colours\nsns.pairplot(Train,hue='CLASS',vars=['FULL_Charge','FULL_AcidicMolPerc'])\n#check on the seaborn(seaborn.pydata.org-dev/generated/seaborn.boxplot.html)","execution_count":57,"outputs":[{"output_type":"execute_result","execution_count":57,"data":{"text/plain":""},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"```mo = pd.DataFrame(out_model)\nmo.to_csv(\"xyz.csv\")\n```"},{"metadata":{},"cell_type":"markdown","source":"# Prepare Your Data For Machine Learning\nMany machine learning algorithms make assumptions about your data. It is often a very good idea to prepare your data in such way to best expose the structure of the problem to the machine learning algorithms that you intend to use. In this chapter you will discover how to prepare your data for machine learning in Python using scikit-learn. After completing this lesson you will know how to:\n\n1. Rescale data.\n2. Standardize data.\n3. Normalize data.\n4. Binarize data.\n### Need For Data Pre-processing\nYou almost always need to pre-process your data. It is a required step. A difficulty is that different algorithms make different assumptions about your data and may require different transforms. Further, when you follow all of the rules and prepare your data, sometimes algorithms can deliver better results without pre-processing. Generally, I would recommend creating many different views and transforms of your data, then exercise a handful of algorithms on each view of your dataset. This will help you to ush out which data transforms might be better at exposing the structure of your problem in general.\n\n### The steps involved are as below:\n\nSplit the dataset into the input and output variables for machine learning.\nApply a pre-processing transform to the input variables.\nSummarize the data to show the change.\nThe scikit-learn library provides two standard idioms for transforming data. Each are useful in di\u000berent circumstances. The transforms are calculated in such a way that they can be applied to your training data and any samples of data you may have in the future. The scikit-learn documentation has some information on how to use various di\u000berent pre-processing methods:\n\nThe Fit and Multiple Transform method is the preferred approach. You call the fit() function to prepare the parameters of the transform once on your data. Then later you can use the transform() function on the same data to prepare it for modeling and again on the test or validation dataset or new data that you may see in the future. The Combined Fit-And-Transform is a convenience that you can use for one o\u000b tasks. This might be useful if you are interested in plotting or summarizing the transformed data.\n\n### Rescale Data\nWhen your data is comprised of attributes with varying scales, many machine learning algorithms can bene\ft from rescaling the attributes to all have the same scale. Often this is referred to as normalization and attributes are often rescaled into the range between 0 and 1. This is useful for optimization algorithms used in the core of machine learning algorithms like gradient descent. It is also useful for algorithms that weight inputs like regression and neural networks and algorithms that use distance measures like k-Nearest Neighbors. You can rescale your data using scikit-learn using the MinMaxScaler class\n\n### NOTE: Since my graph and summary data shows varying means and Gaussian distribution. i would use Standardize data method\n\n\n\n### Standardize of Data\nStandardization is a useful technique to transform attributes with a Gaussian distribution and differing means and standard deviations to a standard Gaussian distribution with a mean of 0 and a standard deviation of 1. It is most suitable for techniques that assume a Gaussian distribution in the input variables and work better with rescaled data, such as linear regression, logistic regression and linear discriminate analysis. You can standardize data using scikit-learn with the StandardScaler class3."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.preprocessing import StandardScaler\n\narray2 = Train.values\n# separate array into input and output components\nX = array2[:,0:11]\nY = array2[:,11]\nscaler = StandardScaler().fit(X)\nrescaledX = scaler.transform(X)\n# summarize transformed data\n#set_printoptions(precision=3)\nprint(rescaledX[0:5,:])","execution_count":58,"outputs":[{"output_type":"stream","text":"[[ 7.69712416e-01 -1.12341031e+00 -1.90047029e-01 1.37605977e-01\n -6.06718766e-01 -7.20629784e-01 -3.11684110e-01 -1.33070267e+00\n -2.25681314e-02 -3.60971652e-01 -9.25122883e-01]\n [ 5.07884366e-01 -4.10857567e-01 -3.76275096e-01 -2.43225309e-01\n -1.18128598e+00 -9.24503172e-01 3.20837658e+00 -1.30322672e+00\n -5.92370366e-01 9.02050407e-01 1.03699430e+00]\n [ 9.00626442e-01 -4.10857567e-01 -9.16336490e-01 -8.65106417e-03\n -1.05360437e+00 -4.63244125e-02 -3.11684110e-01 -1.30383154e+00\n -4.59030969e-01 -1.40916462e+00 2.31808537e+00]\n [ 7.69712416e-01 -5.74065761e-01 -7.11485617e-01 -8.70124978e-01\n 1.59370848e-01 6.27395116e-01 -3.11684110e-01 -1.30201709e+00\n -7.01486075e-01 -2.30020073e+00 6.98862456e-01]\n [ 1.42428254e+00 2.04070778e-03 -3.66963693e-01 -1.04957427e+00\n -4.79037163e-01 2.00315519e-01 -3.11684110e-01 -1.30184429e+00\n -7.71259861e-02 -1.97723618e+00 1.44656245e+00]]\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"# Feature Selection For Machine\nLearning The data features that you use to train your machine learning models have a huge in uence on the performance you can achieve. Irrelevant or partially relevant features can negatively impact model performance. In this chapter you will discover automatic feature selection techniques that you can use to prepare your machine learning data in Python with scikit-learn. After completing this lesson you will know how to use:\n\n## Univariate Selection.\nRecursive Feature Elimination.\nPrinciple Component Analysis.\nFeature Importance.\nFeature Selection\nFeature selection is a process where you automatically select those features in your data that contribute most to the prediction variable or output in which you are interested. Having irrelevant features in your data can decrease the accuracy of many models, especially linear algorithms like linear and logistic regression. Three benets of performing feature selection before modeling your data are:\n\nReduces Overffitting: Less redundant data means less opportunity to make decisions based on noise.\nImproves Accuracy: Less misleading data means modeling accuracy improves.\nReduces Training Time: Less data means that algorithms train faster.\nUnivariate Selection\nStatistical tests can be used to select those features that have the strongest relationship with the output variable. The scikit-learn library provides the SelectKBest class2 that can be used with a suite of different statistical tests to select a specific number of features. The example below uses the chi-squared (𝑐ℎ𝑖2) statistical test for non-negative features to select 4 of the best features from the Pima Indians onset of diabetes dataset.\n\nYou can see the scores for each attribute and the 4 attributes chosen (those with the highest scores): plas, test, mass and age. I got the names for the chosen attributes by manually mapping the index of the 4 highest scores to the index of the attribute names.\n\n# Recursive Feature Elimination method.\nThe Recursive Feature Elimination (or RFE) works by recursively removing attributes and building a model on those attributes that remain. It uses the model accuracy to identify which attributes (and combination of attributes) contribute the most to predicting the target attribute. You can learn more about the RFE class3 in the scikit-learn documentation. The example below uses RFE with the logistic regression algorithm to select the top 3 features. The choice of algorithm does not matter too much as long as it is skillful and consistent.\n\n### NOTE: Since i dont have much information about the interpretetion of my varaibles, Recursive Feature Elimination method would be the best. "},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.feature_selection import RFE\nfrom sklearn.linear_model import LogisticRegression\n\narray_1 = Train.values\nX = array_1[:,0:11]\nY = array_1[:,11]\n# feature extraction\nmodel = LogisticRegression()\nrfe = RFE(model, 10)\nfit = rfe.fit(X, Y)\nprint(\"Num Features: \", fit.n_features_)\nprint(\"Selected Features:\", fit.support_)\nprint(\"Feature Ranking: \", fit.ranking_)","execution_count":59,"outputs":[{"output_type":"stream","text":"Num Features: 10\nSelected Features: [ True True True True True True True True False True True]\nFeature Ranking: [1 1 1 1 1 1 1 1 2 1 1]\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"# Evaluate the Performance of Machine Learning Algorithms with Resampling\nYou need to know how well your algorithms perform on unseen data. The best way to evaluate the performance of an algorithm would be to make predictions for new data to which you already know the answers. The second best way is to use clever techniques from statistics called resampling methods that allow you to make accurate estimates for how well your algorithm will perform on new data. In this chapter you will discover how you can estimate the accuracy of your machine learning algorithms using resampling methods in Python and scikit-learn on the Pima Indians dataset. Let's get started.\n\n## Evaluate Machine Learning Algorithms\nWhy can't you train your machine learning algorithm on your dataset and use predictions from this same dataset to evaluate machine learning algorithms? The simple answer is overffitting. Imagine an algorithm that remembers every observation it is shown during training. If you evaluated your machine learning algorithm on the same dataset used to train the algorithm, then an algorithm like this would have a perfect score on the training dataset. But the predictions it made on new data would be terrible. We must evaluate our machine learning algorithms on data that is not used to train the algorithm. The evaluation is an estimate that we can use to talk about how well we think the algorithm may actually do in practice. It is not a guarantee of performance. Once we estimate the performance of our algorithm, we can then re-train the final algorithm on the entire training dataset and get it ready for operational use. Next up we are going to look at four different techniques that we can use to split up our training dataset and create useful estimates of performance for our machine learning algorithms:\n\n* Train and Test Sets.\n* k-fold Cross Validation.\n* Leave One Out Cross Validation.\n* Repeated Random Test-Train Splits.\n\n## Split into Train and Test Sets\nThe simplest method that we can use to evaluate the performance of a machine learning algorithm is to use different training and testing datasets. We can take our original dataset and split it into two parts. Train the algorithm on the train part, make predictions on the second part and evaluate the predictions against the expected results. The size of the split can depend on the size and species of your dataset, although it is common to use 67% of the data for training and the remaining 33% for testing. This algorithm evaluation technique is very fast. It is ideal for large datasets (millions of records) where there is strong evidence that both splits of the data are representative of the underlying problem. Because of the speed, it is useful to use this approach when the algorithm you are investigating is slow to train. A downside of this technique is that it can have a high variance. This means that di\u000berences in the training and test dataset can result in meaningful diferences in the estimate of accuracy. In the example below we split the Pima Indians dataset into 70%/30% splits for training and test and evaluate the accuracy of a Logistic Regression model."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import train_test_split\nfrom sklearn.linear_model import LogisticRegression\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\ntest_size = 0.30\nseed = 7\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\nrandom_state=seed)\nmodel = LogisticRegression()\nmodel.fit(X_train, Y_train)\nresult = model.score(X_test, Y_test)\nprint(\"Accuracy: \", (result*100.0))","execution_count":60,"outputs":[{"output_type":"stream","text":"Accuracy: 91.55701754385966\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"# K-fold Cross Validation\nCross validation is an approach that you can use to estimate the performance of a machine learning algorithm with less variance than a single train-test set split. It works by splitting the dataset into k-parts (e.g. k = 5 or k = 10). Each split of the data is called a fold. The algorithm is trained on k 1 folds with one held back and tested on the held back fold. This is repeated so that each fold of the dataset is given a chance to be the held back test set. After running cross validation you end up with k diferent performance scores that you can summarize using a mean and a standard deviation. The result is a more reliable estimate of the performance of the algorithm on new data. It is more accurate because the algorithm is trained and evaluated multiple times on different data. The choice of k must allow the size of each test partition to be large enough to be a reasonable sample of the problem, whilst allowing enough repetitions of the train-test evaluation of the algorithm to provide a fair estimate of the algorithms performance on unseen data. For modest sized datasets in the thousands or tens of thousands of records, k values of 3, 5 and 10 are common."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import KFold\nfrom sklearn.model_selection import cross_val_score\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n\nnum_folds = 10 #number of folds to use are 10\nseed = 7 #reproducibility\n\nkfold = KFold(n_splits=num_folds, random_state=seed)\nmodel = LogisticRegression()\nresults = cross_val_score(model, X, Y, cv=kfold)\n\nprint(f\"Accuracy:\", (results.mean()*100.0, results.std()*100.0))","execution_count":61,"outputs":[{"output_type":"stream","text":"Accuracy: (83.5359128018065, 27.08521320979506)\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"# Leave One Out Cross Validation\nYou can configure cross validation so that the size of the fold is 1 (k is set to the number of observations in your dataset). This variation of cross validation is called leave-one-out cross validation. The result is a large number of performance measures that can be summarized in an effort to give a more reasonable estimate of the accuracy of your model on unseen data. A downside is that it can be a computationally more expensive procedure than k-fold cross validation. In the example below we use leave-one-out cross validation."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import LeaveOneOut\nfrom sklearn.model_selection import cross_val_score\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\nnum_folds = 10\nloocv = LeaveOneOut()\nmodel = LogisticRegression()\nresults = cross_val_score(model, X, Y, cv=loocv)\nprint(\"Accuracy:\", (results.mean()*100.0, results.std()*100.0))","execution_count":62,"outputs":[{"output_type":"stream","text":"Accuracy: (91.4417379855168, 27.974673416141517)\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"# Repeated Random Test-Train Splits\nAnother variation on k-fold cross validation is to create a random split of the data like the train/test split described above, but repeat the process of splitting and evaluation of the algorithm multiple times, like cross validation. This has the speed of using a train/test split and the reduction in variance in the estimated performance of k-fold cross validation. You can also repeat the process many more times as needed to improve the accuracy. A down side is that repetitions may include much of the same data in the train or the test split from run to run, introducing redundancy into the evaluation. The example below splits the data into a 70%/30% train/test split and repeats the process 10 times."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import ShuffleSplit\nfrom sklearn.model_selection import cross_val_score\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\nn_splits = 10\ntest_size = 0.30\nseed = 7\nkfold = ShuffleSplit(n_splits=n_splits, test_size=test_size, random_state=seed)\nmodel = LogisticRegression()\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(\"Accuracy: \" , (results.mean()*100.0, results.std()*100.0))","execution_count":63,"outputs":[{"output_type":"stream","text":"Accuracy: (91.30482456140349, 0.5803122202806698)\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"# NOTE: What Techniques to Use When\nThis section lists some tips to consider what resampling technique to use in diferent circum- stances.\n\nGenerally k-fold cross validation is the gold standard for evaluating the performance of amachine learning algorithm on unseen data with k set to 3, 5, or 10.\nUsing a train/test split is good for speed when using a slow algorithm and producesperformance estimates with lower bias when using large datasets.\nTechniques like leave-one-out cross validation and repeated random splits can be usefulintermediates when trying to balance variance in the estimated performance, modeltraining speed and dataset size.\nThe best advice is to experiment and find a technique for your problem that is fast and produces reasonable estimates of performance that you can use to make decisions. If in doubt, use 10-fold cross validation.\n# Machine Learning Algorithm Performance Metrics\n\nThe metrics that you choose to evaluate your machine learning algorithms are very important.\nChoice of metrics in\nuences how the performance of machine learning algorithms is measured\nand compared. They in\nuence how you weight the importance of different characteristics in\nthe results and your ultimate choice of which algorithm to choose.\n\n## Algorithm Evaluation Metrics\nIn this lesson, various different algorithm evaluation metrics are demonstrated for both classification and regression type machine learning problems. In each recipe, the dataset is downloaded\ndirectly from the Machine Learning repository.\n\n## Classiffication Metrics\nClassiffication problems are perhaps the most common type of machine learning problem and as such there are a myriad of metrics that can be used to evaluate predictions for these problems. In this section we will review how to use the following metrics:\n\n* Classiffication Accuracy.\n* Logarithmic Loss.\n* Area Under ROC Curve.\n* Confusion Matrix.\n* Classiffication Report.\n\n## Classiffication Accuracy\nClassiffication accuracy is the number of correct predictions made as a ratio of all predictions made. This is the most common evaluation metric for classi\fcation problems, it is also the most misused. It is really only suitable when there are an equal number of observations in each class (which is rarely the case) and that all predictions and prediction errors are equally important, which is often not the case. Below is an example of calculating classiffication accuracy."},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\nkfold = KFold(n_splits=10, random_state=7)\nmodel = LogisticRegression()\nscoring = 'accuracy'\nresults = cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\nprint(\"Accuracy:\", (results.mean(), results.std()))","execution_count":64,"outputs":[{"output_type":"stream","text":"Accuracy: (0.835359128018065, 0.2708521320979506)\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"## Logarithmic Loss\nLogarithmic loss (or logloss) is a performance metric for evaluating the predictions of probabilities of membership to a given class. The scalar probability between 0 and 1 can be seen as a measure of confidence for a prediction by an algorithm. Predictions that are correct or incorrect are rewarded or punished proportionally to the confidence of the prediction."},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\nkfold = KFold(n_splits=10, random_state=7)\nmodel = LogisticRegression()\nscoring = 'neg_log_loss'\nresults = -cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\nprint(\"Logloss:\", (results.mean(), results.std()))","execution_count":65,"outputs":[{"output_type":"error","ename":"ValueError","evalue":"y_true contains only one label (1.0). Please provide the true labels explicitly through the labels argument.","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)","\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mmodel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mLogisticRegression\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0mscoring\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'neg_log_loss'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0mcross_val_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m,\u001b[0m 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753\u001b[0m \u001b[0mjob_idx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_jobs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 754\u001b[0;31m \u001b[0mjob\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_backend\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply_async\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbatch\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcallback\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 755\u001b[0m \u001b[0;31m# A job can complete so quickly than its callback is\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 756\u001b[0m \u001b[0;31m# called before we get here, causing self._jobs 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**self._kwargs)\n\u001b[1;32m 259\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 260\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sign\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_score_func\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_pred\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_kwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 261\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 262\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_factory_args\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/opt/conda/lib/python3.6/site-packages/sklearn/metrics/_classification.py\u001b[0m in \u001b[0;36mlog_loss\u001b[0;34m(y_true, y_pred, eps, normalize, sample_weight, labels)\u001b[0m\n\u001b[1;32m 2253\u001b[0m raise ValueError('y_true contains only one label ({0}). Please '\n\u001b[1;32m 2254\u001b[0m \u001b[0;34m'provide the true labels explicitly through the '\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2255\u001b[0;31m 'labels argument.'.format(lb.classes_[0]))\n\u001b[0m\u001b[1;32m 2256\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2257\u001b[0m raise ValueError('The labels array needs to contain at least two '\n","\u001b[0;31mValueError\u001b[0m: y_true contains only one label (1.0). Please provide the true labels explicitly through the labels argument."]}]},{"metadata":{},"cell_type":"markdown","source":"# Area Under ROC Curve\nArea under ROC Curve (or AUC for short) is a performance metric for binary classiffication problems. The AUC represents a model's ability to discriminate between positive and negative classes. An area of 1.0 represents a model that made all predictions perfectly. An area of 0.5 represents a model that is as good as random. ROC can be broken down into sensitivity and specificity. A binary classiffication problem is really a trade-off between sensitivity and specificity.\n\n* Sensitivity is the true positive rate also called the recall. It is the number of instances from the positive (first) class that actually predicted correctly.\n\n* Specificity is also called the true negative rate. Is the number of instances from the negative (second) class that were actually predicted correctly."},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\nkfold = KFold(n_splits=10, random_state=7)\nmodel = LogisticRegression()\nscoring = 'roc_auc'\nresults = cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\nprint(\"AUC:\", (results.mean(), results.std()))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Confusion Matrix\nThe confusion matrix is a handy presentation of the accuracy of a model with two or more classes. The table presents predictions on the x-axis and accuracy outcomes on the y-axis. The cells of the table are the number of predictions made by a machine learning algorithm. For example, a machine learning algorithm can predict 0 or 1 and each prediction may actually have been a 0 or 1. Predictions for 0 that were actually 0 appear in the cell for prediction = 0 and actual = 0, whereas predictions for 0 that were actually 1 appear in the cell for prediction = 0 and actual = 1. And so on."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.metrics import confusion_matrix\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\ntest_size = 0.30\nseed = 7\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\nrandom_state=seed)\n\nmodel = LogisticRegression()\nmodel.fit(X_train, Y_train)\n\npredicted = model.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nprint(matrix)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Classiffication Report\nThe scikit-learn library provides a convenience report when working on classiffication problems to give you a quick idea of the accuracy of a model using a number of measures. The classification report() function displays the precision, recall, F1-score and support for each class. "},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.metrics import classification_report\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\ntest_size = 0.30\nseed = 7\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\nrandom_state=seed)\nmodel = LogisticRegression()\nmodel.fit(X_train, Y_train)\npredicted = model.predict(X_test)\nreport = classification_report(Y_test, predicted)\nprint(report)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Spot-Check Classiffication Algorithms.\nSpot-checking is a way of discovering which algorithms perform well on your machine learning problem. You cannot know which algorithms are best suited to your problem beforehand. You must trial a number of methods and focus attention on those that prove themselves the most promising.\n\n1. How to spot-check machine learning algorithms on a classi\fcation problem.\n2. How to spot-check two linear classification algorithms.\n3. How to spot-check four nonlinear classification algorithms.\n\nAlgorithm Spot-Checking\nYou cannot know which algorithm will work best on your dataset beforehand. You must use trial and error to discover a shortlist of algorithms that do well on your problem that you can then double down on and tune further. I call this process spot-checking. The question is not: What algorithm should I use on my dataset? Instead it is: What algorithms should I spot-check on my dataset? You can guess at what algorithms might do well on your dataset, and this can be a good starting point. I recommend trying a mixture of algorithms and see what is good at picking out the structure in your data. Below are some suggestions when spot-checking algorithms on your dataset:\n\nTry a mixture of algorithm representations (e.g. instances and trees).\n\nTry a mixture of learning algorithms (e.g. di\u000berent algorithms for learning the same type of representation).\n\nTry a mixture of modeling types (e.g. linear and nonlinear functions or parametric and nonparametric).\n\nAlgorithms Overview\nWe are going to take a look at six classi\fcation algorithms that you can spot-check on your dataset. Starting with two linear machine learning algorithms:\n\nLogistic Regression.\nLinear Discriminant Analysis.\nThen looking at four nonlinear machine learning algorithms:\n\nk-Nearest Neighbors.\nNaive Bayes.\nClassi\fcation and Regression Trees.\nSupport Vector Machines.\nLinear Machine Learning Algorithms\nThis section demonstrates minimal recipes for how to use two linear machine learning algorithms: logistic regression and linear discriminant analysis.\n\nLogistic Regression\nLogistic regression assumes a Gaussian distribution for the numeric input variables and can model binary classiffication problems. You can construct a logistic regression model using the LogisticRegression class."},{"metadata":{"trusted":true},"cell_type":"code","source":"# Logistic Regression Classification\nfrom pandas import read_csv\nfrom sklearn.model_selection import KFold\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.linear_model import LogisticRegression\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\nnum_folds = 10\nkfold = KFold(n_splits=10, random_state=7)\nmodel = LogisticRegression()\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Linear Discriminant Analysis\nLinear Discriminant Analysis or LDA is a statistical technique for binary and multiclass classiffication. It too assumes a Gaussian distribution for the numerical input variables. You can construct an LDA model using the LinearDiscriminantAnalysis class"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\nnum_folds = 10\nkfold = KFold(n_splits=10, random_state=7)\nmodel = LinearDiscriminantAnalysis()\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Nonlinear Machine Learning Algorithms\nThis section demonstrates minimal recipes for how to use 4 nonlinear machine learning algorithms.\n\n## k-Nearest Neighbors\nThe k-Nearest Neighbors algorithm (or KNN) uses a distance metric to find the k most similar instances in the training data for a new instance and takes the mean outcome of the neighbors as the prediction. You can construct a KNN model using the KNeighborsClassifier class."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.neighbors import KNeighborsClassifier\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\nnum_folds = 10\nkfold = KFold(n_splits=10, random_state=7)\nmodel = KNeighborsClassifier()\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Naive Bayes\nNaive Bayes calculates the probability of each class and the conditional probability of each class given each input value. These probabilities are estimated for new data and multiplied together, assuming that they are all independent (a simple or naive assumption). When working with real-valued data, a Gaussian distribution is assumed to easily estimate the probabilities for input variables using the Gaussian Probability Density Function. You can construct a Naive Bayes model using the GaussianNB class4."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.naive_bayes import GaussianNB\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\nkfold = KFold(n_splits=10, random_state=7)\nmodel = GaussianNB()\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Classiffication and Regression Trees\nClassiffication and Regression Trees (CART or just decision trees) construct a binary tree from the training data. Split points are chosen greedily by evaluating each attribute and each value of each attribute in the training data in order to minimize a cost function (like the Gini index). You can construct a CART model using the DecisionTreeClassifier class"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.tree import DecisionTreeClassifier\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\nkfold = KFold(n_splits=10, random_state=7)\nmodel = DecisionTreeClassifier()\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Support Vector Machines\nSupport Vector Machines (or SVM) seek a line that best separates two classes. Those data instances that are closest to the line that best separates the classes are called support vectors and in uence where the line is placed. SVM has been extended to support multiple classes. Of particular importance is the use of di\u000berent kernel functions via the kernel parameter."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.svm import SVC\nfrom sklearn.metrics import matthews_corrcoef\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\nkfold = KFold(n_splits=10)\nmodel = SVC()\nscoring = 'acuracy'\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())\n\ntest_set = Test.values\nmodel.fit(X, Y)\noutput = model.predict(test_set)\n\nmcc = matthews_corrcoef(model.predict(X), Y)\nprint('MCC: ',mcc)\n\nfinalreport1 = pd.DataFrame(output)\nfinalreport1.columns = ['CLASS']\nfinalreport1.index.name = 'Index'\nfinalreport1['CLASS'] = finalreport1['CLASS'].map({0.0:False, 1.0:True})\n\nfinalreport1.to_csv('finalreport1_sv.csv')\n\nprint(finalreport1['CLASS'].unique())\nprint('False: ',finalreport1.groupby('CLASS').size()[0].sum())\nprint('True: ',finalreport1.groupby('CLASS').size()[1].sum())","execution_count":69,"outputs":[{"output_type":"stream","text":"0.8350280093798853\nMCC: 0.8187103751493263\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"# Spot-Check Regression Algorithms\n* Linear Regression.\n* Ridge Regression.\n* LASSO Linear Regression.\n* Elastic Net Regression.\n\n## Then looking at three nonlinear machine learning algorithms:\n\n* k-Nearest Neighbors.\n* Classification and Regression Trees.\n* Support Vector Machines.\n* Linear Regression\n\nLinear regression assumes that the input variables have a Gaussian distribution. It is also assumed that input variables are relevant to the output variable and that they are not highly correlated with each other (a problem called collinearity). You can construct a linear regression model using the LinearRegression class."},{"metadata":{"trusted":true},"cell_type":"code","source":"import pandas as pd\ndf = pd.DataFrame([0]*16)\ndf.to_csv('results.csv', index=False, header=False)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"raw","source":""}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4} \ No newline at end of file From af3321966407ab5eb1ce27cbbda2854bb8a48f35 Mon Sep 17 00:00:00 2001 From: Maria_Magdalene_Namaganda Date: Thu, 12 Mar 2020 20:02:59 +0300 Subject: [PATCH 17/29] This is Maria's updated version --- Fezile Dlamini.ipynb | 778 -------- KAYAGA NASHIM MILVAT.ipynb | 2767 --------------------------- kakooza trevor Starter Kernel.ipynb | 1 - 3 files changed, 3546 deletions(-) delete mode 100644 Fezile Dlamini.ipynb delete mode 100644 KAYAGA NASHIM MILVAT.ipynb delete mode 100644 kakooza trevor Starter Kernel.ipynb diff --git a/Fezile Dlamini.ipynb b/Fezile Dlamini.ipynb deleted file mode 100644 index 2dd9fe7..0000000 --- a/Fezile Dlamini.ipynb +++ /dev/null @@ -1,778 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", - "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" - }, - "outputs": [], - "source": [ - "# This Python 3 environment comes with many helpful analytics libraries installed\n", - "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", - "# For example, here's several helpful packages to load in \n", - "\n", - "import numpy as np # linear algebra\n", - "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", - "\n", - "# Input data files are available in the \"../input/\" directory.\n", - "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", - "\n", - "import os\n", - "for dirname, _, filenames in os.walk('/kaggle/input'):\n", - " for filename in filenames:\n", - " print(os.path.join(dirname, filename))\n", - "\n", - "# Any results you write to the current directory are saved as output." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Importing Libraries" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0", - "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a" - }, - "outputs": [], - "source": [ - "###Importing libraries\n", - "import pandas\n", - "import scipy\n", - "import numpy\n", - "import matplotlib\n", - "import sklearn\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Loading some libraries\n", - "### These are some of the libraries I think I will need" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from pandas import read_csv\n", - "from pandas.plotting import scatter_matrix\n", - "from matplotlib import pyplot\n", - "from sklearn.model_selection import train_test_split\n", - "from sklearn.model_selection import cross_val_score\n", - "from sklearn.model_selection import StratifiedKFold\n", - "from sklearn.metrics import classification_report\n", - "from sklearn.metrics import confusion_matrix\n", - "from sklearn.metrics import accuracy_score\n", - "from sklearn.linear_model import LogisticRegression\n", - "from sklearn.tree import DecisionTreeClassifier\n", - "from sklearn.neighbors import KNeighborsClassifier\n", - "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", - "from sklearn.naive_bayes import GaussianNB\n", - "from sklearn.svm import SVC" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import warnings\n", - "warnings.filterwarnings('ignore')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Loading My Dataset\n", - "\n", - "##### I am going to first use my training dataset, then the test dataset last." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "train = pandas.read_csv('/kaggle/input/ace-class-assignment/AMP_TrainSet.csv')\n", - "train\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "test= pandas.read_csv('/kaggle/input/ace-class-assignment/Test.csv')\n", - "test" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Inspecting my train dataset" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "train.shape" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "train.isnull().sum() ###this will show the number of null values in my data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "train.count() #returns number of non-null values in my data" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "##### It seems i have no missing values in my data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "train.describe() #returns summary of the whole data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "train.info() #It returns range, column, number of non-null objects of each column, datatype and memory usage" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "##### This shows that my dataset has 3038 rows (instances) and 12 columns (attributes)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "##### I will also take a look at how many instances i have for each class" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "train.groupby('CLASS').size()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "train.groupby('CLASS').size().plot(kind='bar')\n", - "pyplot.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### I have two groups of classes, each with 1519 instances" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# DATA VISUALISATION" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### I will start with univariate plots to see each indiviadual variable" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "train.hist(figsize=(16,16))\n", - "pyplot.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "train.corr(method='pearson')['CLASS'] #Here I tried to see the correlation of all attributes with the class" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Multivariate " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "correlations = train.corr()\n", - "# plot correlation matrix\n", - "fig = pyplot.figure()\n", - "ax = fig.add_subplot(111)\n", - "cax = ax.matshow(correlations, vmin=-1, vmax=1)\n", - "fig.colorbar(cax)\n", - "ticks = np.arange(0,9,1)\n", - "ax.set_xticks(ticks)\n", - "ax.set_yticks(ticks)\n", - "ax.set_xticklabels(train.columns)\n", - "ax.set_yticklabels(train.columns)\n", - "pyplot.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### i did this plot in order to see which features are highly correlated as this can be a problem in soome models if some features are used together whereas they are highly correlated." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# EVALUATING ALGORITHMS\n", - "#### I will now evaluate some algorithms and estimate their accuracy on unseen data." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Building models" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "array = train.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "test_size = 0.32\n", - "seed = 3\n", - "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", - "random_state=seed)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "len(X_test)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "\n", - "\n", - "models = []\n", - "models.append(('LR', LogisticRegression(solver='liblinear', multi_class='ovr')))\n", - "models.append(('LDA', LinearDiscriminantAnalysis()))\n", - "models.append(('KNN', KNeighborsClassifier()))\n", - "models.append(('CART', DecisionTreeClassifier()))\n", - "models.append(('NB', GaussianNB()))\n", - "models.append(('SVM', SVC(gamma='auto')))\n", - "# evaluate each model in turn\n", - "results = []\n", - "names = []\n", - "for name, model in models:\n", - " kfold = StratifiedKFold(n_splits=10)\n", - " cv_results = cross_val_score(model, X_train, Y_train, cv=kfold, scoring='accuracy')\n", - " results.append(cv_results)\n", - " names.append(name)\n", - " print('%s: %f (%f)' % (name, cv_results.mean(), cv_results.std()))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Compare Algorithms\n", - "pyplot.boxplot(results, labels=names)\n", - "pyplot.title('Algorithm Comparison')\n", - "pyplot.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### from here, NB is the best performing." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Make predictions on validation dataset\n", - "model = GaussianNB()\n", - "model.fit(X_train, Y_train)\n", - "predictions = model.predict(X_test)\n", - "print(predictions)\n", - "\n", - "#from sklearn.metrics import matthews_corrcoef\n", - "#print('MCC', matthews_corrcoef(model.predict(X_test), Y_test))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#with all features\n", - "from sklearn.model_selection import train_test_split\n", - "from sklearn.naive_bayes import GaussianNB\n", - "\n", - "array = train.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "test_size = 0.32\n", - "seed = 3\n", - "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", - "random_state=seed)\n", - "model = GaussianNB()\n", - "model.fit(X_train, Y_train)\n", - "result = model.score(X_test, Y_test)\n", - "print(\"Accuracy: \", (result*100.0))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Evaluate predictions\n", - "print(accuracy_score(Y_test, predictions))\n", - "print(confusion_matrix(Y_test, predictions))\n", - "print(classification_report(Y_test, predictions))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "test" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "Y=train.CLASS\n", - "X=train.drop(\"CLASS\",axis=1)\n", - "OUTPUT=model.fit(X, Y).predict(test.values)\n", - "OUTPUT_1=pd.DataFrame(OUTPUT)\n", - "OUTPUT_1.columns=[\"CLASS\"]\n", - "OUTPUT_1.index.name=\"Index\"\n", - "OUTPUT_1[\"CLASS\"]=OUTPUT_1[\"CLASS\"].map({0.0:False,1.0:True})\n", - "OUTPUT_1.to_csv(\"output\")\n", - "print(OUTPUT_1[\"CLASS\"].unique())\n", - "print(OUTPUT_1[\"CLASS\"].nunique())\n", - "print(OUTPUT_1.groupby(\"CLASS\").size()[0].sum())\n", - "print(OUTPUT_1.groupby(\"CLASS\").size()[1].sum())" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#feature selection using feature importance\n", - "X = train.iloc[:,0:11] #independent columns\n", - "y = train.iloc[:,-1] #target column\n", - "from sklearn.ensemble import ExtraTreesClassifier\n", - "import matplotlib.pyplot as plt\n", - "model = ExtraTreesClassifier()\n", - "model.fit(X,y)\n", - "print(model.feature_importances_) #use inbuilt class feature_importances of tree based classifiers\n", - "#plot graph of feature importances for better visualization\n", - "feat_importances = pd.Series(model.feature_importances_, index=X.columns)\n", - "feat_importances.nlargest(10).plot(kind='barh')\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "train.columns" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "newtrain=train.drop([ 'FULL_AURR980107', 'FULL_OOBM850104', 'NT_EFC195', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104'], axis=1)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "newtest=test.drop([ 'FULL_AURR980107', 'FULL_OOBM850104', 'NT_EFC195', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104'], axis=1)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "newtrain" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "array = newtrain.values\n", - "X = array[:,0:5]\n", - "Y = array[:,-1]\n", - "test_size = 0.32\n", - "seed = 3\n", - "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", - "random_state=seed)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "models = []\n", - "models.append(('LR', LogisticRegression(solver='liblinear', multi_class='ovr')))\n", - "models.append(('LDA', LinearDiscriminantAnalysis()))\n", - "models.append(('KNN', KNeighborsClassifier()))\n", - "models.append(('CART', DecisionTreeClassifier()))\n", - "models.append(('NB', GaussianNB()))\n", - "models.append(('SVM', SVC(gamma='auto')))\n", - "# evaluate each model in turn\n", - "results = []\n", - "names = []\n", - "for name, model in models:\n", - " kfold = StratifiedKFold(n_splits=23, shuffle=True)\n", - " cv_results = cross_val_score(model, X_train, Y_train, cv=kfold, scoring='accuracy')\n", - " results.append(cv_results)\n", - " names.append(name)\n", - " print('%s: %f (%f)' % (name, cv_results.mean(), cv_results.std()))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "model = GaussianNB()\n", - "model.fit(X_train, Y_train)\n", - "result = model.score(X_test, Y_test)\n", - "print(\"Accuracy: \", (result*100.0))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Evaluate predictions\n", - "print(accuracy_score(Y_test, predictions))\n", - "print(confusion_matrix(Y_test, predictions))\n", - "print(classification_report(Y_test, predictions))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "Y=newtrain.CLASS\n", - "X=newtrain.drop(\"CLASS\",axis=1)\n", - "OUTPUT=model.fit(X, Y).predict(newtest.values)\n", - "OUTPUT_1=pd.DataFrame(OUTPUT)\n", - "OUTPUT_1.columns=[\"CLASS\"]\n", - "OUTPUT_1.index.name=\"Index\"\n", - "OUTPUT_1[\"CLASS\"]=OUTPUT_1[\"CLASS\"].map({0.0:False,1.0:True})\n", - "OUTPUT_1.to_csv(\"out1\")\n", - "print(OUTPUT_1[\"CLASS\"].unique())\n", - "print(OUTPUT_1[\"CLASS\"].nunique())\n", - "print(OUTPUT_1.groupby(\"CLASS\").size()[0].sum())\n", - "print(OUTPUT_1.groupby(\"CLASS\").size()[1].sum())" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#checking accuracy using data with selected features from feature importance\n", - "from sklearn.model_selection import train_test_split\n", - "from sklearn.naive_bayes import GaussianNB\n", - "from sklearn.metrics import matthews_corrcoef\n", - "\n", - "array = train.values\n", - "X = array[:,[0,1,3,5,7]]\n", - "Y = array[:,11]\n", - "test_size = 0.32\n", - "seed = 3\n", - "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", - "random_state=seed)\n", - "model = GaussianNB()\n", - "model.fit(X_train, Y_train)\n", - "result = model.score(X_test, Y_test)\n", - "prediction=model.predict(X_test)\n", - "matrix=matthews_corrcoef(Y_test,prediction)\n", - "print(\"Accuracy: \", (result*100.0))\n", - "print(matrix)\n", - "\n", - "# making predictions on the test data\n", - "\n", - "#output=model.predict(test.values)\n", - "#output1=pd.DataFrame(output)\n", - "#output1.columns=['CLASS']\n", - "#output1.index.name='Index'\n", - "#output1['CLASS']=output1['CLASS'].map({0.0:False, 1.0:True})\n", - "\n", - "#print(output1['CLASS'].unique())\n", - "#print(output1['CLASS'].nunique())\n", - "\n", - "#print(output1.groupby('CLASS').size()[0].sum())\n", - "#print(output1.groupby('CLASS').size()[1].sum())\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "array2 = np.array(test)\n", - "X = array2[:,[0,1,3,5,7]]\n", - "x_t=array[:,[0,1,3,5,7]]\n", - "y_t=array[:,11]\n", - "\n", - "#array3 = train.values\n", - "#X_t = array3[:,[0,1,3,5,7]]\n", - "#Y_t=array3[:,10]\n", - "test_size = 0.32\n", - "seed = 3\n", - "#X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", - "#random_state=seed)\n", - "test=array3[:,[0,1,3,5,7]]\n", - "model = GaussianNB()\n", - "\n", - "#result = model.score(X_t, Y_t)\n", - "model.fit(x_t, y_t)\n", - "prediction=model.predict(X)\n", - "\n", - "#matrix=matthews_corrcoef(Y_t,prediction)\n", - "#print(\"Accuracy: \", (result*100.0))\n", - "#print(matrix)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## FEATURE SELECTION" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#feature selection using Logistic regression\n", - "from sklearn.feature_selection import RFE\n", - "from sklearn.linear_model import LogisticRegression\n", - "\n", - "array_1 = train.values\n", - "X = array_1[:,0:11]\n", - "Y = array_1[:,11]\n", - "# feature extraction\n", - "model = LogisticRegression()\n", - "rfe = RFE(model, 5)\n", - "fit = rfe.fit(X, Y)\n", - "print(\"Num Features: \", fit.n_features_)\n", - "print(\"Selected Features:\", fit.support_)\n", - "print(\"Feature Ranking: \", fit.ranking_)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#checking accuracy using data with selected features from feature importance\n", - "from sklearn.model_selection import train_test_split\n", - "from sklearn.naive_bayes import GaussianNB\n", - "\n", - "array = train.values\n", - "X = array[:,[0,2,3,5,7]]\n", - "Y = array[:,11]\n", - "test_size = 0.32\n", - "seed = 3\n", - "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", - "random_state=seed)\n", - "model = GaussianNB()\n", - "model.fit(X_train, Y_train)\n", - "result = model.score(X_test, Y_test)\n", - "print(\"Accuracy: \", (result*100.0))\n", - "\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#CHECKING ACCURACY WITH ALL FEATURES\n", - "array = train.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "test_size = 0.32\n", - "seed = 3\n", - "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", - "random_state=seed)\n", - "model = GaussianNB()\n", - "model.fit(X_train, Y_train)\n", - "result = model.score(X_test, Y_test)\n", - "print(\"Accuracy: \", (result*100.0))\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "train.head(5)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.3" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/KAYAGA NASHIM MILVAT.ipynb b/KAYAGA NASHIM MILVAT.ipynb deleted file mode 100644 index 60d7103..0000000 --- a/KAYAGA NASHIM MILVAT.ipynb +++ /dev/null @@ -1,2767 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", - "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "/kaggle/input/ace-class-assignment/Test.csv\n", - "/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\n" - ] - } - ], - "source": [ - "# This Python 3 environment comes with many helpful analytics libraries installed\n", - "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", - "# For example, here's several helpful packages to load in \n", - "\n", - "import numpy as np # linear algebra\n", - "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", - "import matplotlib.pyplot as plt\n", - "import seaborn as sns\n", - "# Input data files are available in the \"../input/\" directory.\n", - "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", - "\n", - "import os\n", - "for dirname, _, filenames in os.walk('/kaggle/input'):\n", - " for filename in filenames:\n", - " print(os.path.join(dirname, filename))\n", - "\n", - "# Any results you write to the current directory are saved as output." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0", - "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a" - }, - "outputs": [], - "source": [ - "import warnings\n", - "warnings.filterwarnings('ignore')" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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count3038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.000000
mean2.0602378.5215200.97141073.6687600.994007-2.4329270.08854515.68323373.6508285.9113611.2352550.500000
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- "\n", - " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 CLASS \n", - "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", - "mean 73.650828 5.911361 1.235255 0.500000 \n", - "std 9.166092 0.693689 0.210012 0.500082 \n", - "min 42.778000 3.533000 0.785000 0.000000 \n", - "25% 67.556000 5.459250 1.082000 0.000000 \n", - "50% 73.697000 5.925500 1.184000 0.500000 \n", - "75% 79.778000 6.382000 1.351000 1.000000 \n", - "max 103.167000 8.662000 2.192000 1.000000 " - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#Generate descriptive statistics that summarize the central tendency, dispersion, and shape of a dataset’s distribution, excluding NaN values\n", - "data.describe()" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "FULL_Charge 0\n", - "FULL_AcidicMolPerc 0\n", - "FULL_AURR980107 0\n", - "FULL_DAYM780201 0\n", - "FULL_GEOR030101 0\n", - 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "#need to know how balanced the class values are\n", - "data.groupby('CLASS').size().plot(kind='bar')" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201FULL_GEOR030101FULL_OOBM850104NT_EFC195AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CT_RACS820104CLASS
FULL_Charge1.000000-0.612996-0.490977-0.434603-0.058725-0.2837580.0880680.355477-0.365374-0.0905700.2329290.534602
FULL_AcidicMolPerc-0.6129961.0000000.7947960.5414810.1152010.513344-0.143168-0.4315900.4496210.002334-0.213543-0.598816
FULL_AURR980107-0.4909770.7947961.0000000.5482530.3461390.462712-0.169540-0.4260970.4562600.032958-0.403599-0.584111
FULL_DAYM780201-0.4346030.5414810.5482531.0000000.0101180.334778-0.090058-0.4087930.8941910.055915-0.326792-0.554838
FULL_GEOR030101-0.0587250.1152010.3461390.0101181.0000000.319157-0.230417-0.160269-0.0290850.040480-0.151935-0.260470
FULL_OOBM850104-0.2837580.5133440.4627120.3347780.3191571.000000-0.230561-0.3362970.275640-0.4527690.155304-0.453287
NT_EFC1950.088068-0.143168-0.169540-0.090058-0.230417-0.2305611.0000000.178683-0.0368440.1459240.0808980.260702
AS_MeanAmphiMoment0.355477-0.431590-0.426097-0.408793-0.160269-0.3362970.1786831.000000-0.3223780.0255800.1715240.693552
AS_DAYM780201-0.3653740.4496210.4562600.894191-0.0290850.275640-0.036844-0.3223781.0000000.045562-0.256060-0.437168
AS_FUKS010112-0.0905700.0023340.0329580.0559150.040480-0.4527690.1459240.0255800.0455621.000000-0.4452840.033432
CT_RACS8201040.232929-0.213543-0.403599-0.326792-0.1519350.1553040.0808980.171524-0.256060-0.4452841.0000000.267652
CLASS0.534602-0.598816-0.584111-0.554838-0.260470-0.4532870.2607020.693552-0.4371680.0334320.2676521.000000
\n", - "
" - ], - "text/plain": [ - " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 \\\n", - "FULL_Charge 1.000000 -0.612996 -0.490977 \n", - "FULL_AcidicMolPerc -0.612996 1.000000 0.794796 \n", - "FULL_AURR980107 -0.490977 0.794796 1.000000 \n", - "FULL_DAYM780201 -0.434603 0.541481 0.548253 \n", - "FULL_GEOR030101 -0.058725 0.115201 0.346139 \n", - "FULL_OOBM850104 -0.283758 0.513344 0.462712 \n", - "NT_EFC195 0.088068 -0.143168 -0.169540 \n", - "AS_MeanAmphiMoment 0.355477 -0.431590 -0.426097 \n", - "AS_DAYM780201 -0.365374 0.449621 0.456260 \n", - "AS_FUKS010112 -0.090570 0.002334 0.032958 \n", - "CT_RACS820104 0.232929 -0.213543 -0.403599 \n", - "CLASS 0.534602 -0.598816 -0.584111 \n", - "\n", - " FULL_DAYM780201 FULL_GEOR030101 FULL_OOBM850104 \\\n", - "FULL_Charge -0.434603 -0.058725 -0.283758 \n", - "FULL_AcidicMolPerc 0.541481 0.115201 0.513344 \n", - "FULL_AURR980107 0.548253 0.346139 0.462712 \n", - "FULL_DAYM780201 1.000000 0.010118 0.334778 \n", - "FULL_GEOR030101 0.010118 1.000000 0.319157 \n", - "FULL_OOBM850104 0.334778 0.319157 1.000000 \n", - "NT_EFC195 -0.090058 -0.230417 -0.230561 \n", - "AS_MeanAmphiMoment -0.408793 -0.160269 -0.336297 \n", - "AS_DAYM780201 0.894191 -0.029085 0.275640 \n", - "AS_FUKS010112 0.055915 0.040480 -0.452769 \n", - "CT_RACS820104 -0.326792 -0.151935 0.155304 \n", - "CLASS -0.554838 -0.260470 -0.453287 \n", - "\n", - " NT_EFC195 AS_MeanAmphiMoment AS_DAYM780201 \\\n", - "FULL_Charge 0.088068 0.355477 -0.365374 \n", - "FULL_AcidicMolPerc -0.143168 -0.431590 0.449621 \n", - "FULL_AURR980107 -0.169540 -0.426097 0.456260 \n", - "FULL_DAYM780201 -0.090058 -0.408793 0.894191 \n", - "FULL_GEOR030101 -0.230417 -0.160269 -0.029085 \n", - "FULL_OOBM850104 -0.230561 -0.336297 0.275640 \n", - "NT_EFC195 1.000000 0.178683 -0.036844 \n", - "AS_MeanAmphiMoment 0.178683 1.000000 -0.322378 \n", - "AS_DAYM780201 -0.036844 -0.322378 1.000000 \n", - "AS_FUKS010112 0.145924 0.025580 0.045562 \n", - "CT_RACS820104 0.080898 0.171524 -0.256060 \n", - "CLASS 0.260702 0.693552 -0.437168 \n", - "\n", - " AS_FUKS010112 CT_RACS820104 CLASS \n", - "FULL_Charge -0.090570 0.232929 0.534602 \n", - "FULL_AcidicMolPerc 0.002334 -0.213543 -0.598816 \n", - "FULL_AURR980107 0.032958 -0.403599 -0.584111 \n", - "FULL_DAYM780201 0.055915 -0.326792 -0.554838 \n", - "FULL_GEOR030101 0.040480 -0.151935 -0.260470 \n", - "FULL_OOBM850104 -0.452769 0.155304 -0.453287 \n", - "NT_EFC195 0.145924 0.080898 0.260702 \n", - "AS_MeanAmphiMoment 0.025580 0.171524 0.693552 \n", - "AS_DAYM780201 0.045562 -0.256060 -0.437168 \n", - "AS_FUKS010112 1.000000 -0.445284 0.033432 \n", - "CT_RACS820104 -0.445284 1.000000 0.267652 \n", - "CLASS 0.033432 0.267652 1.000000 " - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#Its a good idea to review all the pairwise correlations of the attributes in the dataset because some machine learning algorithm like linear and logistic regression can suffer poor performance if there are highly c orrelated attributes in the dataset\n", - "data.corr(method='pearson')" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "#plot a heat map to show the correlation of the data\n", - "plt.figure(figsize=(8,8))\n", - "sns.heatmap(data.corr(method='pearson'))\n" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "FULL_Charge 0.534602\n", - "FULL_AcidicMolPerc -0.598816\n", - "FULL_AURR980107 -0.584111\n", - "FULL_DAYM780201 -0.554838\n", - "FULL_GEOR030101 -0.260470\n", - "FULL_OOBM850104 -0.453287\n", - "NT_EFC195 0.260702\n", - "AS_MeanAmphiMoment 0.693552\n", - "AS_DAYM780201 -0.437168\n", - "AS_FUKS010112 0.033432\n", - "CT_RACS820104 0.267652\n", - "CLASS 1.000000\n", - "Name: CLASS, dtype: float64" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#also checked the corelation in regards to the class since am trying to build a ML agorithm for that class\n", - "data.corr(method='pearson')['CLASS']" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": 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\n", 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gfLa2fa/K8S62PUjurwOeavt5ku4HnFr77wNYp/YKW/SH5izFAJIWAHe2GG9tSXez/fsm3vrA3SrH+IPtLwJfbNa/K7A3cLik02y/qHK8JwMvBm4dWS6gehOXpJtneomSpGp7PPBu4GzgCNuW9FTbL2shFixLCgDPB55s+zeSPgWcWzOQ7XcB75L0rtqJfAad7ivAhra/3Dx+r6RzgC9LegnLknBNHwfuDfyj7f8DkPQT29u0EAvKQXjgGcBnAGz/oq2LvGlK7h8ATgQ2k/QOyhnZm1uM99/A1yX9F2Xn+mvg6Moxlv6vNmfqxwPHN5dtz6scC8pZ0W22v7HChkiXthDvRuAxgy/PSLyrawezfXbTHvxq4HRJb6SdxDCwvqTtKc2ba9v+TbMdf5D0xzYC2j5I0hbA1gx9f21/s3KorvcVSbq37ZsAbJ/RNKt9FtikdjDbr5a0A3CspJOAD9HuvnKjpOcAPwOeCOwHIGkd2jnRmZ5mGQBJDwWeRkmKX7d9ScvxdgGe3sT7iu3TKq//H2y/t+Y655PmHsXJtldoM5V0qO03thh7C+DfgMW2H9BSjDNGFr3I9s8l3Qc4rY2iUJLeTbm6+wEwOIDY9lTfOJb0IuAK22eOLF8IvMX2K1qKuxbwKmBP4IG2799SnAdTTlDvB7zf9seb5X8OPNP2G6rHnJbkLmnc0fsW239oIdbalC/n02uvez6QdF9gC8qZyrXjzqxj9TX7z91s3zbrm1d93ZcCjxg0F7btrrKvSNoc2N72KZPellqmqVnmXGAr4NeUM+mNgJ9Lug54he1zagWy/UdJtw1fJrahaX45iNIEM6jPfB3weeDdtm+sHG974COUtsafNYu3lHQj8Pe2q7YTNzHvTblZvDRBUA6cVf+2oVidfZ5DcRdT9s07gMts/5BlNz1ruwJYF2g1uU9iX1nJthxpe/8W1vtQYDeG9s2m3b16i4CkVwD/Y/uypifVUcAewJXAvrbPqx1zmpL7l4ETB00jkp5JSRrHU7pJPrZyvN8BF0r6KvCbwULbr6kY43jgdMqd818ANHfP96XccKndn/i/gL+xfdbwQkmPa16r2vNI0l8BhwBfYVmC2Al4p6R/sf2JmvHo+POU9GfAYZR7CzsA3wE2lvQH4CW2q99XoBw0zpf0dYYSfOX9ErrfV2ZqVxfw7JqxmnhvpPRSOw4YNBtuSWmDP872uyuHfC3lJi5N3EcA2wDbU5prnlw53lQ1y6xQ2H6wTNL5th9VOd6+45bbrnZTVdKlth+yqq+tQbzLbG87w2uX235Q5XiXAo8dPWNu+jCfZfvBteN1/HmeR2kvvV7SNsD7bO/e3NT9R9vPrBmvidn6ftnE6Xpf+SNlZrbhriNunm9he73K8X4EbDfarCtpPeDimf72NYi3NEc1vanOsv3vzfOqXawHpunM/YbmaHtc83wv4NdN+2b1LpG2j266Jy603UbvAICrJP0TcPRQd6z7Ai8F2jjrO1XSlyiDJwbr3wr4K8qVUW1ifA+EO1n+S1xL15/n2ravbx7/lNKDBdtflfT+FuJ1tV9C9/vKFcDTbP909IU2elZR9sH7s+JUn5vTThfrO5t2/V9TOoW8Y+i1VnrLTFNyfxHlEv+k5vm3m2VrAy+sHUzSrsB7gfWAbSQ9Cnhr5V4JewEHAt/QsmHI/wecTAt/k+3XSHoWy9oZBVwDHN7SjaR3AOdK+grLEsRCSvPI21qI1+nnCSyR9DHg65TP9H8AJN2Dsl9W19F+OYl95f3AxpSD5Kh/bSHe6yhdnS9j+X3zQZTeM7UdDCyh7Bcn274YljbtXdFCvOlolmnOzt9t+x87jHkOsDPlJshgROyFtv+0q23og6YJ5s9ZPkGcZvvXE92wCiStC7wCeBhlOPlRzc349YHNbK/OBPCzxcx+WUnTDXJHlt83z7bdyhiFpk/7PYf3/cGJgO1basebijP35gvTdf2MO2zfpOVHj3V2JJT0Mtv/VXmda1OGdm9JGfL83aHX3my7du0cmh35uFnf2LI2Ps+mvfbDY5b/lhUv92vpZL+cxL6ykm15hu2v1l6v7Tspg7VG421oe3Rkbo14d1CaZWh6zOxEaX3YFbhv7XjTVDjsPEknS3qJhopDtRjvIpWBFWtL2lbSB4HvzvZLFf1LC+v8D+DPgF8BH5T0vqHX2vwsV6BSV6dLbXyeM5J0akur7mq/nDf7Ch0XtaMMEGuFpMdK+nfKwf9k4FvAQ1uJNQ3NMgAqZQBG2ZWLQQ3Fuwfwz8Cgx8NpwNtt/65ijAtmegl4sO2qtWwkXWD7Ec3jdShnnZtSumad6frFmWZKAqLUflkww+urG6/rz3OmHg4Cvmh785rxmpjD+6Uo++Xbau6XTZyu95WuC5W9fiXx/tl21ZIHKiVTXki5p3AspZTKErdXy2Z6knuXVIqSbQ1c3tbAlybO/1Hao0fbnwV8t/ZQaEk/tP3QkWUHN9uwWQvdv/4AfJLxzQYvsH3PyvG6/jz/CHyD8T1/Hme7lV4QXZjAvvJrZi5U9mnbVZstJP0OeA9l4NmoA2xXLcEt6XrgUsqN4y/a/p2kK9xSaQyYkjZ3AEl3pxTb2Q64+2B57TN3SS8H3gn8mNIbYX/bM51VrKkvUqrhnT9mO/6nhXhLJO3iZdX3sP1WSddSRiPWdgHwXtsXjb4gqY3SDl1/npdQBvpcNiZeG933BqNh3wQsYvnCYY+oHKrrfaXrQmXnAid5zMj2JgfUdj/K1dY+wPtV6hKtL2mdpi2+uqk5c5f0GeCHlBsQbwX+ErjE9msrx7kI2KkZmPIA4JO2H18zxl2FpCcDV83Qd3mx7SUT2KxqJL0AuHBcf3NJz7N90phfW9OYlwL/CFzIUH/sNnrm9JmkhwA3DI1TGH7tvm6xhk5zovocSqJ/EqUIYu3y3lOV3M+zvf2gLbDphnaa7Z0rx1lutNjo89qau+aD7liD2ivfc0v/MRpTT4PS77bVCptd6frz7Jqkb9t+UkexOt9XdBcpVDYg6V6U2liHVV/3tOzzkr5ne0dJ3wT+HvgF5Utbtc1KpRDZcNe9vYefu2IND5X6OB8GLmOoOBNlIMXf2/5KrVhNvOF6GtcMxdsbqF5Po7kRtx+wO2U04CBBfB742OjQ7wrxuv48Xw/cZPtjI8tfTem7XH2UqqSnUf4PR2vLfK5ynK73lbGFyih1e6oXKtOEiszNsC3VZyWD6UruL6cU7n8EpXDRhsDBto+oHGds7Y4B160tcwnwLNtXjizfBjjF9p/UitWst+t6GsdSvpxHs3yC2BfYxPZeleN1/XleBDza9u0jy+9GGQxTux0cSf9N6Tp3McuaZar3GpvAvnI+Mxcq+w9Xnk5T0mmUInNHe8Uic0+33dkk4JKutr1V7fVOzQ1V2//ZPPwG0Nod5prJew7WYVnSG/YzSlnX2rqup/For1is6xrgTLUzGXHXn6dHE3uz8PdN81AbHuluRqN2va9sMJrYAWyfKamNuX0X2T50JNYvgEMltdK9eiVaOcOemuTenA3twYq9BN5aOc4XWMmH7bo1PI4CzpZ0HMvXt9iLdgZudF1P49eS9gQ+24wGHAz53pMVuyvWMO7z3IrSlNDKQJhxN9+aduO2nCnpYbZbG2jT6Hpf6bpQ2VXqsMicyqC9cXlFtDA6FaarWebLwE3AOSybXozaNyJUCvnMaFxXrTWM9zDguSxf3+Lktr686rCehqRFwKGUWijDk6ycDhxo+yctxPwTVix21crnqVKv/jXAG1g2IfYOlEJXh7dxFdg0PT0Q+AmlzV2UK4g2moC6rr0yrlDZyW6hUJlKzaMDm3ijReYOtX1D5XjbUpL46IFja8qN48trxoPpSu4X2X54xzHXAwY1xy+tfQNwhpib2v5li+tfCNxs+8Ym+S6mdCm9uK2YTdz7UPa31v62SWgS0oHAwylnZhdTbsi1Un5A0tbjlrfRFXJS+0ofSfoi8CbbF4wsXwwcYnvX2jGnqbbMdyV1VvlO0lMpvS4Op/TA+JGkp1SO8SxJP5H0bUnbS7oYOEvSNU2viKokHUi5Z3Fmc4P6y8CzgOM183DsNY25o6TH2P4VsJmk1zcJsY1Yuww9vrek/5R0gaRPtdVUYvtU239m+z62N20et1VXZpDEN6IUm9oV2KilxN75vrKSbTmypfU+VNLTRtv0h/ejihaNJnaAZqzHohbige15/UMZrHEBpZjPHyhDeC8YLG8x7jnAQ4aePxg4p3KM84E/AR5PKdD0uGb5nwDntvA3XUyZGOA+wC3Agmb5BsBFLcQ7hDLycAnwLkpzzMHANyn1O2rHO3fo8X8Cb6dc9h5AGY1YO95Xhh4f1MZ+OCbma4GLKAP53tp8D17dg31lkxl+7gNc00K81zS55CTKPKa7jduPKsa7fHVeW5Ofabih+pwJxV3XQyMPbf+oGThV051uBoRIus32mU2sS5r2ztr+aPu3km4Hfks5oGD7Ny117ngB8CjgbpRxCVvavlnSe4CzWH42mtoWe9nUi/82WxfX1TRc+GxPygGsbftRpi78DYCkQ4H/BT5YOU7X+8r1zDzN3mZjf2PNvALYwfatTZPTCZIWuUx918YfeLakV9j+6PBCSftRTiSrm4bkvhmwqUcudVVmpLmW9upmD2bZOaZ5/pfU/0+4UdLfAPei9Cw5gDLJ89NZsYBSDeeqzN+4AWUQzNHNjeqdaafM6R0uN99uk/Rj2zdDqXcuqY3udJs1TQYC7iVJbk6NaKcJchI3rMRQh4LmcRvJqOt9petp9tZ2U7Pd9pVNM+wJzT2NNj7P1wEnShrOI4spM2rt3kK8qUju76F0Txp1CXAkZWdrw98Br6RcvonSlLDCxAxraF/gzZQkMSgqdBrlgPWKyrGgTL6wZxPvBEpPiBdRLk8PbyHe7ZLuYfs2Si8SYOnowDaS+0eBQaXJoyklaq9vBqesUEysggeolKrV0OOlXHnqu8Z/Ue7LnNg8fx7tdPPsel/pepq9X0h6lJsic80Z/HMo3Wmr39tz6W75BEk7UW6+A3zJ9um1Yw3M+94yWskUYpK+78oj16IeSXez/fsxyzcFNrfd9YQdVXXdbXYo7qMpBacEfNP2eW3E6TNJW1KuLH8x5rUn2v7OBDarqmlI7pfbftCqvrYG8Waa8AGoX1q1OZLvQRmwcQelh85Hbf+4Zpwm1rnA54Bj21j/DDE7K+QlaRPKAJtrKWezb6LcrL4EeKcrz9sq6V6DpqYxry0c18SwBrFWOnmE6/fLnsS+0mmhshm6ev7QY0pUT6Np6Ar5NUnv0MhdHEn/Qul9UdudlHbMYygzp+w68lONpHdTRuCdSekJdAWljvwJKiM7a9uY0o3uDEnfk3SApKoTWAxTKeR1GfD/gGcDf0GZ7u6y5rXa/pvSRrwDcAalhvahlBuCH28h3v8MHkj6+shrtcv9/pLStLSk+Tln6KeN0sld7ytvpBQpE/A94Ozm8bFNt8za8Wbq6vnprrt6tqaNLjiVuxBtQJmW6seUwmGfBS6n7AgbthTzoZQkdC4lYTwbWKeFOBcOPV4H+E7zeGPa6W423FXwyZR7CL+gJML9W4h3CaV/7+jybSiDYWrHO7/5V8DPxr1WOd554x6Pe14h1r8D32/+z55Mc9Xd1s8E9pUfUXqojS5fD7ishXiddvWcxM+8P3O3/Rvb+wDPoJx9fRx4pu29PTRDuaTtKsb8oe1DXOq4f4FS7+KAWusfcufQ5fb9gbWb+IOh+q2x/S3bf0+5BD6U0nxRW9eFvNZSGVa+FbBhc6k9GB27XgvxPMPjcc/XLFCZlOZRwGeAl1AmjP9XlYqXrepoXxkUKhvVVqGyP9r+LaVq6XJdPVuINRHT0FsGANtXUJotZnIMUGVSDUlbUIpN7U6piXIAZULb2t5J+ZJeSrla+Lsm/gLKWVptK1RidOmq+GXaKc7UdSGvd1Fm6wL4a+A/JRl4GOVKrLbhrpebDV3Oi+X7wFfhcmp5hqTzKJ/h22ju0dSORff7SteFymbq6vk02unq2bl5f0N1rtTM1FRhPd+gdKc7ntIFbLkbVa5/42oTSgnjVifjnhR1WMiribc2Zb++Q2WykEdRmmh+3kKsQ1b2uu1qB5RmiPxulIo8fcObAAAWOklEQVShCyg3Oz9tu5W5WidB3Ra1W4flu3o+ltIV+aeUom9Tfwbfp+ReZTo8SVey7JJ6+MMZVN9rrZb80DY8BPgH21X7us92o8j2+2rGm2Vbqnc3a7oIzsiVZ/OZK0kH2V6j0auSfkM5Sz+Wcs9puS+u68/E1Om+IukewB/cFOdrvgPPBq603cZV82j8dSn9z39m+7q243UhyX2CJD0CeC+lrfEkyhDyD1POIg6z/W+V491J6XFxKsvKxS5V80yzibc2pcfRFsCXbV/UDBR5E7B+jSutkXh3Um6UDSY9Xm4ouyvPtztXNfZNSR9n5nZ8u/5MTF3vK98E9rN9maQHUXrMfJLSpPY92wdVjncE8EHbFzeD6v6X0ktuE8qJ1bE1403CVCd3Sfe3fW3z+Ezbj6u47t2B023f1DzfCHiqK85oL+ksyryR/wvsAvwT8CngLbZ/VyvOULxHUdpqd6F0oTuWMvN6W5Nxf5zSxv49ygHrKsrNuANrfo5D8Q6gjBm4idKb6sThm+6TUqvJsEsT2FeWDlaU9DbKNIyvVCm7fY4rzz4l6WLb2zWPX0f5bj+vGc186rT9f40z7cm9lYllm3Wf72WFpwbLqn5JR2Oo1NBY1EYb45jYT6C0MT4deKPtk2f5ldWJcRHwCNt3Sro7pa/2gzxmVGDluNtQ/rbdKAeUd7oZZj4Jlc7cX2z7v2dqLmmzSa2jfeUCNwMEJX0HeM/gBKCNkejD32WVGaA+Y/vjo69Ns6npLTODNrsLjusmWvvzurvKrO+Dv+NW4BGDAVtttRE3vXG2p9TQuIYy63sbbnczvZ7t30n6UduJvYn1E0mfp/RjfgmlXPPEkjt19tNBzfF7rvRdlXW4r1wg6b2UbrIPAr7SxN+opXg3Nk2EPwOeSKm2ObjRun5LMTuVM/eZ130UpQ/s4ZS2zlcDG9t+acUYZ6zk5eptxJJeRultcXdKD4Hj27x5JOk2ys0/KAnugc3zVqaGk/QASlPCbpTudMcBX2yjiauJ9yrbH5rD+95k+51tbENbJrCvrE+pVb85cJTt7zfLnwA80PYxK/v91Yj3YOADlFHM7x86a/9zyjiaN9SMNwnzPrlL+iAzTyy7r+17tRR3A+AtlEtRUc4k3j7NXaSam2QXsqzy3miPi6pVDDXDlHBD8aqWa27+vguAzwM3s+LfV7uHR+c38Zsz6Vew4kTxbdxQ7XJfeYbtr87w2qG231gz3l3BNDTLrKxuRhs1NYClI9Wq17SYC0nPAP7J9jMqr3qnyutbqUHybtrAt6MkiEuaAWlteCvLktCGLcWYtM8D3wK+xvJ13WvrdF8BDpd0gO0vDRY0/d6PopxdVyXpX4ErbB8xsvwA4H59OJjM+zP3lZH0Xtv/UHmd77f9OklfYMwVQ80zFkk7A0ewrCvkOymlDgS8o4W+y/9E6WLZ+g3bJt69KNPdLaa0eQt4JKX3xX6eoaLitJB0B3DbuJcozU7VryrH3ehvwwT2lUWUka9vsv255gb8CZQrsH1deXJ6ST8AHj64JzS0fC3K9J0PH/+b02MaztxX5oVA1eTOspmX3lt5veMcBuxP6Qr5LEp1yLe4TPXVhq2BcyS9svYAohl8gDKUe+/Bl6i5WfwW4EOUipjVNAlhL0rJiC8A/wg8hVJ07m22f1kzHqXwW9e9Kr4o6dm2T2k5Tqf7istsSE8HTpO0GeVG+Fm226rQ6NHE3iy8c9ChYdpN+5n71ba3mvR2rK7RNluVqege2HLMR1MGS/2Q0sd+6Q5eu3eOpMtsb7uqr61BvOMppZM3oKmsSUnyTwIeZbvqfLxddpmTdAvL5hTdALid8rdCe1cJXe4rg+/B5pSr168yNANTC/HOBl5k+7KR5dtSatgvrhlvEub9mbtmnqRAtNAVUtKFrKSiX+UeHhtJev7y4Zc9r90s06zzXEn/TCmd/ECWL7VQewRn12dAD7P98KY72zW2BzMlfVlSG4XYPtPCOsey3WkXyCZml/vKYUOPLwDuO7SsjXgHA6dKejvLz2l6EKWI2dSb98md8sEPzlhG3d5CvMHZ3Subf4cnyB7XvromvsHyE4AMPzelOFQ1zeXuYZRCZTsPupu16DuSDqY0iSw9YEp6C6UJqrbbAVyKhl078lobbcfrNn/fOLb9thZi0pwAPImyj3yrpdG+ne4rtru+2X+qpOdRmu5e3Sy+GNjDUz7948BUN8u0SdJ3bD9xtmXTRNIVwLsp0/i1/h/f3FD9GKUU8/mUZLQ9cB7wcleuginpOpbN5rNX85jm+Qtt37dyvHF9oe9BmVz6Prar99iR9GHKIJ9B7ZO9gB/bfuXMv7VacbreV54/ssg0s0/ZvqXt+EPbcXdgV9udXZW1Zd4nd61Y6c/AL91yqVNJ5wOvsv3t5vkTgA/X7KkwZij5YIf+tu2f1IozFG+B7evHLN+KctPzPbVjNut/IKUAlICL3dKcnJL2Xdnrto9uI24T+56UQTj7UcpFH9bGoB9JF1N6ebh5vhblxm61yWqa9Xa6r0j6rzGLNwEeQelZ1caUmoPYawPPpJRY+HPK1dAL2orXlWloljlszLJNVAoK7eP2aobsBxylUjEOymjVqgNFGD+UfBHwz5L+n+3jxry+2oa/rJI2pdSz3odStbF6WVU19VBs/1jS/YZ7Xcx1dOeqGE7ekjYsi9oddNbcE3o9pdnuaODRrjwR94hLKZNYDAaAbUVpo66q633F9svGLW8Gwh1PKTxXlaSnAC+izO37PUoZgm1s125+nYh5f+Y+E0mLgffZfkrLce5F+ZxuajPOSMxNgK/VHv3YnF3uTtmhH0z5ku5le8uacYbiLe0NNKZnUCujOyX9HeWm2KAWy63AobY/3EKs9wDPB46kTPDQegVKlclkHkNJRjSP/5fmflCtcRhd7yuzbEv1fUXSNZTRtx8BTrJ9i6Sf2G592sKuTMOZ+1i2lzRnZ1Vphup7g66v7mBCC9s3tNTX9jpKUngzpenHKqWN26IZHo97vubBpDcDT6CUb72iWfYA4N8lbWL77ZVDvoFS6/zNlKutpZtCS90TKb08utD1vjKWyqQdv29h1Z8Fnke5Z/FHlUJz03mmO4OpTe6S7ks7/xkTqb43rBm52sal/ZsohbU+AnxK0qdbiDGsswmkGy8BHumhQmG2r5D0QsqctFWTu+3OJ5i3/Q1YekU5XFum6vSPdLyvzDAifBNKv/cX145n+7Uqddx3ojQ3vQe4V7OvnNLFVVjb5n2zjMYXDtuEcob2Wttf6H6r6pihT/0mwLWUIdeXtBT3AZQdem9gW+AQysQWK0yKvIZxBlUhhytC0jx/gO0NZvrd1Yx3qe2HzPDaD20/tGa8SZC0P2Vi7N9SBhW1Ov1jh/vKn40sMvAr4DLbbXR5Ho2/LmVikn0oVSE3bTtm26YhuY/2gBj8p5/dRm+EobhHUw4eNzbPN6b0gKh2U1UrVk008Ku2bwKObMOfUtpVX1h7dOyYv285rl8V8uuUiTm+PrJ8Z0pZh66LYVUn6TLg8a5fSmEusdvcVx5nu42xD6tM0lNsf3PS27GmpiG5L7T909nfWT3uCkPLuxhurlJq+HmUodF/0VKMjShnYQA/6vJmcZskbUepmvhtlg1+ewylF8Ruti+e4OZVIenLwPO76tHR1b4ycvP9f20/vo04Q/E6nd93Eqahzf0kyiAYJH3W9h4dxV1L0saDbm1ND5ZWPq+mW+ezKWdFu1Bu9hyx0l9a/ThHUg4eP6Fc0m8t6UTgb2tf/krajzIX5nua5z+j3MsQpaTxR2rGc5ns+OGUz3G7Js43gb9xSxN2TMBBwHdV5t9deqPR9mtqBul6X2H5G+x3r7zucT7Gsvl9PyCp1fl9J2Eakvvwf3or7YozOIzyJTqBcgb4QkpJ3mpU6rYPBk6cQSl1sONMfX4reDOwLrDVYNRf0+XtcEqlxrdUjve3lIPVwHW2t2hGAX6FcrOuKpfp/M6g9PYY1I/vS2IH+A/gdMpEGitUNayo631lrabpc62hx0u/+y3cMF7MBOb37dI0NMvM2Fe6g9gPoxQsEmXm9x9UXv+dlIkXXjoYkSrpihZvjl1EOXjcNrJ8Q+BMV65hLekc2zsMPV863Zyks20/pnK8Qf34HSjlDtaiR/XjASR91/YTOojT9b5yJctuEI+qfsO4q3EXkzQNZ+6PlHQz5T99/eYxtNuXGMrKfwD8oGkH313Seyq3g+9A6YXwNZVaHscBa1dc/6g7x7XV2r5VUhtH+XsPPxlK7GsB92khXqf14yfkjKbHzBdYvlmm9pltp/uK7UVzeZ+k7SrdO3mopMHIXgEPbJ63Mr/vJMz7M/dJmaEd/HNtdb2U9ERKE80elLPOE20fWTnG94GnMv7s6Azbj6wc78PADbbfPLL87cCmtv+2crxO68dPgqRxNYfaOLPtdF+Zq1pn2F335JqEJPcRY9rBPw18cK5nFhXirwU8g3L2+bJmWZWzlQlc+m5AaSZ5DGUQEZRmkiWUqpBVB4pIutz2g2Z4rRfJfRxJ67VwM/xKOtxX5qqLHmsj8VrvudOWJPcRXbeDz3Gbur7XUOvSd7C+B1B6rwD8wCNVISsevI5m2ZR6o/XjH2z7JWsaY75ompt2olxZ7urK5YxXYTuq7itziNf1d6HTg0lN09Dm3rWu28HnousZjY6h6X5ag0udlys6iPdqShe3y1VKNg/Xj9+vwvonTtJjKQl9d8po5ldSJpyYlKr7yjw0tWe/Se4jbJ9HSQZvHGoHX0/SqbTQDj7Xzeo4XtcHkyrxmt4we2r5+vFvbOtKoUuS3kHpjvtTykQdbwWWuMUa9XPU9b7SeimCvui88NE0sf0d26+ijGJ7P2WQA7B0NGRfdX0wqRrP9o9tf8H2yaOJvXHMmGXz3f7A/1HGBvy37V8xP84qq2yDpK21bO4EJO0k6d8lvb7p3FCC2Y+rEW9VNq3jeNUkuc+B7TttnzYyuKjVBCHp/kNPc7ZS1zR+Ye8HvAN4LqXZ6RhK1+C+XH0fT1ORVdKjKJOP/5RyA76NWvxfmeNbp/Y+TV92jEloO0GcSZlxp5OzFUn3tz2YVLqLKnydxhsxH854V4ntPwKnAqc2IyqfQ5mv9WeSvm77RRPatFr/d+sP7Q8vBo6yfVjTe6yN2dYWzOVNti9qIXYnktxXX9sJouuzy04PJhOI1xtNOYUTgBOakgCjk0uvsaYf+I1uCoVJ2olSZ+Yq4EODrpcV/++G9/edKTV0aMoDtPFduLdWnJR7KdufayFmp5Lc56/cRK0ZbLJXCtVIuhtloNsi2v3+Hk/pkXPTUDPJu1jWTPLyyvFOl3Q88HNgY0r9HCRtDrRRG+jelKufsf34gST3u5LaCULjJyKBssNttKbrX0VTfRN1DvpypfB54CZKvZw2pp8b6LqZ5HWUKe82B55k+w/N8m0pXT5ru8oV52aYj5LcV03tBLFkNV9bLV0fTObZwWsab6KOs6XtXWZ/2xrrtJmkGXR2HJQbqpJeS+n6+RNKT7XaHiLpiba/M7xQ0pOBa2foZTVVktxXTdWdemV9lCW9t2asRqcHkwnEW5mpu4k6g+9K+lPbF7Ycp9NmEkkPpgwe3Icy09qnKSPo25o96yzgljHLf0s5mOzaUtzOJLmvmi4TxAuBf6i5wq4PJl3Hm2dXCm15EvDSpoDY72mvimHXzSQ/pJT92NX25QCSDmghzsBmti8YXWh7iaRFLcbtTJL7iHmUILpuRqh+MJlAvPl0pdCWZ3URZALNJHtQztzPUJlK8Dja/Q6sbLan9VuM25kk9xV1liBUpu4b+xI9773SRrwJNHN1blCKVtJmtDgdXdfNJLZPBE7UsjmEDwDuK+kjlLIfcx10NFdnS3qF7Y8OL1SZGvKcyrEmIlUhV4Gk99qudrbZXFqb7krwruxg8n3bW05zvFm25ae2F3YVry2SnkuZAvL+lKkEt6ZMJVi1HMZQddT9hppJOq2O2uw/ewJ72d658rrvC5xI6fU2SOaLgfWA3d2D6faS3FfBtCeICRxMOo03y7ZcbXurruK1pZlEY2fga7a3bwYX7WN7/8pxdqecuT8BGDST/KftbWrGmbTm8xtMGXix7dMnuT01JbmvgtoJQtJoqVQDv7R9da0YdyXz6UqhLZKW2F7cJPntm66J37O9Y0vxBs0k+1AOKkfTTjNJVJY29xEdt4MfNmbZJk0VvH1sVx0s0vXBZAIHr3OY+UphakeljrhRZZLqbwGflHQdcEdbwWz/BvhkE2vQTHIgkOQ+z+XMfcR8aEqQtBh4n+2nVF7vGWMWb0JpZ2zjYNJpvLuC5kz6t5SKrn9JGUb/yaYEcMRSSe7zVJfTibV1MOk63l2lmasp6rWt7a9Jugewtu1xA3LiLizNMiPmQ4Jo7uR3dtRtBm5s2IN4nTZzTYKkV1Am7tgEeCBlIpkjgKdNcrti/klyX1FnCWKGAVObUHoovLZWnDlsR6cHk7bizdQHu7lS+ADQyZVJy14J7EgZPo/ty5o+7xHLSXIf0XGCGB0UZcqAkdfbvq5iHKD7g8l8OXh1fWXSst/bvn1Qu6uZiSltq7GCJPc5ailBnGH7p5XXuTKdHkwmEG+srq9MWvYNSW+iTLH3DODvgS9MeJtiHsoN1TlqEsQptneouM6lN00lfdb2HrXWPUO8hV0eTCYQb6VXCranPgk29dT3A55J6dF1GmVwUb7IsZwk9xFdJghJ59nefvRxWyZwMOk63r4jiwZXCmd3eaUQMR+kWWZFXTYleIbHbRnuu9/F0P+u43XdzNUZSSuUpx3WQsnfmHJJ7ivqMkE8UtLNlCS4fvMYltXovlfleF0fTLqOdxLQ2ZVCx+6kfIaforSx/3aymxPzXZplRnTdlNAlSX8EfkNzMAFuG7xECweTCcTrtJmra5IeSqnxsivwA0qi/4rt1soPxPTKmfuKum5K6Izttfscj+6vFDpl+4fAIcAhkvYCPgEcCrxnohsW81KS+4p6nSB6rutmrk5J2oJShnd34NeUCS1OnOhGxbyVZpkRXTclRMyFpG8A9wSOB04Abhh+3fYN434v7rqS3COmgKQrWXYlOfylHZx09KoJMdZckntEj0jazvbFk96OmLy1Jr0BEVHVMZPegJgfktwj+qX2bGExpZLcI/ol7awBJLlHRPRSkntEv/RlIvBYQ+ktEzEFmnlTb7R9U/N8J+B5wFXAh2wnqcdycuYeMR2OBzYAkPQo4DPAT4FHAh+e4HbFPJXyAxHTYX3b1zaPXwwcZfuwZvKOqZ/4O+rLmXvEdBju4rgz8HUA23eS7o8xRs7cI6bD6ZKOB34ObAycDiBpc+B3k9ywmJ+S3COmw+uAvYDNgSfZ/kOzfFvKNJARy0lvmYgp09xQfRHwQuAnwOdsf3CyWxXzTc7cI6aApAdTarnvQ5nT99OUk7OdJrphMW/lzD1iCki6E/gWsJ/ty5tlV6TUb8wkvWUipsMewC+AMyR9VNLTSC+ZWImcuUdMEUkbUEam7kPpEnk0cKLtr0x0w2LeSXKPmFKSNgH2BPayvfOktyfmlyT3iIgeSpt7REQPJblHRPRQkntERA8luUdE9FCSe0RED/1/qcxo78lXaY0AAAAASUVORK5CYII=\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - " data.skew().plot(kind='bar')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## understanding data with visualization" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Histogram\n", - "### I want to understand each attribute of my dataset independently" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Data pre-processing" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure(figsize=(20,20))\n", - "data.hist()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Standardize data" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[ 7.69712416e-01 -1.12341031e+00 -1.90047029e-01 1.37605977e-01\n", - " -6.06718766e-01 -7.20629784e-01 -3.11684110e-01 -1.33070267e+00\n", - " -2.25681314e-02 -3.60971652e-01 -9.25122883e-01]\n", - " [ 5.07884366e-01 -4.10857567e-01 -3.76275096e-01 -2.43225309e-01\n", - " -1.18128598e+00 -9.24503172e-01 3.20837658e+00 -1.30322672e+00\n", - " -5.92370366e-01 9.02050407e-01 1.03699430e+00]\n", - " [ 9.00626442e-01 -4.10857567e-01 -9.16336490e-01 -8.65106417e-03\n", - " -1.05360437e+00 -4.63244125e-02 -3.11684110e-01 -1.30383154e+00\n", - " -4.59030969e-01 -1.40916462e+00 2.31808537e+00]\n", - " [ 7.69712416e-01 -5.74065761e-01 -7.11485617e-01 -8.70124978e-01\n", - " 1.59370848e-01 6.27395116e-01 -3.11684110e-01 -1.30201709e+00\n", - " -7.01486075e-01 -2.30020073e+00 6.98862456e-01]\n", - " [ 1.42428254e+00 2.04070778e-03 -3.66963693e-01 -1.04957427e+00\n", - " -4.79037163e-01 2.00315519e-01 -3.11684110e-01 -1.30184429e+00\n", - " -7.71259861e-02 -1.97723618e+00 1.44656245e+00]]\n" - ] - } - ], - "source": [ - "from sklearn.preprocessing import StandardScaler\n", - "array = data.values\n", - "#separate array into input and output components\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "scaler = StandardScaler().fit(X)\n", - "rescaledX = scaler.transform(X)\n", - "# summarize transformed data\n", - "#set_printoptions(precision=3)\n", - "print(rescaledX[0:5,:])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Feature selection\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Chose Recursive Feature Elimination because i dont have the library for my data in this case\n" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Num Features: 8\n", - "Selected Features: [ True False True False True True True True False True True]\n", - "Feature Ranking: [1 3 1 2 1 1 1 1 4 1 1]\n" - ] - } - ], - "source": [ - "from sklearn.feature_selection import RFE\n", - "from sklearn.linear_model import LogisticRegression\n", - "\n", - "array1 = data.values\n", - "X = array1[:,0:11]\n", - "Y = array[:,11]\n", - "# feature extraction\n", - "model = LogisticRegression()\n", - "rfe = RFE(model,8)\n", - "fit = rfe.fit(X,Y)\n", - "print(\"Num Features:\", fit.n_features_)\n", - "print(\"Selected Features:\", fit.support_)\n", - "print(\"Feature Ranking:\", fit.ranking_)" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", - " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", - " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", - " 'CLASS'],\n", - " dtype='object')" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "data.columns" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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} - ], - "source": [ - "drop_test = test.drop(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'AS_DAYM780201'],axis=1)\n", - "drop_test" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [], - "source": [ - "seleceted_train = X[:,fit.support_]\n", - "selected_test = test.values[:,fit.support_]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Evaluate the Performance of Machine Learning Algorithms with Resampling¶\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Split into Train and Test Sets" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Accuracy: 91.55701754385966\n" - ] - } - ], - "source": [ - "from sklearn.model_selection import train_test_split\n", - "from sklearn.linear_model import LogisticRegression\n", - "\n", - "array = data.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "test_size = 0.30\n", - "seed = 7\n", - "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", - "random_state=seed)\n", - "model = LogisticRegression()\n", - "model.fit(X_train, Y_train)\n", - "result = model.score(X_test, Y_test)\n", - "print(\"Accuracy: \", (result*100.0))\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## K-fold Cross Validation" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Accuracy: (83.5359128018065, 27.08521320979506)\n" - ] - } - ], - "source": [ - "from sklearn.model_selection import KFold\n", - "from sklearn.model_selection import cross_val_score\n", - "\n", - "array = data.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "\n", - "num_folds = 10 #number of folds to use\n", - "seed = 7 #reproducibility\n", - "\n", - "kfold = KFold(n_splits=num_folds, random_state=seed)\n", - "model = LogisticRegression()\n", - "results = cross_val_score(model, X, Y, cv=kfold)\n", - "\n", - "print(f\"Accuracy:\", (results.mean()*100.0, results.std()*100.0))\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Leave One Out Cross Validation" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Accuracy: (91.4417379855168, 27.974673416141517)\n" - ] - } - ], - "source": [ - "from sklearn.model_selection import LeaveOneOut\n", - "from sklearn.model_selection import cross_val_score\n", - "\n", - "array = data.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "num_folds = 10\n", - "loocv = LeaveOneOut()\n", - "model = LogisticRegression()\n", - "results = cross_val_score(model, X, Y, cv=loocv)\n", - "print(\"Accuracy:\", (results.mean()*100.0, results.std()*100.0))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Repeated Random Test-Train Splits" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Accuracy: (91.30482456140349, 0.5803122202806698)\n" - ] - } - ], - "source": [ - "from sklearn.model_selection import ShuffleSplit\n", - "from sklearn.model_selection import cross_val_score\n", - "\n", - "array = data.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "n_splits = 10\n", - "test_size = 0.30\n", - "seed = 7\n", - "kfold = ShuffleSplit(n_splits=n_splits, test_size=test_size, random_state=seed)\n", - "model = LogisticRegression()\n", - "results = cross_val_score(model, X, Y, cv=kfold)\n", - "print(\"Accuracy: \" , (results.mean()*100.0, results.std()*100.0))\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Machine Learning Algorithm Performance Metrics" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Algorithms Overview\n", - "### linear machine learning algorithms:\n", - "\n", - " Logistic Regression.\n", - " Linear Discriminant Analysis.\n", - "### onlinear machine learning algorithms\n", - "\n", - " k-Nearest Neighbors.\n", - " Naive Bayes.\n", - " Classication and Regression Trees.\n", - " Support Vector Machines.\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Linear Machine Learning Algorithms" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Logistic Regression" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.835359128018065\n", - "MCC: 0.8342865299822478\n", - "[False True]\n", - "False: 383\n", - "True: 375\n" - ] - } - ], - "source": [ - "# Logistic Regression Classification\n", - "from pandas import read_csv\n", - "from sklearn.model_selection import KFold\n", - "from sklearn.model_selection import cross_val_score\n", - "from sklearn.linear_model import LogisticRegression\n", - "\n", - "array = data.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "num_folds = 10\n", - "kfold = KFold(n_splits=10, random_state=7)\n", - "model = LogisticRegression()\n", - "results = cross_val_score(model, X, Y, cv=kfold)\n", - "print(results.mean())\n", - "\n", - "model.fit(X,Y)\n", - "output = model.predict(test.values)\n", - "\n", - "from sklearn.metrics import matthews_corrcoef\n", - "mcc = matthews_corrcoef(model.predict(X),Y)\n", - "print('MCC:',mcc)\n", - " \n", - "my_report = pd.DataFrame(output)\n", - "my_report.columns = ['CLASS']\n", - "my_report.index.name = \"Index\"\n", - "my_report['CLASS']=my_report['CLASS'].map({0.0:False, 1.0:True})\n", - "my_report.to_csv(\"report_XGB.csv\")\n", - "\n", - "print(my_report['CLASS'].unique())\n", - "print('False: ',my_report.groupby('CLASS').size()[0].sum())\n", - "print('True: ',my_report.groupby('CLASS').size()[1].sum())" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [ - 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" - ], - "text/plain": [ - " FULL_Charge FULL_AURR980107 FULL_GEOR030101 FULL_OOBM850104 \\\n", - "0 4.0 0.873 0.987 -4.833 \n", - "1 4.0 0.892 0.931 -0.584 \n", - "2 2.0 0.901 1.039 -5.664 \n", - "3 4.5 0.869 0.982 -5.423 \n", - "4 -4.0 1.061 0.976 -2.002 \n", - ".. ... ... ... ... \n", - "753 -1.5 1.100 0.991 -1.987 \n", - "754 -1.0 1.085 1.027 -0.745 \n", - "755 -1.0 1.108 1.033 -1.789 \n", - "756 -1.0 0.955 1.023 1.141 \n", - "757 -7.0 1.078 1.009 -0.066 \n", - "\n", - " NT_EFC195 AS_MeanAmphiMoment AS_FUKS010112 CT_RACS820104 \n", - "0 0 0.382 7.225 1.234 \n", - "1 0 0.320 4.942 1.853 \n", - "2 0 0.164 5.969 1.174 \n", - "3 0 2.010 5.462 1.138 \n", - "4 0 2.758 5.582 1.453 \n", - ".. ... ... ... ... \n", - "753 0 15.185 7.053 1.325 \n", - "754 0 16.550 6.729 1.132 \n", - "755 0 16.112 6.036 1.219 \n", - "756 0 20.630 5.669 1.111 \n", - "757 0 17.168 6.688 1.305 \n", - "\n", - "[758 rows x 8 columns]" - ] - }, - "execution_count": 29, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "drop_test" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Linear Discriminant Analysis¶\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", - "\n", - "\n", - "array = data.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "num_folds = 10\n", - "kfold = KFold(n_splits=10, random_state=7)\n", - "model = LinearDiscriminantAnalysis()\n", - "results = cross_val_score(model, X, Y, cv=kfold)\n", - "print(results.mean())\n", - "\n", - "\n", - "model.fit(X,Y)\n", - "output = model.predict(test.values)\n", - "\n", - "from sklearn.metrics import matthews_corrcoef\n", - "mcc = matthews_corrcoef(model.predict(X),Y)\n", - "print('MCC:',mcc)\n", - " \n", - "lda_report = pd.DataFrame(output)\n", - "lda_report.columns = ['CLASS']\n", - "lda_report.index.name = \"Index\"\n", - "lda_report['CLASS']=lda_report['CLASS'].map({0.0:False, 1.0:True})\n", - "lda_report.to_csv(\"ldareport.csv\")\n", - "\n", - "print(lda_report['CLASS'].unique())\n", - "print('False: ',lda_report.groupby('CLASS').size()[0].sum())\n", - "print('True: ',lda_report.groupby('CLASS').size()[1].sum())\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Nonlinear Machine Learning Algorithms" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### k-Nearest Neighbors" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.8027933385443807\n", - "MCC: 0.8690586462107053\n", - "[False True]\n", - "False: 402\n", - "True: 356\n" - ] - } - ], - "source": [ - "from sklearn.neighbors import KNeighborsClassifier\n", - "\n", - "array = data.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "num_folds = 10\n", - "kfold = KFold(n_splits=10, random_state=7)\n", - "model = KNeighborsClassifier()\n", - "results = cross_val_score(model, X, Y, cv=kfold)\n", - "print(results.mean())\n", - "\n", - "\n", - "\n", - "model.fit(X,Y)\n", - "output = model.predict(test.values)\n", - "\n", - "from sklearn.metrics import matthews_corrcoef\n", - "mcc = matthews_corrcoef(model.predict(X),Y)\n", - "print('MCC:',mcc)\n", - " \n", - "report_k = pd.DataFrame(output)\n", - "report_k.columns = ['CLASS']\n", - "report_k.index.name = \"Index\"\n", - "report_k['CLASS']=report_k['CLASS'].map({0.0:False, 1.0:True})\n", - "report_k.to_csv(\"report_k.csv\")\n", - "\n", - "\n", - "print(report_k['CLASS'].unique())\n", - "print('False: ',report_k.groupby('CLASS').size()[0].sum())\n", - "print('True: ',report_k.groupby('CLASS').size()[1].sum())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Naive Bayes" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.880815746048289\n", - "MCC: 0.8407203694376205\n", - "[ True False]\n", - "False: 370\n", - "True: 388\n" - ] - } - ], - "source": [ - "from sklearn.naive_bayes import GaussianNB\n", - "array = data.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "kfold = KFold(n_splits=10, random_state=7)\n", - "model = GaussianNB()\n", - "results = cross_val_score(model, X, Y, cv=kfold)\n", - "print(results.mean())\n", - "\n", - "\n", - "model.fit(X,Y)\n", - "output = model.predict(test.values)\n", - "\n", - "from sklearn.metrics import matthews_corrcoef\n", - "mcc = matthews_corrcoef(model.predict(X),Y)\n", - "print('MCC:',mcc)\n", - " \n", - "report_bayes = pd.DataFrame(output)\n", - "report_bayes.columns = ['CLASS']\n", - "report_bayes.index.name = \"Index\"\n", - "report_bayes['CLASS']=report_bayes['CLASS'].map({0.0:False, 1.0:True})\n", - "report_bayes.to_csv(\"report_bayes.csv\")\n", - "\n", - "\n", - "print(report_bayes['CLASS'].unique())\n", - "print('False: ',report_bayes.groupby('CLASS').size()[0].sum())\n", - "print('True: ',report_bayes.groupby('CLASS').size()[1].sum())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Classiffication and Regression Trees" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from sklearn.tree import DecisionTreeClassifier\n", - "array = data.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "kfold = KFold(n_splits=10, random_state=7)\n", - "model = DecisionTreeClassifier()\n", - "results = cross_val_score(model, X, Y, cv=kfold)\n", - "print(results.mean())\n", - "\n", - "\n", - "model.fit(X,Y)\n", - "output = model.predict(test.values)\n", - "\n", - "from sklearn.metrics import matthews_corrcoef\n", - "mcc = matthews_corrcoef(model.predict(X),Y)\n", - "print('MCC:',mcc)\n", - " \n", - "report_tree = pd.DataFrame(output)\n", - "report_tree.columns = ['CLASS']\n", - "report_tree.index.name = \"Index\"\n", - "report_tree['CLASS']=report_tree['CLASS'].map({0.0:False, 1.0:True})\n", - "report_tree.to_csv(\"report_tree.csv\")\n", - "\n", - "\n", - "print(report_tree['CLASS'].unique())\n", - "print('False: ',report_tree.groupby('CLASS').size()[0].sum())\n", - "print('True: ',report_tree.groupby('CLASS').size()[1].sum())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Support Vector Machines " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from sklearn.svm import SVC\n", - "\n", - "array = data.values\n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "kfold = KFold(n_splits=10, random_state=7)\n", - "model = SVC()\n", - "results = cross_val_score(model, X, Y, cv=kfold)\n", - "print(results.mean())\n" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.3" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/kakooza trevor Starter Kernel.ipynb b/kakooza trevor Starter Kernel.ipynb deleted file mode 100644 index 1885d6f..0000000 --- a/kakooza trevor Starter Kernel.ipynb +++ /dev/null @@ -1 +0,0 @@ -{"cells":[{"metadata":{},"cell_type":"markdown","source":" # KAKOOZA TREVOR\n## Kaggle assignment\n### started on the 28th /feb/2020"},{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n for filename in filenames:\n print(os.path.join(dirname, filename))\n\n# Any results you write to the current directory are saved as output.","execution_count":34,"outputs":[{"output_type":"stream","text":"/kaggle/input/amp-data-set/Test.csv\n/kaggle/input/amp-data-set/AMP_TrainSet.csv\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"# Import the necessary tools required to work on the datasets**"},{"metadata":{"trusted":true},"cell_type":"code","source":"#import the necessary libraries you are going to use\nimport warnings\nwarnings.filterwarnings('ignore')\n\n# -----> Put your code here below:\n\n\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns","execution_count":35,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"\n# This first session is about loading the give dataset and viewing them. \n\n* The two data set provided are\n1. test.csv\n2. AMP_TrainSet.csv \n\n### Now load the data set using.\n```\nTrain = pd.read_csv(\"../input/amp-data-set/AMP_TrainSet.csv\")\nTest = pd.read_csv(\"../input/amp-data-set/Test.csv\")\n```\n"},{"metadata":{"trusted":true},"cell_type":"code","source":"#using pandas we call the data set\nTest = pd.read_csv('/kaggle/input/amp-data-set/Test.csv')\nTrain = pd.read_csv(\"../input/amp-data-set/AMP_TrainSet.csv\")","execution_count":36,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Check the dataset info\n## View the first five raws of the datasets"},{"metadata":{"trusted":true},"cell_type":"code","source":"#head.() is ued to view the first five raws of the data set.\nTest.head()","execution_count":37,"outputs":[{"output_type":"execute_result","execution_count":37,"data":{"text/plain":" FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n0 4.0 3.704 0.873 73.519 \n1 4.0 4.444 0.892 62.444 \n2 2.0 0.000 0.901 47.000 \n3 4.5 0.000 0.869 69.222 \n4 -4.0 21.591 1.061 71.682 \n\n FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n0 0.987 -4.833 0 0.382 \n1 0.931 -0.584 0 0.320 \n2 1.039 -5.664 0 0.164 \n3 0.982 -5.423 0 2.010 \n4 0.976 -2.002 0 2.758 \n\n AS_DAYM780201 AS_FUKS010112 CT_RACS820104 \n0 74.556 7.225 1.234 \n1 56.056 4.942 1.853 \n2 47.000 5.969 1.174 \n3 69.222 5.462 1.138 \n4 66.000 5.582 1.453 ","text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201FULL_GEOR030101FULL_OOBM850104NT_EFC195AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CT_RACS820104
04.03.7040.87373.5190.987-4.83300.38274.5567.2251.234
14.04.4440.89262.4440.931-0.58400.32056.0564.9421.853
22.00.0000.90147.0001.039-5.66400.16447.0005.9691.174
34.50.0000.86969.2220.982-5.42302.01069.2225.4621.138
4-4.021.5911.06171.6820.976-2.00202.75866.0005.5821.453
\n
"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"Train.head()","execution_count":38,"outputs":[{"output_type":"execute_result","execution_count":38,"data":{"text/plain":" FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n0 5.0 0.000 0.951 74.842 \n1 4.0 5.405 0.931 71.595 \n2 5.5 5.405 0.873 73.595 \n3 5.0 4.167 0.895 66.250 \n4 7.5 8.537 0.932 64.720 \n\n FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n0 0.975 -3.663 0 0.282 \n1 0.957 -4.011 1 0.600 \n2 0.961 -2.512 0 0.593 \n3 0.999 -1.362 0 0.614 \n4 0.979 -2.091 0 0.616 \n\n AS_DAYM780201 AS_FUKS010112 CT_RACS820104 CLASS \n0 73.444 5.661 1.041 1 \n1 68.222 6.537 1.453 1 \n2 69.444 4.934 1.722 1 \n3 67.222 4.316 1.382 1 \n4 72.944 4.540 1.539 1 ","text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201FULL_GEOR030101FULL_OOBM850104NT_EFC195AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CT_RACS820104CLASS
05.00.0000.95174.8420.975-3.66300.28273.4445.6611.0411
14.05.4050.93171.5950.957-4.01110.60068.2226.5371.4531
25.55.4050.87373.5950.961-2.51200.59369.4444.9341.7221
35.04.1670.89566.2500.999-1.36200.61467.2224.3161.3821
47.58.5370.93264.7200.979-2.09100.61672.9444.5401.5391
\n
"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"## Shape function\n* This function helps to view the total raws and columns (dimension) of the dataset. "},{"metadata":{"trusted":true},"cell_type":"code","source":"# check the dimensions of your data\n\nTrain.shape, Test.shape\n","execution_count":39,"outputs":[{"output_type":"execute_result","execution_count":39,"data":{"text/plain":"((3038, 12), (758, 11))"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"# Data type\n* This returns a Series with the data type of each column.\n* The result’s index is the original DataFrame’s columns"},{"metadata":{"trusted":true},"cell_type":"code","source":"Test.dtypes","execution_count":40,"outputs":[{"output_type":"execute_result","execution_count":40,"data":{"text/plain":"FULL_Charge float64\nFULL_AcidicMolPerc float64\nFULL_AURR980107 float64\nFULL_DAYM780201 float64\nFULL_GEOR030101 float64\nFULL_OOBM850104 float64\nNT_EFC195 int64\nAS_MeanAmphiMoment float64\nAS_DAYM780201 float64\nAS_FUKS010112 float64\nCT_RACS820104 float64\ndtype: object"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"Train.dtypes","execution_count":41,"outputs":[{"output_type":"execute_result","execution_count":41,"data":{"text/plain":"FULL_Charge float64\nFULL_AcidicMolPerc float64\nFULL_AURR980107 float64\nFULL_DAYM780201 float64\nFULL_GEOR030101 float64\nFULL_OOBM850104 float64\nNT_EFC195 int64\nAS_MeanAmphiMoment float64\nAS_DAYM780201 float64\nAS_FUKS010112 float64\nCT_RACS820104 float64\nCLASS int64\ndtype: object"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"## isnull().sum\n* This function helps to see if the dataset has any missing values."},{"metadata":{"trusted":true},"cell_type":"code","source":"Train.isnull().sum","execution_count":42,"outputs":[{"output_type":"execute_result","execution_count":42,"data":{"text/plain":""},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"Test.isnull().sum()","execution_count":43,"outputs":[{"output_type":"execute_result","execution_count":43,"data":{"text/plain":"FULL_Charge 0\nFULL_AcidicMolPerc 0\nFULL_AURR980107 0\nFULL_DAYM780201 0\nFULL_GEOR030101 0\nFULL_OOBM850104 0\nNT_EFC195 0\nAS_MeanAmphiMoment 0\nAS_DAYM780201 0\nAS_FUKS010112 0\nCT_RACS820104 0\ndtype: int64"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"* When we look at the data ,it shows that both the test and train dataset does not have any missing values"},{"metadata":{},"cell_type":"markdown","source":""},{"metadata":{},"cell_type":"markdown","source":"## Then in column of class we check and find out,\n* How is the data divied into.\n* Here the unique function does that."},{"metadata":{"trusted":true},"cell_type":"code","source":"Train['CLASS'].unique()","execution_count":44,"outputs":[{"output_type":"execute_result","execution_count":44,"data":{"text/plain":"array([1, 0])"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"# Descriptive statistics of the data\n* Generate descriptive statistics that summarize the central tendency,\ndispersion and shape of a dataset's distribution, excluding\n``NaN`` values.\n\nAnalyzes both numeric and object series, as well\nas ``DataFrame`` column sets of mixed data types. The output\nwill vary depending on what is provided.\n\n### For example this function will provide the following summary\n* Count.\n* Mean.\n* Standard Deviation.\n* Minimum Value.\n* 25th Percentile.\n* 75th Percentile(Median).\n* Maximum Value.\n"},{"metadata":{"trusted":true},"cell_type":"code","source":"Train.describe()","execution_count":45,"outputs":[{"output_type":"execute_result","execution_count":45,"data":{"text/plain":" FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\ncount 3038.000000 3038.000000 3038.000000 3038.000000 \nmean 2.060237 8.521520 0.971410 73.668760 \nstd 3.819929 7.586652 0.107413 8.527489 \nmin -16.000000 0.000000 0.684000 42.750000 \n25% 0.000000 2.516000 0.895000 68.294000 \n50% 2.000000 7.143000 0.963000 74.059500 \n75% 4.000000 13.158000 1.041000 79.343750 \nmax 30.000000 46.667000 1.451000 101.682000 \n\n FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\ncount 3038.000000 3038.000000 3038.000000 3038.000000 \nmean 0.994007 -2.432927 0.088545 15.683233 \nstd 0.031333 1.707223 0.284133 11.575665 \nmin 0.866000 -10.432000 0.000000 0.041000 \n25% 0.974000 -3.606000 0.000000 5.587500 \n50% 0.994000 -2.296500 0.000000 14.988500 \n75% 1.011000 -1.283250 0.000000 26.807750 \nmax 1.196000 3.576000 1.000000 51.280000 \n\n AS_DAYM780201 AS_FUKS010112 CT_RACS820104 CLASS \ncount 3038.000000 3038.000000 3038.000000 3038.000000 \nmean 73.650828 5.911361 1.235255 0.500000 \nstd 9.166092 0.693689 0.210012 0.500082 \nmin 42.778000 3.533000 0.785000 0.000000 \n25% 67.556000 5.459250 1.082000 0.000000 \n50% 73.697000 5.925500 1.184000 0.500000 \n75% 79.778000 6.382000 1.351000 1.000000 \nmax 103.167000 8.662000 2.192000 1.000000 ","text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201FULL_GEOR030101FULL_OOBM850104NT_EFC195AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CT_RACS820104CLASS
count3038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.000000
mean2.0602378.5215200.97141073.6687600.994007-2.4329270.08854515.68323373.6508285.9113611.2352550.500000
std3.8199297.5866520.1074138.5274890.0313331.7072230.28413311.5756659.1660920.6936890.2100120.500082
min-16.0000000.0000000.68400042.7500000.866000-10.4320000.0000000.04100042.7780003.5330000.7850000.000000
25%0.0000002.5160000.89500068.2940000.974000-3.6060000.0000005.58750067.5560005.4592501.0820000.000000
50%2.0000007.1430000.96300074.0595000.994000-2.2965000.00000014.98850073.6970005.9255001.1840000.500000
75%4.00000013.1580001.04100079.3437501.011000-1.2832500.00000026.80775079.7780006.3820001.3510001.000000
max30.00000046.6670001.451000101.6820001.1960003.5760001.00000051.280000103.1670008.6620002.1920001.000000
\n
"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"## Class Distribution\n\nA groupby operation involves some combination of splitting the\nobject, applying a function, and combining the results. This can be\nused to group large amounts of data and compute operations on these\ngroups."},{"metadata":{"trusted":true},"cell_type":"code","source":"Train.groupby('CLASS').size().plot(kind='bar')","execution_count":46,"outputs":[{"output_type":"execute_result","execution_count":46,"data":{"text/plain":""},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
","image/png":"iVBORw0KGgoAAAANSUhEUgAAAYAAAAEGCAYAAABsLkJ6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAESVJREFUeJzt3XuMXGd5x/Hvj5iEW8G5LBBsh03BBQJtIWxDWqqKYsgNhFOVVIlQY6Vp3aqh5VIEAf6ICkIFUZESiaZyicGoKJByUSwaSq0EhKo2IRsIuRKyDRAvDslSh7Ql5RJ4+se8bgZ77bV31jvB7/cjjeac5zxnzjvSeH8+t5lUFZKk/jxq3AOQJI2HASBJnTIAJKlTBoAkdcoAkKROGQCS1CkDQJI6ZQBIUqcMAEnq1IpxD2BfjjnmmJqcnBz3MCTp58oNN9zw3aqaWKjvER0Ak5OTTE9Pj3sYkvRzJcm39qfPQ0CS1CkDQJI6ZQBIUqcMAEnqlAEgSZ0yACSpUwaAJHXKAJCkTj2ibwT7eTF54T+NewiHlG+++xXjHsIhxc/n0jnUPpvuAUhSpwwASeqUASBJnTIAJKlTBoAkdcoAkKROGQCS1CkDQJI6ZQBIUqcMAEnqlAEgSZ0yACSpUwsGQJLNSe5Lcss8y96UpJIc0+aT5JIkM0luSnLiUO+GJHe2x4alfRuSpAO1P3sAHwZO272YZA3wcuDuofLpwNr22Ahc2nqPAi4CXgScBFyU5MhRBi5JGs2CAVBVXwR2zrPoYuDNQA3V1gMfqYFrgZVJjgVOBbZV1c6quh/YxjyhIklaPos6B5DkVcC3q+qruy1aBWwfmp9ttb3VJUljcsA/CJPkccDbgVPmWzxPrfZRn+/1NzI4fMRxxx13oMOTJO2nxewBPAM4Hvhqkm8Cq4EvJ3kqg//ZrxnqXQ3s2Ed9D1W1qaqmqmpqYmJiEcOTJO2PAw6Aqrq5qp5cVZNVNcngj/uJVfUdYCtwbrsa6GTggaq6B/gccEqSI9vJ31NaTZI0JvtzGejlwL8Dz0oym+T8fbRfBdwFzAB/D/wpQFXtBN4JXN8e72g1SdKYLHgOoKrOWWD55NB0ARfspW8zsPkAxydJOki8E1iSOmUASFKnDABJ6pQBIEmdMgAkqVMGgCR1ygCQpE4ZAJLUKQNAkjplAEhSpwwASeqUASBJnTIAJKlTBoAkdcoAkKROGQCS1CkDQJI6ZQBIUqcMAEnq1P78KPzmJPcluWWo9t4kX0tyU5JPJ1k5tOytSWaS3JHk1KH6aa02k+TCpX8rkqQDsT97AB8GTtuttg14XlX9CvB14K0ASU4Azgae29b52ySHJTkM+ABwOnACcE7rlSSNyYIBUFVfBHbuVvuXqnqozV4LrG7T64GPVdUPq+obwAxwUnvMVNVdVfUj4GOtV5I0JktxDuAPgM+26VXA9qFls622t/oekmxMMp1kem5ubgmGJ0maz0gBkOTtwEPAR3eV5mmrfdT3LFZtqqqpqpqamJgYZXiSpH1YsdgVk2wAXgmsq6pdf8xngTVDbauBHW16b3VJ0hgsag8gyWnAW4BXVdWDQ4u2AmcnOSLJ8cBa4EvA9cDaJMcnOZzBieKtow1dkjSKBfcAklwOvAQ4JskscBGDq36OALYlAbi2qv6kqm5NcgVwG4NDQxdU1U/a67wW+BxwGLC5qm49CO9HkrSfFgyAqjpnnvJl++h/F/CueepXAVcd0OgkSQeNdwJLUqcMAEnqlAEgSZ0yACSpUwaAJHXKAJCkThkAktQpA0CSOmUASFKnDABJ6pQBIEmdMgAkqVMGgCR1ygCQpE4ZAJLUKQNAkjplAEhSpwwASerUggGQZHOS+5LcMlQ7Ksm2JHe25yNbPUkuSTKT5KYkJw6ts6H135lkw8F5O5Kk/bU/ewAfBk7brXYhcHVVrQWubvMApwNr22MjcCkMAoPBj8m/CDgJuGhXaEiSxmPBAKiqLwI7dyuvB7a06S3AmUP1j9TAtcDKJMcCpwLbqmpnVd0PbGPPUJEkLaPFngN4SlXdA9Cen9zqq4DtQ32zrba3+h6SbEwynWR6bm5ukcOTJC1kqU8CZ55a7aO+Z7FqU1VNVdXUxMTEkg5OkvSwxQbAve3QDu35vlafBdYM9a0GduyjLkkak8UGwFZg15U8G4Arh+rntquBTgYeaIeIPgeckuTIdvL3lFaTJI3JioUaklwOvAQ4Jsksg6t53g1ckeR84G7grNZ+FXAGMAM8CJwHUFU7k7wTuL71vaOqdj+xLElaRgsGQFWds5dF6+bpLeCCvbzOZmDzAY1OknTQeCewJHXKAJCkThkAktQpA0CSOmUASFKnDABJ6pQBIEmdMgAkqVMGgCR1ygCQpE4ZAJLUKQNAkjplAEhSpwwASeqUASBJnTIAJKlTBoAkdcoAkKROjRQASd6Q5NYktyS5PMljkhyf5Lokdyb5eJLDW+8RbX6mLZ9cijcgSVqcRQdAklXAnwNTVfU84DDgbOA9wMVVtRa4Hzi/rXI+cH9VPRO4uPVJksZk1ENAK4DHJlkBPA64B3gp8Im2fAtwZpte3+Zpy9clyYjblyQt0qIDoKq+Dfw1cDeDP/wPADcA36uqh1rbLLCqTa8Ctrd1H2r9R+/+ukk2JplOMj03N7fY4UmSFjDKIaAjGfyv/njgacDjgdPnaa1dq+xj2cOFqk1VNVVVUxMTE4sdniRpAaMcAnoZ8I2qmquqHwOfAn4DWNkOCQGsBna06VlgDUBb/iRg5wjblySNYJQAuBs4Ocnj2rH8dcBtwOeBV7eeDcCVbXprm6ctv6aq9tgDkCQtj1HOAVzH4GTul4Gb22ttAt4CvDHJDINj/Je1VS4Djm71NwIXjjBuSdKIVizcsndVdRFw0W7lu4CT5un9AXDWKNuTJC0d7wSWpE4ZAJLUKQNAkjplAEhSpwwASeqUASBJnTIAJKlTBoAkdcoAkKROGQCS1CkDQJI6ZQBIUqcMAEnqlAEgSZ0yACSpUwaAJHXKAJCkThkAktSpkQIgycokn0jytSS3J/n1JEcl2ZbkzvZ8ZOtNkkuSzCS5KcmJS/MWJEmLMeoewPuBf66qZwO/CtzO4Mfer66qtcDVPPzj76cDa9tjI3DpiNuWJI1g0QGQ5InAbwGXAVTVj6rqe8B6YEtr2wKc2abXAx+pgWuBlUmOXfTIJUkjGWUP4BeBOeBDSb6S5INJHg88paruAWjPT279q4DtQ+vPtpokaQxGCYAVwInApVX1AuD7PHy4Zz6Zp1Z7NCUbk0wnmZ6bmxtheJKkfRklAGaB2aq6rs1/gkEg3Lvr0E57vm+of83Q+quBHbu/aFVtqqqpqpqamJgYYXiSpH1ZdABU1XeA7Ume1UrrgNuArcCGVtsAXNmmtwLntquBTgYe2HWoSJK0/FaMuP6fAR9NcjhwF3Aeg1C5Isn5wN3AWa33KuAMYAZ4sPVKksZkpACoqhuBqXkWrZunt4ALRtmeJGnpeCewJHXKAJCkThkAktQpA0CSOmUASFKnDABJ6pQBIEmdMgAkqVMGgCR1ygCQpE4ZAJLUKQNAkjplAEhSpwwASeqUASBJnTIAJKlTBoAkdcoAkKROGQCS1KmRAyDJYUm+kuQzbf74JNcluTPJx9sPxpPkiDY/05ZPjrptSdLiLcUewOuA24fm3wNcXFVrgfuB81v9fOD+qnomcHHrkySNyUgBkGQ18Argg20+wEuBT7SWLcCZbXp9m6ctX9f6JUljMOoewN8AbwZ+2uaPBr5XVQ+1+VlgVZteBWwHaMsfaP0/I8nGJNNJpufm5kYcniRpbxYdAEleCdxXVTcMl+dprf1Y9nChalNVTVXV1MTExGKHJ0lawIoR1n0x8KokZwCPAZ7IYI9gZZIV7X/5q4EdrX8WWAPMJlkBPAnYOcL2JUkjWPQeQFW9tapWV9UkcDZwTVW9Bvg88OrWtgG4sk1vbfO05ddU1R57AJKk5XEw7gN4C/DGJDMMjvFf1uqXAUe3+huBCw/CtiVJ+2mUQ0D/r6q+AHyhTd8FnDRPzw+As5Zie5Kk0XknsCR1ygCQpE4ZAJLUKQNAkjplAEhSpwwASeqUASBJnTIAJKlTBoAkdcoAkKROGQCS1CkDQJI6ZQBIUqcMAEnqlAEgSZ0yACSpUwaAJHXKAJCkTi06AJKsSfL5JLcnuTXJ61r9qCTbktzZno9s9SS5JMlMkpuSnLhUb0KSdOBG2QN4CPiLqnoOcDJwQZITGPzY+9VVtRa4mod//P10YG17bAQuHWHbkqQRLToAquqeqvpym/5v4HZgFbAe2NLatgBntun1wEdq4FpgZZJjFz1ySdJIluQcQJJJ4AXAdcBTquoeGIQE8OTWtgrYPrTabKvt/lobk0wnmZ6bm1uK4UmS5jFyACR5AvBJ4PVV9V/7ap2nVnsUqjZV1VRVTU1MTIw6PEnSXowUAEkezeCP/0er6lOtfO+uQzvt+b5WnwXWDK2+GtgxyvYlSYs3ylVAAS4Dbq+q9w0t2gpsaNMbgCuH6ue2q4FOBh7YdahIkrT8Voyw7ouB3wduTnJjq70NeDdwRZLzgbuBs9qyq4AzgBngQeC8EbYtSRrRogOgqv6V+Y/rA6ybp7+ACxa7PUnS0vJOYEnqlAEgSZ0yACSpUwaAJHXKAJCkThkAktQpA0CSOmUASFKnDABJ6pQBIEmdMgAkqVMGgCR1ygCQpE4ZAJLUKQNAkjplAEhSpwwASeqUASBJnVr2AEhyWpI7kswkuXC5ty9JGljWAEhyGPAB4HTgBOCcJCcs5xgkSQPLvQdwEjBTVXdV1Y+AjwHrl3kMkiRgxTJvbxWwfWh+FnjRcEOSjcDGNvs/Se5YprH14Bjgu+MexELynnGPQGPyiP98/hx9Np++P03LHQCZp1Y/M1O1Cdi0PMPpS5Lpqpoa9zik+fj5XH7LfQhoFlgzNL8a2LHMY5AksfwBcD2wNsnxSQ4Hzga2LvMYJEks8yGgqnooyWuBzwGHAZur6tblHEPnPLSmRzI/n8ssVbVwlyTpkOOdwJLUKQNAkjplAEhSp5b7PgAtoyTPZnCn9SoG91vsALZW1e1jHZikRwT3AA5RSd7C4Ks2AnyJwSW4AS73S/gkgVcBHbKSfB14blX9eLf64cCtVbV2PCOT9i3JeVX1oXGPowfuARy6fgo8bZ76sW2Z9Ej1l+MeQC88B3Doej1wdZI7efgL+I4Dngm8dmyjkoAkN+1tEfCU5RxLzzwEdAhL8igGX8G9isE/rFng+qr6yVgHpu4luRc4Fbh/90XAv1XVfHuvWmLuARzCquqnwLXjHoc0j88AT6iqG3dfkOQLyz+cPrkHIEmd8iSwJHXKAJCkThkA6lqSpyb5WJL/SHJbkquS/FKSW/bSvyLJd5P81W71Vyb5SpKvttf541Z/VpIvJLkxye1J/MpjPWJ4EljdShLg08CWqjq71Z7Pvi9DPAW4A/i9JG+rqkryaAbfZX9SVc0mOQKYbP2XABdX1ZXt9X/54Lwb6cC5B6Ce/Tbw46r6u12FdlXK9r2vwjnA+4G7gZNb7RcY/GfqP9tr/LCq7mjLjmVw+e2u1795yUYvjcgAUM+eB9ywv81JHgusY3AJ4+UMwoCq2sngp02/leTyJK9p92AAXAxck+SzSd6QZOWSvgNpBAaAtP9eCXy+qh4EPgn8TpLDAKrqDxmEw5eANwGbW/1DwHOAfwReAlzbDhFJY2cAqGe3Ai88gP5zgJcl+SaDPYejGRxGAgaHd6rqYuDlwO8O1XdU1eaqWg88xGDPQxo7A0A9uwY4Iskf7Sok+TXg6bs3Jnki8JvAcVU1WVWTwAXAOUmekOQlQ+3PB77V1jutnSQmyVMZhMa3D87bkQ6MdwKra0meBvwNgz2BHwDfZPBFercB9w61vh944a6rhdq6RzG4IuiZDM4JPAP4X+D7wOuqajrJ+4BXtNcGeG9V/cPBfE/S/jIAJKlTHgKSpE4ZAJLUKQNAkjplAEhSpwwASeqUASBJnTIAJKlT/wcIGF/zVTOjcwAAAABJRU5ErkJggg==\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"## Correlations Between Attributes\nIs the a mutual relationship or connection between two or more things.\n\nNote: Correlation refers to the relationship between two variables and how they may or may notchange together. The most common method for calculating correlation is Pearson's Correlation Coefficient, that assumes a normal distribution of the attributes involved.\n\nA correlation of -1 or 1 shows a full negative or positive correlation respectively. Whereas a value of 0 shows no correlation at all. "},{"metadata":{"trusted":true},"cell_type":"code","source":"Train.corr(method='pearson')","execution_count":47,"outputs":[{"output_type":"execute_result","execution_count":47,"data":{"text/plain":" FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 \\\nFULL_Charge 1.000000 -0.612996 -0.490977 \nFULL_AcidicMolPerc -0.612996 1.000000 0.794796 \nFULL_AURR980107 -0.490977 0.794796 1.000000 \nFULL_DAYM780201 -0.434603 0.541481 0.548253 \nFULL_GEOR030101 -0.058725 0.115201 0.346139 \nFULL_OOBM850104 -0.283758 0.513344 0.462712 \nNT_EFC195 0.088068 -0.143168 -0.169540 \nAS_MeanAmphiMoment 0.355477 -0.431590 -0.426097 \nAS_DAYM780201 -0.365374 0.449621 0.456260 \nAS_FUKS010112 -0.090570 0.002334 0.032958 \nCT_RACS820104 0.232929 -0.213543 -0.403599 \nCLASS 0.534602 -0.598816 -0.584111 \n\n FULL_DAYM780201 FULL_GEOR030101 FULL_OOBM850104 \\\nFULL_Charge -0.434603 -0.058725 -0.283758 \nFULL_AcidicMolPerc 0.541481 0.115201 0.513344 \nFULL_AURR980107 0.548253 0.346139 0.462712 \nFULL_DAYM780201 1.000000 0.010118 0.334778 \nFULL_GEOR030101 0.010118 1.000000 0.319157 \nFULL_OOBM850104 0.334778 0.319157 1.000000 \nNT_EFC195 -0.090058 -0.230417 -0.230561 \nAS_MeanAmphiMoment -0.408793 -0.160269 -0.336297 \nAS_DAYM780201 0.894191 -0.029085 0.275640 \nAS_FUKS010112 0.055915 0.040480 -0.452769 \nCT_RACS820104 -0.326792 -0.151935 0.155304 \nCLASS -0.554838 -0.260470 -0.453287 \n\n NT_EFC195 AS_MeanAmphiMoment AS_DAYM780201 \\\nFULL_Charge 0.088068 0.355477 -0.365374 \nFULL_AcidicMolPerc -0.143168 -0.431590 0.449621 \nFULL_AURR980107 -0.169540 -0.426097 0.456260 \nFULL_DAYM780201 -0.090058 -0.408793 0.894191 \nFULL_GEOR030101 -0.230417 -0.160269 -0.029085 \nFULL_OOBM850104 -0.230561 -0.336297 0.275640 \nNT_EFC195 1.000000 0.178683 -0.036844 \nAS_MeanAmphiMoment 0.178683 1.000000 -0.322378 \nAS_DAYM780201 -0.036844 -0.322378 1.000000 \nAS_FUKS010112 0.145924 0.025580 0.045562 \nCT_RACS820104 0.080898 0.171524 -0.256060 \nCLASS 0.260702 0.693552 -0.437168 \n\n AS_FUKS010112 CT_RACS820104 CLASS \nFULL_Charge -0.090570 0.232929 0.534602 \nFULL_AcidicMolPerc 0.002334 -0.213543 -0.598816 \nFULL_AURR980107 0.032958 -0.403599 -0.584111 \nFULL_DAYM780201 0.055915 -0.326792 -0.554838 \nFULL_GEOR030101 0.040480 -0.151935 -0.260470 \nFULL_OOBM850104 -0.452769 0.155304 -0.453287 \nNT_EFC195 0.145924 0.080898 0.260702 \nAS_MeanAmphiMoment 0.025580 0.171524 0.693552 \nAS_DAYM780201 0.045562 -0.256060 -0.437168 \nAS_FUKS010112 1.000000 -0.445284 0.033432 \nCT_RACS820104 -0.445284 1.000000 0.267652 \nCLASS 0.033432 0.267652 1.000000 ","text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201FULL_GEOR030101FULL_OOBM850104NT_EFC195AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CT_RACS820104CLASS
FULL_Charge1.000000-0.612996-0.490977-0.434603-0.058725-0.2837580.0880680.355477-0.365374-0.0905700.2329290.534602
FULL_AcidicMolPerc-0.6129961.0000000.7947960.5414810.1152010.513344-0.143168-0.4315900.4496210.002334-0.213543-0.598816
FULL_AURR980107-0.4909770.7947961.0000000.5482530.3461390.462712-0.169540-0.4260970.4562600.032958-0.403599-0.584111
FULL_DAYM780201-0.4346030.5414810.5482531.0000000.0101180.334778-0.090058-0.4087930.8941910.055915-0.326792-0.554838
FULL_GEOR030101-0.0587250.1152010.3461390.0101181.0000000.319157-0.230417-0.160269-0.0290850.040480-0.151935-0.260470
FULL_OOBM850104-0.2837580.5133440.4627120.3347780.3191571.000000-0.230561-0.3362970.275640-0.4527690.155304-0.453287
NT_EFC1950.088068-0.143168-0.169540-0.090058-0.230417-0.2305611.0000000.178683-0.0368440.1459240.0808980.260702
AS_MeanAmphiMoment0.355477-0.431590-0.426097-0.408793-0.160269-0.3362970.1786831.000000-0.3223780.0255800.1715240.693552
AS_DAYM780201-0.3653740.4496210.4562600.894191-0.0290850.275640-0.036844-0.3223781.0000000.045562-0.256060-0.437168
AS_FUKS010112-0.0905700.0023340.0329580.0559150.040480-0.4527690.1459240.0255800.0455621.000000-0.4452840.033432
CT_RACS8201040.232929-0.213543-0.403599-0.326792-0.1519350.1553040.0808980.171524-0.256060-0.4452841.0000000.267652
CLASS0.534602-0.598816-0.584111-0.554838-0.260470-0.4532870.2607020.693552-0.4371680.0334320.2676521.000000
\n
"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"## Plotting to show the correlation\n\nplot a heat map to show us the correlation of the data.\n\nWith the help of ; seaborn\nthe we can use spearman or pearson method.\n"},{"metadata":{"trusted":true},"cell_type":"code","source":"import seaborn as sns","execution_count":48,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#The first step is to choose the figure size then use the heatmap to plot.\nplt.figure(figsize=(7,7))\nsns.heatmap(Train.corr(method='pearson'))","execution_count":49,"outputs":[{"output_type":"execute_result","execution_count":49,"data":{"text/plain":""},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"## we can also check the correlation in regards to the CLASS"},{"metadata":{"trusted":true},"cell_type":"code","source":"Train.corr(method='pearson')['CLASS']","execution_count":50,"outputs":[{"output_type":"execute_result","execution_count":50,"data":{"text/plain":"FULL_Charge 0.534602\nFULL_AcidicMolPerc -0.598816\nFULL_AURR980107 -0.584111\nFULL_DAYM780201 -0.554838\nFULL_GEOR030101 -0.260470\nFULL_OOBM850104 -0.453287\nNT_EFC195 0.260702\nAS_MeanAmphiMoment 0.693552\nAS_DAYM780201 -0.437168\nAS_FUKS010112 0.033432\nCT_RACS820104 0.267652\nCLASS 1.000000\nName: CLASS, dtype: float64"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"# Skew of Univariate Distributions\n### Definition of skew.\n* Is the suddenly change direction or position.\n* or Skew refers to a distribution that is assumed Gaussian (normal or bell curve) that is shifted or squashed in one direction or another. \n\n\nYou can calculate the skew of each attribute using the skew() function on the Pandas DataFrame.\n\n#### NOTE: If skewness value lies above +1 or below -1, data is highly skewed. If it lies between +0.5 to -0.5, it is moderately skewed. If the value is 0, then the data is symmetric\n\n### Positively skewed data:\nIf tail is on the right as that of the second image in the figure, it is right skewed data. It is also called positive skewed data. Common transformations of this data include square root, cube root, and log.\n\n### Cube root transformation:\nThe cube root transformation involves converting x to 𝑥(1/3) . This is a fairly strong transformation with a substantial effect on distribution shape: but is weaker than the logarithm. It can be applied to negative and zero values too. Negatively skewed data.\n\n### Square root transformation:\nApplied to positive values only. Hence, observe the values of column before applying.\n\n### Logarithm transformation:\nThe logarithm, x to log base 10 of x, or x to log base e of x (ln x), or x to log base 2 of x, is a strong transformation and can be used to reduce right skewness.\n\n### Negatively skewed data:\nIf the tail is to the left of data, then it is called left skewed data. It is also called negatively skewed data. Common transformations include square , cube root and logarithmic. We will discuss what square transformation is as others are already discussed."},{"metadata":{"trusted":true},"cell_type":"code","source":"Train.skew().plot(kind='bar')\n#When we look to the data its highly positively skewed","execution_count":51,"outputs":[{"output_type":"execute_result","execution_count":51,"data":{"text/plain":""},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"# Data visualization\n## Understand Your Data With Visualization\nYou must understand your data in order to get the best results from machine learning algorithms. The fastest way to learn more about your data is to use data visualization.\n\n### Univariate Plots\nIn this section we will look at three techniques that you can use to understand each attribute of your dataset independently.\n\nHistograms.\nDensity Plots.\nBox and Whisker Plots.\n\n\n# Histograms"},{"metadata":{"trusted":true},"cell_type":"code","source":"plt.figure(figsize=(16,16))\nTrain.hist()\nplt.show()","execution_count":52,"outputs":[{"output_type":"display_data","data":{"text/plain":"
"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"## Density Plots\nDensity plots are another way of getting a quick idea of the distribution of each attribute. The plots look like an abstracted histogram with a smooth curve drawn through the top of each bin, much like your eye tried to do with the histograms.\n\n"},{"metadata":{"trusted":true},"cell_type":"code","source":"Train.plot(kind='density', subplots=True, layout=(3,4), sharex=False)\nplt.show","execution_count":53,"outputs":[{"output_type":"execute_result","execution_count":53,"data":{"text/plain":""},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"## Box and Whisker Plots\nAnother useful way to review the distribution of each attribute is to use Box and Whisker Plots or boxplots for short."},{"metadata":{"trusted":true},"cell_type":"code","source":"#boxplots help to represent outlies\nTrain.plot(kind='box', subplots=True, layout=(3,4), sharex=False, sharey=False)\nplt.show()","execution_count":54,"outputs":[{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"## Multivariate Plots\nThis section provides examples of two plots that show the interactions between multiple variables in your dataset.\n\n* Correlation Matrix Plot.\n* Scatter Plot Matrix.\n* Correlation Matrix Plot\n\nCorrelation gives an indication of how related the changes are between two variables. If two variables change in the same direction they are positively correlated. If they change in opposite directions together (one goes up, one goes down), then they are negatively correlated. You can calculate the correlation between each pair of attributes. This is called a correlation matrix. You can then plot the correlation matrix and get an idea of which variables have a high correlation with each other. This is useful to know, because some machine learning algorithms like linear and logistic regression can have poor performance if there are highly correlated input variables in your data."},{"metadata":{"trusted":true},"cell_type":"code","source":"Train.columns","execution_count":55,"outputs":[{"output_type":"execute_result","execution_count":55,"data":{"text/plain":"Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n 'CLASS'],\n dtype='object')"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"correlations = Train.corr()\n# plot correlation matrix\nfig = plt.figure()\nax = fig.add_subplot(111)\ncax = ax.matshow(correlations, vmin=-1, vmax=1)\nfig.colorbar(cax)\nticks = np.arange(0,9,1)\nax.set_xticks(ticks)\nax.set_yticks(ticks)\nax.set_xticklabels(Train.columns)\nax.set_yticklabels(Train.columns)\nplt.show()","execution_count":56,"outputs":[{"output_type":"display_data","data":{"text/plain":"
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ZiCIAgakLZi5hnUJevlOyZJrZKm5o7hkiZI+mlJuvtc1A5JcyUNK4lfLU8HZQ6S9HNJz0iaKel+Sft72WVXXAdBEJQjCXFZTUcjsr72mJaVav1IxU0nrsBlJGG6EZYUNXcgSW+/2hmjknqZWfUFKEEQNBXN3GNaXx1TlyJpR9K2HZ82szYAM3sWeFbScKCnpF8AHwReAsaa2TJJnyVtAdKH9OLxRDN7R9KVpJXaewGPSboA+A2wMelF5BhgHzN7XdI/kxRM+wAPA/9qtupUHd+37HOQFs8GQVDfGLCyiZUh1suhPKB/bhjvpi4ob1dgaqlDyDECuNjMdgXeBD7p4Tea2b5mtgfwJHBKLs9OwGFm9jXSLJp7zGxv4CaS6B6SdgaOBw70HmIr8OnSws1skpmNMrNRm2zcs7P3GgTBOsZqHMaLobzGYrWhPCqvWO6KT/Y5M5vq548Cw/18N0nfBQYDg1h1jcBvc47uIOAYADO7XdIiDz8U2Ad4xIcq+wML1tVNBEHQRRi0NqbPqYn11TGV4w2gdGfcocDrBdieCewhqUc2lFfCitx5K8mBQNr192gzmyZpAmmtQcbbufNKL8gEXGVmZ61NpYMgqE/Szg/Ny/o6lFeOR4ADJW0O4LPx+rLqJoVrhZk9A0wBvi3vukgaIWlslawbAPMl9abMEFyO/wOOc7tH0O5g7waOlbSpxw2VtN3a30kQBPWBaK3xaESix+SY2auS/g24TVIPYCkwvqSHM11Sdn09MB2YIOnoXJoDzGxemSJOBS4C5kh6h9RDO7NKtf6DNGHheWAGyVGV49vANZKOB/4MzAeW+OSHc4A/+T2tJC2U69QGkkEQdC9p8kNjOp1aWC8dk5kNqhD+e+D3FeKGVzB3ZY1lvgV8tkL0brl0P8id/wwX5SqxNaEkaDFwpJm1SPoAcLCZrfC01wHX1VLHIAgag7SOKRxTUN9sC1zvvaJ3qewAgyBoEtqixxTUiqSHSe+m8pxoZjPWVZlmNpu0pikIgvWA6DEFa4SZ7d/ddegMs54bVojI312/KWZfx7uXFbOu6qaFndFJW5Vbp40sxM7eo58qxM6Dt+5eiJ3W+zYtxM42X5xTiJ1pj+5YiB2AAY9Uej27Zjx96a6F2Okshmht4rlr4ZiCIAgakBjKC4IgCOoGQ7xrzbtLSzimIAiCBiMtsI2hvCAIgqCOiMkPQRAEQd1gJlqteXtMzXtnQRAETUwbqumoBUljJD0taY6kiWXif5hTZJgl6c1cXF54dXIR99bljqk71GM9/V6STNKRNaT9gqSTyoS/pzYraZSkn1SxM1fSAyVhU6sp1koaLekPfj5B0mue7wnXaAqCYD0mTX7oVdNRDUk9gYuBo4BdgPGSdlmlPLOvmtmersrwP8CNuehlWZyZfbyI++uOobzuUI8FGE/a7HQ8q8pHrIaZXVrNmJlNIW3MWo0NJG1jZi+6PtLacJ2Zneabsc6UNNnMqirfhrptEDQnBU9+2A+Y4+KlSLoWGAs8USH9eJIG3DpjvRjK8x29jwUmAEdI6peLO0nSdEnTJP3aw86VdIaf7+NxD5I2QM3y5Xs1gyRdIWmG2/pkrvjrSWJ9kD7Qa3I2+uXy/V3SwR3dh5ktAJ4BtpM0UNLlkh7xvGPd5gRJv5V0C/AnD/u6lzHN1W6DIGhwWk01HTWwFauqKMzzsNVwdYLtgXtywf0kTZH0UMmG1mtNd/SY+kvKRPGeM7NjuqDMA72sZyTdB3wUuFHSrsDZJIXX1yUNLZP3CuDLZvZnSRdWsP8fwGIzGwkgKa/rdANpo9cfAB8jyVec6HFfAjCzkZLeT9oFfKdKNyFpB2AHksz62STV2n+RNBj4m6S7POkHgN3NbKGko4Cjgf1dln21e1ROWr1v38GVig+CoE5Yw50fhknKj+5MMrNJuety3quSDOE44IYSNe5tzexlb5/ukTTDpX7WmroYymPdq8eOB67182tJjuFG4BDSQ34dwMwW5jNJ2ggYbGZ/9qBfk8ZhSzmM9IHhdhbl4hYCiySNI8mjv5OLO4g0XouZPSXpeZJkeinHSzqIJCj4eXc4RwAfz3p2QD9cUh24M3cvhwFXmNk75e7RwyYBkwA23HDrJtbFDILmoa32WXmvm1lHe3LNA7bJXW8NvFwh7ThyI0cAZvay/33Wf/jvRRrZWWvqZbr4OlOP9Rd7nyQ14meTfh1sLGkDP++oIa4WX2u660gvFyeUyVcL15nZaWXyftLMnl4lUNqf1dVtw9kEQRORNnEt7E3MI8AISdsDL5GczwmliST9A6mdfjAXNgR4x8xW+AS1A4Hvd7ZC9fKOaZ2px5J6DNPMbBszG25m2wG/Iw1v3Q0cJ2ljL3eVYS4zexNY7L0VqKwi+yfgPcdRMpQHcBPpwyqddHF/ZtOH8LYFnqY27gC+7O/PkFRpd/E/Af8iaYCnKzdcGQRBA2GIldazpqOqrTRB6jRSm/IkcL2ZzZR0nqT8LLvxwLVmlv+huzMwRdI04F7gAjOrNGmiZuqix7SO1WPHkxxDnt8BXzSzX0s6H/izpFbg76zeq/kMcLmS6myl2XzfBS72aeCtJEXZ96ZTmtkS4Huw2gzES4BLJc0AWoAJ/sujQjGr8B3gR6TnImAu8E+liczsdkl7kr487wK3Af+vlgKCIKhPzCh0ga2Z3UZqG/Jh3yy5PrdMvr8CxWy3n6PLHVNXq8eWUXvFzCYDk/38KuCqkvhzc+ePAnvkos/18PuA+/x8KXByLfU2s7m4Yq2ZLWd1R1hq+0rK3KeZLQM+XyZ8tfRmdgEQs/GCoGmoffFsI1IXPaYgCIKgdoxie0z1RlM5JnWDemwQBEF3EEKBDUKjq8fWA209xYqhvTttpyjl2UP7t1ZPVAO/V1v1RDWy5darzbhfK5a0lP6GWjtUzCOqfY5oFXqomEmg1qu4yaQDXimoTnXiCwyFUGAQBEFQPxiwsoZ98BqV5r2zIAiCpkWhxxQEQRDUD8Ya7fzQcIRjCoIgaECixxQEQRDUDWaKHlMQBEFQP6TJD8XMfK1HutXlqo7UbJVTp82F5XWZrpT0nNdzmqRDS+r3tIc/4lsAZXHHu0bTTEnfz4VvK+le11KaLumjubizlCSOny6p4+WSFpSp51BJd0qa7X+HePiZuWf7uD/v2CsvCBoe0Wo9ajoake6udV6Sd0/frqcryKvZrglnumTHvwOlKrefNrM9SPvfXQjgm8NeCBxqZrsCm+Uc2jmkzRL3Iu3me4nn2cWvdwXGAJf4DumQthoaU6ZeE4G7zWwEaWPaiQBmdmFODvks4M/lZC+CIGgs0uQH1XQ0It3tmLoc3/C0rJrtGvAgFRQeS+J2AGaZ2Wt+fRdJggPSd2tDP9+Idv2TsaQdfFeY2XMkUcD9AMzsfpK+Uyljad/v7yrSzumlrKKeGwRBY9NKj5qORqS7a90/N9RUugP4uuI9NVvSRqkf7Th5WcYAN9cQNwd4vw8T9iI5jEyQ61zgnyXNI+3q+2UPr1nmOMdmZjYfwP9umo90yYsxpF3VV0PS55SkkaesXLG0SlFBEHQ32c4Pzdpj6u7JD/WkZltLuRf6e6JNgQNK0l0taSDQE9gbkpKtpC+ShALbgL+SelFZPa40s4skfQD4taTdWDOZ41r5GPCXSsN4eQXbQUO2CVHBIGgA2rq9X7HuqMc76wo1229KmkuSNT/K1WxrKfdM4H2k90NXlaT9NLA98BuSWi0AZnaLme1vZh8giQDO9qhTSLpSmNmDJGn0YayZzHHGq5K28HvcAlhQEj+OGMYLgqbBDFa29ajpaETqsdbdombrmkrzs8kJPnttDGmSxHu4eOGPgR75GXMet5LktA6QtLPb2dT/DgH+FbjMk78AZGXtTHJMr5F0osZJ6qskdTwC+FuV+5pMux7UyeR0rSRtBHyEClpXQRA0Hmkor0dNRyNSd7U2s1eBTM12KkmltZya7Tw//tvDJuTC5knauoz5Smq2mb79ScA5Xu49wLf9XVRpHY2kWvv1MnHLgIuAMzzox5KeAP5Ckh2e5eFfAz7rksTXkNRrzcxmknpSTwC3A18ys1YASdeQJlf8g9/jKW7rAuBwSbOBw1lVFPAY4E9m9naZ5xEEQYPS6vvlVTsakW59x1SHarZPAAfXktfMfodPJjCz0SVxF+XOy05J97IOrBB3PnB+mfBKtt7Ae19l4q6khmcTBEHjkE0XLwpJY0gjQT2By1z1Oh8/gbT05SUP+qmZXeZxJ5NGigC+66rgnaK7Jz8EQRAEa0xxWxL5u/eLSaMt84BHJE32H895rjOz00ryDgW+BYwi+ctHPe+iztSpaR1TqNkGQdDMtBU3TLcfMMfMngWQdC1pbWSpYyrHkcCd2YxfSXeS3s13arJV0zqmULNdO6wHtPTt/Bf+poWjCqhNccqzP9nykULsAOz4f/sUYqd1p2J+8bYMqC911gu3rbTEb804ZMbphdgBaBlQjB3rVR+v5dOsvML2yiu3drJc+/lJSR8GZgFfNbMXK+Sttu6yKvXxlIMgCIKaWcMFtsOyBfR+fK7EXC1rJ28BhpvZ7qQdbLL3SOti3WXz9piCIAiamTUYynvdzDoawqi6dtInWGX8AvheLu/okrz31VqxSkSPKQiCoMEoeBPXR4ARkraX1Ie0IH9yPkG2gN/5OPCkn99B2nN0iK/VPMLDOkX0mIIgCBqQomblmVmLpNNIDqUncLmZzZR0HjDFl9R8RdLHgRbSRtITPO9CSd8hOTeA84pQMAjHFARB0GCYiZYCd3Uws9tIm0nnw76ZOz+LJJ1TLu/lwOWFVYZwTEEQBA1Jo+4cXgvd9o5J3aBe6/ln+PGEpO9K6luS5quSlvsec0jaVEm5dvNcmkskTZQ0WkkJ95RcXKaOmynfXpe7x7m+3RGSeku6yuvypKSzcjbGKKnXzpE0MRd+tYc/rqRm29vDJeknnn66pL1zeW6X9KakP9TyjIIgqH9CKHDd0V3qtQeb2UjSorIdcLmHHONJ46XHAJjZAtIMlB8AeKN/EGk/PIAZwPG5/OOAadmFmR2fU5H9HUliA+BTQF+vyz7A5905Z6uwjwJ2AcYrqdoCXA28HxgJ9AdO9fCjSJu9jgA+B/wsV58LSdIeQRA0EeGYmhDfTfwLwNG+rQaSdgQGkfZ9yu9LNwnYUdLBwE+B03wncUi7hPeTtJkkkVY9/7G0PI87jvYV0QYMVBIQ7A+8C7xFbhW2mb1L0owa63W+zTd6NdKO49lGtWOBX3nUQ8DgbBaNmd0NLOnMswqCoL5odqHA7nRM3aFeuwpm9hbwHKmnAe3y4w+QdvDe1NO1AV8k9XhmucR5nhtIPaAPAo8BK8oU9yHgVTObncvzNjCf5Nx+4LNZqq6k9iG8E0m7j1NLno5QTsG2ZXlsQh4EjUAbquloRLpz8kN3qNeWI//JjQOOMbM2STeSnM3FAGY2VdLjwCVlbFxPUql9P8mxfbBMmszpZewHtAJbkgQKH5B0F7WtpL4EuN/MHihzD5XyVCSvYDtw41CwDYJ6xwxaGlQEsBbqbVbeOlOvLYeScu1wYJak3Uk9pzvTqBt9gGfJqdGS5NFX27zNzF6RtJK0O++/UeKYfLjuE6R3SRknALf7kOACSX8h7dD7Ih2swpb0LWAT4PO5NGujehsEQQPTqMN0tVBvLnddqteugqRBpJ7Hzb5F+3jgXFe2HW5mWwJbSdquRpPfBL6RifqVcBjwlJnNy4W9ABziM+oGAgcAT9HBKmxJp5J28y0VTpwMnOS2DgAWm9n8GusdBEGD0ezvmOqqx2Rmr0rK1Gt7AEspr16bXV8PTCep1x6dS3NAiRPIc69PROhBUrP9joePI81uy3OTh3+PKpjZXzuIHsfq28BfDFwBPE4airvCzKYDlFuF7XkuBZ4HHvRe3Y1mdh5pYdxHgTnAO8BnskIkPUAaYhwkaR5wipl1esuQIAi6F2tQp1ML3eaYulq9tkp+zGz7MmGnl1yPLrm+jzIbFprZuSXXE8qkWUp6h1WuLqutwvbwsp+Xz9L7UoW4D5ULD4KgsWnUiQ21UFc9piAIgqA6Zs39jqkpHZNCvTYIgqZGtMasvMYi1GuDIGh24h1TsN7Q2h/e2KPzX/hbp40soDaw5da/fV/OAAAffklEQVSd3kEfKE4OHeCZ4y4txM6+jx1XiJ2+i4ppoN7arhg7h19/ZiF21H+1lRlrzbJNirm3ln69C7Gz+t4wa0a2V16zEo4pCIKg0bD0nqlZCccUBEHQgMSsvCAIgqBusJj8EARBENQbMZQXBEEQ1BXNPCuvefuCQRAETYpZcky1HLVQSTU7F3+6q35Pl3R3fg9RrapGPrmI++tWx6TukVcfJOlnkp6R9HdJj0r6rMcNl7SspE4nedxGkn7l+Z7x843K5HvC43rnyjzLP/CnJR3pYf0k/U3SNEkzJX07l357SQ9Lmq0kzd7Hwz8s6TFJLZKOLbmvkz39bEkn58LPl/SipKW1PJ8gCBqDojZxVceq2Rl/B0aZ2e4kLbnv5+LyauQfL+LeurvH1B3y6pcBi4ARZrYXSXF2aC7+mZI6/crDfwk8a2Y7mtmOJIHBy0rzkWTPtyap1eIf8DhgVy/rEv8irAAOMbM9gD2BMb4zOKRNY39oZiO8rqd4+AvABOA3+RtSUuD9FrA/SefpW5Iy+ZBbPCwIgibCrLajBiqqZreXZfea2Tt++RDt6tnrhO52TF2KknT6fsA52Y7lZvaamXW4e7ik95G0lL6TCz4PGOU238NlL/5Gu4LsWOBaM1thZs+RdgDfz2XQs15Mbz/Mdz4/hPSrBOAq4Gi3Pdd3IC9deXgkcKeZLXQJjztJThAze6iaBIZyCratb4eCbRDUO4Zoa+tR0wEMy/5/+/G5EnNrqoB9CqsuEe7ndh8qUXlYa7p78kN/SVP9/DkzO2Ydl7crMK1ERqOUHXN1AvgySbxwal5rycxaPd2uJOkNIA3RkXou/+ZBW5F+YWS896F7z+lR4H3AxWb2sA9TvmlmLaXpO6BT0up5Bdt+W4eCbRA0AmvwH/V1MxvVQXzNCtiS/pkkaPqRXPC2ZvaypB2AeyTNMLNnaq/e6nS3Y+pWeXVJZ5OkJzZ1YUBoH5LLpxtboXzlwjOHNgK4IdNWooMP3R3dnpIGAzdJ2g14tVL6jm5lLfIEQdCoWKGz8mpSwJZ0GHA28BEzW/FeVcxe9r/PSroP2AvolGOqx6G8dSmv/gSwh4sQYmbnuxPasEq+mcBeWT4AP98DeNKDMof2PuAASdlLwKofupm9SdJ1GkO6z8FKcuxl05chpNWDYH3DajyqU1E1O0PSXsDPgY+b2YJc+BBJff18GHAgqZ3tFPXomNaZvLqZzQGmAN/1YbRs6K3Dnx6e7+/AObngc4DHPC6fdj4wETjLgyYD4yT1lbQ9qUf1N0mbeE8JSf1pl1834F4gm3V3MhWEE3PcARzhX5IhwBEeFgRBk1LUdHF/bZCpZj8JXG9mMyWdl/uBfSEwCPhtybTwnYEpkqaR2q0LzKzTjqm7h/JWowvk1U8lPeQ5khYCy4Bv5OJL3zFdbmY/Ib3w+x9Jc0iO7EHaZ8uVcjNwrqQPmdkDkq4n/YpoAb7k76e2AK5yB9mD9GX4g+f/BnCtpO+SHOIvASTtS5J7HwJ8TNK3zWxXM1so6Tskpw5wnpkt9DzfB04ABihJq19WqrAbBEFjYUBbW3ELbMupZpvZN3Pnh1XI91fSTORC6VbH1E3y6m8Bn68QNxfoXyFuEfDPHeTbLXdtpGG+7Pp84PySPNNJY7Hl7D1LmSneZvYIFaZpmtnlwOVlwr8OfL1cniAIGhQDmnjnh7rrMQVBEATVib3yGhCFvHoQBM1MOKbGI+TV144eK2HgvM4PEew9+qkCagNLWkp/W6wdrTsVN8+nKOXZR/a+vhA7u9/7r4XYGbCgmJau175vFmJn0DUbFWIH4JWPLi/EzpBb+xRip/PUvg9eI9K0jikIgqCpiR5TEARBUDcYWIGz8uqNcExBEAQNSTimIAiCoJ6IobwgCIKgrgjHFARBENQNTb7Atsv3ylP3qNZWVJ/1+F0l3SNplivA/ofrImXlvOZ1nSnpBkkDPO5cSeZ6TZmtr3pYVvfxkmYoSRLfnt2H530p9xw+mrOxmuKth18uaYGkx0vub6ikO73ud6pdJDCL39ef+yqqt0EQNC4FCgXWHd2xiWt3qNZWVJ/1DVQnkzYf3Im0ldAHgfzikOu8rrsC7wLH5+JmkHbjzTgW313Xdwj/MXCwSxJPJ22WmPHD3HO4zfNUUryFtO3SmDL3NxG42xVv7/Zr3F5PkiJubOoaBM1Em2o7GpB63F28UFRdffYE4C9m9icAlw8+jVzjnrPVCxhIkjvPuBmXIXahrMXAa1kWPwZ6D2xDqstRlFW89brdDyyskOcqP39P8db5MvA7YEFpptx9vadg27IsFGyDoBGQ1XY0It3hmPrnhq9u6oLydqGM+iyQqc/uSlKRJRf/DDBIUqbTdLzvOP4SSRvqllzyt4AXlUT+xgPX5eysBL5I6lW97HX5ZS7vaT7Ed3lu+G1t1Gg3y+TT/e+mAJK2Ao4BLu0os5lNMrNRZjaqV/+BVYoKgqDbqVWLKRxTzeSH8jIp9XWpWptXmS0XXik+X/51LgK4OcnJnFmS7lrS8NvRJFmKVIDUm+SY9gK2JA3lZTpNPwN2BPYE5gMX5epVqR5ryo+Ab+SdchAEzYDS5IdajgakXoby1qVqbTX12ZkkDXty8TsAS81sST7c5SxuAT5cUsYtwInACy6rkbGn53vG815Pen+Fmb1qZq2uM/UL2mUu1kaN9lXXd8L/ZsN2o0i6TnNJ774uKdGsCoKgUYke0zpnXavWdqQ+ezVwkJKefTYZ4ifA9yuYPIgSPXszy8QGzy9J+xKwi6RN/PpwXIo9cyTOMUA2066s4m2V25xMUrqFnOKtmW1vZsNdw+oG4F/N7OYqtoIgaATaajwakLpYx9QFqrUV1WfNbJmksR5/MdAT+DWQn4p+vKSDSI58HjChzD1cWybsZUnfBu6XtBJ4Ppf3+5L2JP2mmYuLF7qk8WqKtwCSrgFGA8NcjfZbZvZL4ALgekmnAC8AnyrzDIIgaBaafB1TlzumblKtrag+6/EzSA1+ubgrK5VTSaLczEbnzi+lzOQDMzuxg/qspnjr4eMrpH8DOLSSPU8zoaP4IAgaiyJn3EkaQ1ra0hO4zMwuKInvC/yKNMP5DeD4bKmPpLNIP/Rbga+YWaeXptTLUF4QBEGwJhT0jsnXOl4MHEWaOTze11PmOQVYZGbvA35IWhtZbd3lWtNUjknSwyW7SkyVNLK76xUEQVDH7AfMMbNnzexd0izjsSVp8mslbwAO9bWZFddddoa6eMdUFKFa23la+xtvjlzZaTsP3rp7AbUBFTTRvWVAceMefRcVM7ZflPLs9K9dUoidHe/5TCF2eswaXIidpUe9W4gdAFtWTFO3eNyS6olq4brqSaqxBkN5wyRNyV1PMrNJuetyaydL29L30phZi6TFwMYe/lBJ3mrrLqvSVI4pCIJgvcBYk+2GXjezUR3E17J2slKaItddvkdTDeUFQRCsNxS3jqmWtZPvpfGt2TYibY+2NusuqxKOKQiCoAEpcK+8R4ARkraX1Ic0mWFySZr8WsljgXt804C1WXdZlRjKC4IgaEQKem3q74xOIykQ9AQu9/WU5wFTzGwyaY/PX/ta0IW4okJH6y47QzimIAiCRqTAdUwuu3NbSdg3c+fLqbBwv9K6y84QjikIgqDBaGRJi1qId0wVcBXai3LXZ7jq7Nm5NVJ5Nd6vVLBTqlQ7VdJgSaMlLc6F3ZXLc5Kkx5UUc5+QdIaHf8rD2nw/wSx9H0lXKCnlTpM0Ohd3n5ISblbOpuvkgQVB0LU0sVBg9JgqswL4hKT/MrP3djnPd1slLXU5jGr80Mx+kA9Ia9N4wMz+qST8KODfgSN8r71+pJ3LIW30+gng5yX2P+t1G+mO54+S9s3tNfhpM5tCEARNQ/SY1k9agEnAV7u43LOAM8zsZUhju2b2Cz9/0syeLpNnF5KkOma2AHiTEimPjsgr2LYuCQXbIGgIQvZiveVi4NOSNuqkna/mhtLuzYV/KBd+toftRomibg1MA8ZK6uVTNvdh1bUFV3gZ/+HbiKxCXsG25wahYBsEdU+NU8UbtVcVQ3kdYGZvSfoV8BVgWSdMrTaU56w2lLeWXA7sDEwhSWv8ldTjgzSM95KkDYDfkYYFf1VAmUEQdCcN6nRqIXpM1fkRaWfdrupKzCT1eGrGzFrM7KsuVz8WGAzM9riX/O8S4DcUsMFiEATdj9pqOxqRcExVMLOFJGHCU7qoyP8iiQhmar59K834y5A0QNJAPz8caDGzJ3xob5iH9wb+iXal3CAIgrokhvJq4yLgtE7k/6qkvFDh0ZUSmtltkjYD7vL3QUYaqkPSMcD/AJsAt0qaamZHApsCd7jC70u0z+Lr6+G9SSu67wJ+0Yn7CIKgXmjiobxwTBXIK+2a2avAgI7SdGDnXODcMlFzgfsq5LkCuKJM+E3ATWXC5wL/UCb8bdZwWDAIggaggSc21EI4piAIgkYkHFNQDZ/uXbqX1G99QW4QBEGxhGMKqrEuNjLsDnr3aWGr7d7otJ3W+wra+aigHVWswGk+b21XTKUGLCimZSlKefaZQ1YbPV4r9vn2Fwuxs6hfcc1TjyHFqOF+Zed7qyeqgc4+IdG4M+5qIRxTEARBoxHvmIIgCIK6IxxTEARBUFeEYwqCIAjqiRjKC4IgCOqLJnZMsSVREARBo2Fds1eepKGS7pQ02/8OKZNmT0kPuojpdEnH5+KulPRcTkWhFv262hyTpGNc0fX9ft1D0k9cZXWGpEdcbqFS/rmSHigJmyppnezb5nvEvS7pvwq2u7RC+BckneTnV0p6x3fzzuJ/7M9vWJH1qRVJ/687yg2CYB3SNXpME4G7zWwESfNtYpk07wAnmdmuwBjgR5IG5+LP9A2m9zSzqbUUWmuPaTzwf8A4vz4e2BLY3cxGAseQxOk6YgNJ2wBI2rnGcteWI4CngePK6Q8VjZldamZ5KYk5wFhIThw4mLSHXXcRjikImowu0mMaC1zl51dRZp9PM5tlZpmawcvAAtJ+nmtNVcckaRBwIGl37cwxbQHMz6S7zWyemS2qYup6kkOD5OiuyZXRU9KF3vOaLunzWdmS7pb0mPfMssZ+uKQnJf3Cu49/ktQ/V9Z44MfAC8ABuXLmSvpP73ZOkbS3pDskPSPpC55mtKT7Jd0k6QlJl7pzyWycL2mapId8s1UknSvpjFz51+TudTTwF9r1kZB0uvc2H5f077l7ekrSZR5+taTDJP3Fu9H7ebqBki73Z/X33DOZIOlGSbd7+u97+AVAf++hXl3ug1FOwXbl4s7ITgVB0GXU3mMalv3/9uNza1DKZmY2H8D/drhy3tupPsAzueDzvV3/oaS+tRRaS4/paOB2M5sFLJS0N8nJfMwbu4sk7VWDnRuAT/j5x4BbcnGnAIvNbF9gX+CzPjS4HDjGzPYm9TouyvWARgAXe/fxTeCTAO6gDgX+QHIQ40vq8aKZfQB4ALgSOJbkvM7LpdkP+BowEtgxV++BwENmtgdwP/DZCvc6G9jEx2PHA9dmEZL2AT4D7O/lfjb3/N5Hcqi7A+8HTgAOAs6gvddzNnCPP6uDgQvlkhfAniSHOBI4XtI2ZjYRWObd6E+Xq2xewbb3Rv3LJQmCoJ6o1Sklx/R69v/bj0l5U5Luyv1Qzh9j16RKkrYAfg18Juu0AGeR2rJ9gaHAN2qxVYtjyjes1wLjzWweaTfrs4A24G5Jh1axsxBYJGkc8CRpXDLjCOAkSVOBh4GNSY5HwH9Kmk6SbNgK2MzzPJcbr3wUGO7n/wTca2bvkBRbj5HUM1fWZP87A3jYzJaY2WvA8ty46N/M7FkzayU5t4M8/F2Swystsxw3knqY+5OcYMZBwE1m9raZLfV0H8rd0wz/UGeSxnbN65qVdQQw0Z/VfUA/YFuPu9vMFpvZcuAJYLsO6hcEQYMiihvKM7PDzGy3MsfvgVfd4WSOZ0HZ+kgbArcC55jZQznb8y2xgqSYUJNQaYfTxSVtDBwC7CbJSJo+JunrXtAfgT9KepXUs7q7SnnXARcDE0qLAr5sZneUlD+BNFa5j5mtlDSX1BADrMglbQWyn/rjgQM9LSQndzDJseXztZXYaKP9eZR+nNn1SncUWZkdPb9rgceAq8ysLfeqq6N3XqX1ydc1K0vAJ83s6XxGSfuz+jOJ5QBB0KR00TqmycDJwAX+9/er1UPqQ5Lj+ZWZ/bYkbgszm+8jXUdTo1BptR7TsV7YdmY23My2AZ4DPixpSy+4B2no6fkayrsJ+D5wR0n4HcAXlQTtkLSTD09tBCxwp3QwVXoA7rUPArb1+g4HvsTqw3nV2E/S9n5vx5MmfqwRZvYCadjtkpKo+4Gj1a46ewyr9qiqcQfw5WxIs8Zh1JXZsw2CoEnomll5FwCHS5oNHO7XSBol6TJPcxzwYWCCVp8WfrWkGaRRn2HAd2sptNov6vFZRXL8jvRuZmHuRdbfgJ9WK8zMlgDfA9Cqk+UuIw1VPeYN7msk73o1cIukKcBU4KkqRXyC9P4l33P4PUmqvKaXbs6DpPseSXIkq4nz1YKZ/bxM2GOSriQ9M4DLzOzvkobXaPY7wI+A6f6s5pKGLztikqd/rNJ7piAIGowu6DGZ2Rukd/al4VOAU/38f4H/rZD/kLUpV+0jUwGkWXnAGWZWrbFvSgbttLnt/tOTO22n9apmlr0oxlhRsheLPrK8EDt1J3uxa3G6DipI9uIbo0oHe9aOL77//kfNbNTa5h+w6Ta20/Gn15R22k9P71RZ3UG8gwiCIGhEmrhPUahjkvQwUDpkdqKZzSiynHWJmd1Hmu0WBEFQt4RQYI2Y2f5F2gu6HlvUmxXXb1Y9YRW2+eKcAmoDPQqaenThtjcXYgfg8OvPLMROr32rbZZSGz1mDa6eqAaKGoJ79Fs/K8TODjd+vhA7AIMeLWZ93hW3fbwQO+nVdeeI3cWDIAiC+qGYGXd1SzimIAiCRiQcUxAEQVAvZDs/NCvhmIIgCBoQtTWvZwrHFARB0GjEO6YgCIKg3mjmobyGkVZXMSq6M/x4QtJ3S7cpkvRVScslbeTXmyrJAm+eS3OJpIlKuk0m6ZRc3F4edoZfX5fbO2qu7wiOpN6SrvK6PCnprJyNMZKeljRH0sRc+NUe/riSHlO2r6D8OcxR0jzZO5fndklvSsp2RA+CoFnomr3yuoWGcUwUo6J7sKfdD9iBtIdcaRmPuC3MbAFpb78fAHijfxBwkaefQbsgIF63admFmR2fSQqT9hi80aM+BfT1uuwDfF5JKLAnaff1o4BdgPGSdvE8V5N0TUaSdlI/1cOPIkmEjAA+B+QXkVwInFjlmQRB0IB0kYJtt9AQjknFqejiaZcCXyDt8j3Uy9gRGAScw6q7kU8CdvTdzX8KnGZmKz3uBaCfpM18Q9UxJCmQ0vqLtANvptprwEBJvUhO5l3gLZLDnONaUO+SpDPGep1vc10TI20Au7XbGkvaAd5cB2Vwpp9iZncDS6o9D+UUbFuWvV0teRAE9UD0mLqdolR038PM3iJJeIzwoEzu/QHgHyRt6unagC+SejyzzKx0yfYNpB7QB0n6SytYnQ8Br5rZ7Fyet4H5JOf2AzNbSBJCfDGXb56HvYcP4Z0I3O5BVfNUI69g26v/wOoZgiDoXixtSVTL0Yg0imMqSkW3lPze1eOAa90R3UhyNgC4Uu7jrK6tBMlBfop2x1ap/vm4/UhCflsC2wNfk7RDSX3eK77k+hLgfjPLNJxqyRMEQRNRpIJtPVL3s/JUvIpuZncDkgbULEm7k3pOd7pOVB/gWdL7now2P1bBzF6RtJIkovVvpJ5TvpxeJJ2ofXLBJ5B6gCuBBZL+Aowi9Xy2yaXbGng5Z+tbJEXf/CZi8zrKEwRBk9LEkkWN0GMqWkU3e2d1CXCzv5caD5ybqd6a2ZbAVpI6VMzN8U3gG2bWWibuMOAp7+FlvAAc4jPqBgIHkEQQHwFGKKnn9iH14iZ7nU8FjiT1FvMOcjJwkts6AFhsZvNrrHcQBA1K9Ji6lyJVdO/1iQg9SKq03/HwcaTZbXlu8vDvVaugmf21g+hxrD7EdzFwBWl4UMAVZjYdQNJpJPn0nsDlZjbT81xKcrwPeq/uRjM7D7gN+CgwB3gH+ExWiKQHSDP5BkmaB5xiZsUonQVB0H008MSGWqh7x2Rmo8uE/QT4yRraGd5B3Grrn8zs9JLr0SXX91FGt8nMzi25nlAmzVJy77BK4m4jOZvS8LKflc/S+1KFuA+VCw+CoPHpiokNPmv5OtJrj7nAceVmP0tqJS2fAXjBzD7u4duT5gUMJU0OO9FnHHdIIwzlBUEQBCV00ay8icDdZjaC9P5+YoV0y7I1m5lTcr4H/NDzLyIt+alK0zkmSQ/ndlvIjpHdXa8gCILCMNLkh1qOzjEWuMrPryJNMKsJf21yCGl5zBrlr/uhvDUlVHQ7R2sfeGuHztuZ9uiOnTcCWK9iBtIPmXF69UQ1ov7FjKEMumajQuwsParqyEhNLOpXTHNQlPLss5/4eSF2AD54+hcKsfPKgQW92PlN502swcSGYZKm5K4nmVnprjeV2CybTGVm87P1nWXo52W0ABeY2c3AxsCbZtbiaWpeY9l0jikIgmC9oHbH9LqZjaoUKekuYPMyUWevQW22NbOXfT3mPZJmkHazKaWmWodjCoIgaDCKFAo0s8MqliO9KmkL7y1tASyoYONl//uspPuAvUizpwdL6uW9pprXWDbdO6YgCIKmxwy11XZ0ksnAyX5+MvD70gSShmTLdiQNI+1r+oTPGL6XtBa1Yv5yhGMKgiBoRLpmE9cLgMMlzSbtbnMBgKRRki7zNDsDUyRNIzmiC8zsCY/7BnC6pDmkd06/rKXQGMoLgiBoQLpiVwczewNYbQ9SM5uCS+/4BgNlZz6b2bOkvUHXiHBMQRAEjYYBnR+mq1vCMQVBEDQizeuXwjEFQRA0Io26QWsthGMKgiBoQAqYcVe3hGMKgiBoNGJ38SAIgqCeSAtsm9czhWMKgiBoRLpA9qK7CMcUBEHQgESPKQiCIKgf4h1TEARBUF8Usg9e3RKOKQiCoBGJobwgCIKgbrBCZNPrlnBMQRAEjUj0mIL1hn5taKelnTYz4JENCqgMDHilmP98LQMKMQPAsk1UiJ1XPrq8EDu2rJj/xj2GFCPRPujR/oXYKUoOHeCv/31pIXZGPnxCIXYKoXn9UjimIAiCRkRtzTuWF44pCIKg0TBigW0QBEFQPwiLBbZBEARBndHEjqlHd1cgCIIgWAvMajs6gaShku6UNNv/DimT5mBJU3PHcklHe9yVkp7Lxe1ZS7nhmIIgCBqN7B1TLUfnmAjcbWYjgLv9etWqmN1rZnua2Z7AIcA7wJ9ySc7M4s1sai2FhmMKgiBoQNTWVtPRScYCV/n5VcDRVdIfC/zRzN7pTKHhmIIgCBqOGofxOv8eajMzmw/gfzetkn4ccE1J2PmSpkv6oaS+tRQakx+CIAgaDWNNnM4wSVNy15PMbFJ2IekuYPMy+c5ekypJ2gIYCdyRCz4LeAXoA0wCvgGcV81WOKYgCIJGpPZRutfNbFSlSDM7rFKcpFclbWFm893xLOignOOAm8xsZc72fD9dIekK4IxaKhxDeUEQBA2IzGo6Oslk4GQ/Pxn4fQdpx1MyjOfODEkivZ96vJZCwzEFQRA0Il3zjukC4HBJs4HD/RpJoyRdliWSNBzYBvhzSf6rJc0AZgDDgO/WUmgM5QVBEDQaZtC67vckMrM3gEPLhE8BTs1dzwW2KpPukLUpNxxTEARBI9LEOz+EYwqCIGhEwjEFQRAEdYMBbeGYgiAIgrrBwJpX9yIcU7AKG/RdziHbz+60nacv3bWA2oAVNG/UehU3AbWlX+9C7Ay5tU8hdhaPW1KIna/sfG8hdq647eOF2HnlwOJ6BEUpz87Y/zeF2OnZWQNGl0x+6C7CMQVBEDQi8Y4pCIIgqCvCMQVBEAT1QyGLZ+uWcExBEASNhgGdl7SoW8IxBUEQNCLRYwqCIAjqh67Zkqi7CMcUBEHQaBhYrGMKgiAI6orY+SEIgiCoK+IdUxAEQVA3mMWsvCAIgqDOiB5TEARBUD8Y1tra3ZVYZ4RjCoIgaDRC9iIIgiCoO5p4unhxWgBBEARBl2CAtVlNR2eQ9ClJMyW1SRrVQboxkp6WNEfSxFz49pIeljRb0nWSatJ6CccUBEHQaJgLBdZydI7HgU8A91dKIKkncDFwFLALMF7SLh79PeCHZjYCWAScUkuh4ZiCIAgaEGttrenoVBlmT5rZ01WS7QfMMbNnzexd4FpgrCQBhwA3eLqrgKNrKVfWxFMOgzVH0mvA81WSDQNeL6C4ouwUaSvsNJadRmU7M9tkbTNLup30DGuhH7A8dz3JzCatYXn3AWeY2ZQycccCY8zsVL8+EdgfOBd4yMze5+HbAH80s92qlReTH4JVqOU/i6QpZlZxvLlWirJTj3UKO11jZ33FzMYUZUvSXcDmZaLONrPf12KiTJh1EF6VcExBEATrMWZ2WCdNzAO2yV1vDbxM6hEPltTLzFpy4VWJd0xBEARBZ3gEGOEz8PoA44DJlt4T3Qsc6+lOBmrpgYVjCtaKNRqf7gI7RdoKO41lJ1iHSDpG0jzgA8Ctku7w8C0l3QbgvaHTgDuAJ4HrzWymm/gGcLqkOcDGwC9rKjcmPwRBEAT1RPSYgiAIgroiHFMQBEFQV4RjCoIgCOqKcExBEARBXRGOKQiCIKgrwjEFQRAEdUU4piAIgqCu+P+fH1lbK032CgAAAABJRU5ErkJggg==\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"# Scatter Plot Matrix\n\nA scatter plot shows the relationship between two variables as dots in two dimensions, one axis for each attribute. You can create a scatter plot for each pair of attributes in your data. Drawing all these scatter plots together is called a scatter plot matrix. Scatter plots are useful for spotting structured relationships between variables, like whether you could summarize the relationship between two variables with a line. Attributes with structured relationships may also be correlated and good candidates for removal from your dataset."},{"metadata":{"trusted":true},"cell_type":"code","source":"#you can use vars to compare two variable and hue to put colours\nsns.pairplot(Train,hue='CLASS',vars=['FULL_Charge','FULL_AcidicMolPerc'])\n#check on the seaborn(seaborn.pydata.org-dev/generated/seaborn.boxplot.html)","execution_count":57,"outputs":[{"output_type":"execute_result","execution_count":57,"data":{"text/plain":""},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{"needs_background":"light"}}]},{"metadata":{},"cell_type":"markdown","source":"```mo = pd.DataFrame(out_model)\nmo.to_csv(\"xyz.csv\")\n```"},{"metadata":{},"cell_type":"markdown","source":"# Prepare Your Data For Machine Learning\nMany machine learning algorithms make assumptions about your data. It is often a very good idea to prepare your data in such way to best expose the structure of the problem to the machine learning algorithms that you intend to use. In this chapter you will discover how to prepare your data for machine learning in Python using scikit-learn. After completing this lesson you will know how to:\n\n1. Rescale data.\n2. Standardize data.\n3. Normalize data.\n4. Binarize data.\n### Need For Data Pre-processing\nYou almost always need to pre-process your data. It is a required step. A difficulty is that different algorithms make different assumptions about your data and may require different transforms. Further, when you follow all of the rules and prepare your data, sometimes algorithms can deliver better results without pre-processing. Generally, I would recommend creating many different views and transforms of your data, then exercise a handful of algorithms on each view of your dataset. This will help you to ush out which data transforms might be better at exposing the structure of your problem in general.\n\n### The steps involved are as below:\n\nSplit the dataset into the input and output variables for machine learning.\nApply a pre-processing transform to the input variables.\nSummarize the data to show the change.\nThe scikit-learn library provides two standard idioms for transforming data. Each are useful in di\u000berent circumstances. The transforms are calculated in such a way that they can be applied to your training data and any samples of data you may have in the future. The scikit-learn documentation has some information on how to use various di\u000berent pre-processing methods:\n\nThe Fit and Multiple Transform method is the preferred approach. You call the fit() function to prepare the parameters of the transform once on your data. Then later you can use the transform() function on the same data to prepare it for modeling and again on the test or validation dataset or new data that you may see in the future. The Combined Fit-And-Transform is a convenience that you can use for one o\u000b tasks. This might be useful if you are interested in plotting or summarizing the transformed data.\n\n### Rescale Data\nWhen your data is comprised of attributes with varying scales, many machine learning algorithms can bene\ft from rescaling the attributes to all have the same scale. Often this is referred to as normalization and attributes are often rescaled into the range between 0 and 1. This is useful for optimization algorithms used in the core of machine learning algorithms like gradient descent. It is also useful for algorithms that weight inputs like regression and neural networks and algorithms that use distance measures like k-Nearest Neighbors. You can rescale your data using scikit-learn using the MinMaxScaler class\n\n### NOTE: Since my graph and summary data shows varying means and Gaussian distribution. i would use Standardize data method\n\n\n\n### Standardize of Data\nStandardization is a useful technique to transform attributes with a Gaussian distribution and differing means and standard deviations to a standard Gaussian distribution with a mean of 0 and a standard deviation of 1. It is most suitable for techniques that assume a Gaussian distribution in the input variables and work better with rescaled data, such as linear regression, logistic regression and linear discriminate analysis. You can standardize data using scikit-learn with the StandardScaler class3."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.preprocessing import StandardScaler\n\narray2 = Train.values\n# separate array into input and output components\nX = array2[:,0:11]\nY = array2[:,11]\nscaler = StandardScaler().fit(X)\nrescaledX = scaler.transform(X)\n# summarize transformed data\n#set_printoptions(precision=3)\nprint(rescaledX[0:5,:])","execution_count":58,"outputs":[{"output_type":"stream","text":"[[ 7.69712416e-01 -1.12341031e+00 -1.90047029e-01 1.37605977e-01\n -6.06718766e-01 -7.20629784e-01 -3.11684110e-01 -1.33070267e+00\n -2.25681314e-02 -3.60971652e-01 -9.25122883e-01]\n [ 5.07884366e-01 -4.10857567e-01 -3.76275096e-01 -2.43225309e-01\n -1.18128598e+00 -9.24503172e-01 3.20837658e+00 -1.30322672e+00\n -5.92370366e-01 9.02050407e-01 1.03699430e+00]\n [ 9.00626442e-01 -4.10857567e-01 -9.16336490e-01 -8.65106417e-03\n -1.05360437e+00 -4.63244125e-02 -3.11684110e-01 -1.30383154e+00\n -4.59030969e-01 -1.40916462e+00 2.31808537e+00]\n [ 7.69712416e-01 -5.74065761e-01 -7.11485617e-01 -8.70124978e-01\n 1.59370848e-01 6.27395116e-01 -3.11684110e-01 -1.30201709e+00\n -7.01486075e-01 -2.30020073e+00 6.98862456e-01]\n [ 1.42428254e+00 2.04070778e-03 -3.66963693e-01 -1.04957427e+00\n -4.79037163e-01 2.00315519e-01 -3.11684110e-01 -1.30184429e+00\n -7.71259861e-02 -1.97723618e+00 1.44656245e+00]]\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"# Feature Selection For Machine\nLearning The data features that you use to train your machine learning models have a huge in uence on the performance you can achieve. Irrelevant or partially relevant features can negatively impact model performance. In this chapter you will discover automatic feature selection techniques that you can use to prepare your machine learning data in Python with scikit-learn. After completing this lesson you will know how to use:\n\n## Univariate Selection.\nRecursive Feature Elimination.\nPrinciple Component Analysis.\nFeature Importance.\nFeature Selection\nFeature selection is a process where you automatically select those features in your data that contribute most to the prediction variable or output in which you are interested. Having irrelevant features in your data can decrease the accuracy of many models, especially linear algorithms like linear and logistic regression. Three benets of performing feature selection before modeling your data are:\n\nReduces Overffitting: Less redundant data means less opportunity to make decisions based on noise.\nImproves Accuracy: Less misleading data means modeling accuracy improves.\nReduces Training Time: Less data means that algorithms train faster.\nUnivariate Selection\nStatistical tests can be used to select those features that have the strongest relationship with the output variable. The scikit-learn library provides the SelectKBest class2 that can be used with a suite of different statistical tests to select a specific number of features. The example below uses the chi-squared (𝑐ℎ𝑖2) statistical test for non-negative features to select 4 of the best features from the Pima Indians onset of diabetes dataset.\n\nYou can see the scores for each attribute and the 4 attributes chosen (those with the highest scores): plas, test, mass and age. I got the names for the chosen attributes by manually mapping the index of the 4 highest scores to the index of the attribute names.\n\n# Recursive Feature Elimination method.\nThe Recursive Feature Elimination (or RFE) works by recursively removing attributes and building a model on those attributes that remain. It uses the model accuracy to identify which attributes (and combination of attributes) contribute the most to predicting the target attribute. You can learn more about the RFE class3 in the scikit-learn documentation. The example below uses RFE with the logistic regression algorithm to select the top 3 features. The choice of algorithm does not matter too much as long as it is skillful and consistent.\n\n### NOTE: Since i dont have much information about the interpretetion of my varaibles, Recursive Feature Elimination method would be the best. "},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.feature_selection import RFE\nfrom sklearn.linear_model import LogisticRegression\n\narray_1 = Train.values\nX = array_1[:,0:11]\nY = array_1[:,11]\n# feature extraction\nmodel = LogisticRegression()\nrfe = RFE(model, 10)\nfit = rfe.fit(X, Y)\nprint(\"Num Features: \", fit.n_features_)\nprint(\"Selected Features:\", fit.support_)\nprint(\"Feature Ranking: \", fit.ranking_)","execution_count":59,"outputs":[{"output_type":"stream","text":"Num Features: 10\nSelected Features: [ True True True True True True True True False True True]\nFeature Ranking: [1 1 1 1 1 1 1 1 2 1 1]\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"# Evaluate the Performance of Machine Learning Algorithms with Resampling\nYou need to know how well your algorithms perform on unseen data. The best way to evaluate the performance of an algorithm would be to make predictions for new data to which you already know the answers. The second best way is to use clever techniques from statistics called resampling methods that allow you to make accurate estimates for how well your algorithm will perform on new data. In this chapter you will discover how you can estimate the accuracy of your machine learning algorithms using resampling methods in Python and scikit-learn on the Pima Indians dataset. Let's get started.\n\n## Evaluate Machine Learning Algorithms\nWhy can't you train your machine learning algorithm on your dataset and use predictions from this same dataset to evaluate machine learning algorithms? The simple answer is overffitting. Imagine an algorithm that remembers every observation it is shown during training. If you evaluated your machine learning algorithm on the same dataset used to train the algorithm, then an algorithm like this would have a perfect score on the training dataset. But the predictions it made on new data would be terrible. We must evaluate our machine learning algorithms on data that is not used to train the algorithm. The evaluation is an estimate that we can use to talk about how well we think the algorithm may actually do in practice. It is not a guarantee of performance. Once we estimate the performance of our algorithm, we can then re-train the final algorithm on the entire training dataset and get it ready for operational use. Next up we are going to look at four different techniques that we can use to split up our training dataset and create useful estimates of performance for our machine learning algorithms:\n\n* Train and Test Sets.\n* k-fold Cross Validation.\n* Leave One Out Cross Validation.\n* Repeated Random Test-Train Splits.\n\n## Split into Train and Test Sets\nThe simplest method that we can use to evaluate the performance of a machine learning algorithm is to use different training and testing datasets. We can take our original dataset and split it into two parts. Train the algorithm on the train part, make predictions on the second part and evaluate the predictions against the expected results. The size of the split can depend on the size and species of your dataset, although it is common to use 67% of the data for training and the remaining 33% for testing. This algorithm evaluation technique is very fast. It is ideal for large datasets (millions of records) where there is strong evidence that both splits of the data are representative of the underlying problem. Because of the speed, it is useful to use this approach when the algorithm you are investigating is slow to train. A downside of this technique is that it can have a high variance. This means that di\u000berences in the training and test dataset can result in meaningful diferences in the estimate of accuracy. In the example below we split the Pima Indians dataset into 70%/30% splits for training and test and evaluate the accuracy of a Logistic Regression model."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import train_test_split\nfrom sklearn.linear_model import LogisticRegression\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\ntest_size = 0.30\nseed = 7\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\nrandom_state=seed)\nmodel = LogisticRegression()\nmodel.fit(X_train, Y_train)\nresult = model.score(X_test, Y_test)\nprint(\"Accuracy: \", (result*100.0))","execution_count":60,"outputs":[{"output_type":"stream","text":"Accuracy: 91.55701754385966\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"# K-fold Cross Validation\nCross validation is an approach that you can use to estimate the performance of a machine learning algorithm with less variance than a single train-test set split. It works by splitting the dataset into k-parts (e.g. k = 5 or k = 10). Each split of the data is called a fold. The algorithm is trained on k 1 folds with one held back and tested on the held back fold. This is repeated so that each fold of the dataset is given a chance to be the held back test set. After running cross validation you end up with k diferent performance scores that you can summarize using a mean and a standard deviation. The result is a more reliable estimate of the performance of the algorithm on new data. It is more accurate because the algorithm is trained and evaluated multiple times on different data. The choice of k must allow the size of each test partition to be large enough to be a reasonable sample of the problem, whilst allowing enough repetitions of the train-test evaluation of the algorithm to provide a fair estimate of the algorithms performance on unseen data. For modest sized datasets in the thousands or tens of thousands of records, k values of 3, 5 and 10 are common."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import KFold\nfrom sklearn.model_selection import cross_val_score\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n\nnum_folds = 10 #number of folds to use are 10\nseed = 7 #reproducibility\n\nkfold = KFold(n_splits=num_folds, random_state=seed)\nmodel = LogisticRegression()\nresults = cross_val_score(model, X, Y, cv=kfold)\n\nprint(f\"Accuracy:\", (results.mean()*100.0, results.std()*100.0))","execution_count":61,"outputs":[{"output_type":"stream","text":"Accuracy: (83.5359128018065, 27.08521320979506)\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"# Leave One Out Cross Validation\nYou can configure cross validation so that the size of the fold is 1 (k is set to the number of observations in your dataset). This variation of cross validation is called leave-one-out cross validation. The result is a large number of performance measures that can be summarized in an effort to give a more reasonable estimate of the accuracy of your model on unseen data. A downside is that it can be a computationally more expensive procedure than k-fold cross validation. In the example below we use leave-one-out cross validation."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import LeaveOneOut\nfrom sklearn.model_selection import cross_val_score\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\nnum_folds = 10\nloocv = LeaveOneOut()\nmodel = LogisticRegression()\nresults = cross_val_score(model, X, Y, cv=loocv)\nprint(\"Accuracy:\", (results.mean()*100.0, results.std()*100.0))","execution_count":62,"outputs":[{"output_type":"stream","text":"Accuracy: (91.4417379855168, 27.974673416141517)\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"# Repeated Random Test-Train Splits\nAnother variation on k-fold cross validation is to create a random split of the data like the train/test split described above, but repeat the process of splitting and evaluation of the algorithm multiple times, like cross validation. This has the speed of using a train/test split and the reduction in variance in the estimated performance of k-fold cross validation. You can also repeat the process many more times as needed to improve the accuracy. A down side is that repetitions may include much of the same data in the train or the test split from run to run, introducing redundancy into the evaluation. The example below splits the data into a 70%/30% train/test split and repeats the process 10 times."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import ShuffleSplit\nfrom sklearn.model_selection import cross_val_score\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\nn_splits = 10\ntest_size = 0.30\nseed = 7\nkfold = ShuffleSplit(n_splits=n_splits, test_size=test_size, random_state=seed)\nmodel = LogisticRegression()\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(\"Accuracy: \" , (results.mean()*100.0, results.std()*100.0))","execution_count":63,"outputs":[{"output_type":"stream","text":"Accuracy: (91.30482456140349, 0.5803122202806698)\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"# NOTE: What Techniques to Use When\nThis section lists some tips to consider what resampling technique to use in diferent circum- stances.\n\nGenerally k-fold cross validation is the gold standard for evaluating the performance of amachine learning algorithm on unseen data with k set to 3, 5, or 10.\nUsing a train/test split is good for speed when using a slow algorithm and producesperformance estimates with lower bias when using large datasets.\nTechniques like leave-one-out cross validation and repeated random splits can be usefulintermediates when trying to balance variance in the estimated performance, modeltraining speed and dataset size.\nThe best advice is to experiment and find a technique for your problem that is fast and produces reasonable estimates of performance that you can use to make decisions. If in doubt, use 10-fold cross validation.\n# Machine Learning Algorithm Performance Metrics\n\nThe metrics that you choose to evaluate your machine learning algorithms are very important.\nChoice of metrics in\nuences how the performance of machine learning algorithms is measured\nand compared. They in\nuence how you weight the importance of different characteristics in\nthe results and your ultimate choice of which algorithm to choose.\n\n## Algorithm Evaluation Metrics\nIn this lesson, various different algorithm evaluation metrics are demonstrated for both classification and regression type machine learning problems. In each recipe, the dataset is downloaded\ndirectly from the Machine Learning repository.\n\n## Classiffication Metrics\nClassiffication problems are perhaps the most common type of machine learning problem and as such there are a myriad of metrics that can be used to evaluate predictions for these problems. In this section we will review how to use the following metrics:\n\n* Classiffication Accuracy.\n* Logarithmic Loss.\n* Area Under ROC Curve.\n* Confusion Matrix.\n* Classiffication Report.\n\n## Classiffication Accuracy\nClassiffication accuracy is the number of correct predictions made as a ratio of all predictions made. This is the most common evaluation metric for classi\fcation problems, it is also the most misused. It is really only suitable when there are an equal number of observations in each class (which is rarely the case) and that all predictions and prediction errors are equally important, which is often not the case. Below is an example of calculating classiffication accuracy."},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\nkfold = KFold(n_splits=10, random_state=7)\nmodel = LogisticRegression()\nscoring = 'accuracy'\nresults = cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\nprint(\"Accuracy:\", (results.mean(), results.std()))","execution_count":64,"outputs":[{"output_type":"stream","text":"Accuracy: (0.835359128018065, 0.2708521320979506)\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"## Logarithmic Loss\nLogarithmic loss (or logloss) is a performance metric for evaluating the predictions of probabilities of membership to a given class. The scalar probability between 0 and 1 can be seen as a measure of confidence for a prediction by an algorithm. Predictions that are correct or incorrect are rewarded or punished proportionally to the confidence of the prediction."},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\nkfold = KFold(n_splits=10, random_state=7)\nmodel = LogisticRegression()\nscoring = 'neg_log_loss'\nresults = -cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\nprint(\"Logloss:\", (results.mean(), results.std()))","execution_count":65,"outputs":[{"output_type":"error","ename":"ValueError","evalue":"y_true contains only one label (1.0). Please provide the true labels explicitly through the labels argument.","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)","\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mmodel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mLogisticRegression\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0mscoring\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'neg_log_loss'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0mcross_val_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m,\u001b[0m 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753\u001b[0m \u001b[0mjob_idx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_jobs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 754\u001b[0;31m \u001b[0mjob\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_backend\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply_async\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbatch\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcallback\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 755\u001b[0m \u001b[0;31m# A job can complete so quickly than its callback is\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 756\u001b[0m \u001b[0;31m# called before we get here, causing self._jobs 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**self._kwargs)\n\u001b[1;32m 259\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 260\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sign\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_score_func\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_pred\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_kwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 261\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 262\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_factory_args\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/opt/conda/lib/python3.6/site-packages/sklearn/metrics/_classification.py\u001b[0m in \u001b[0;36mlog_loss\u001b[0;34m(y_true, y_pred, eps, normalize, sample_weight, labels)\u001b[0m\n\u001b[1;32m 2253\u001b[0m raise ValueError('y_true contains only one label ({0}). Please '\n\u001b[1;32m 2254\u001b[0m \u001b[0;34m'provide the true labels explicitly through the '\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2255\u001b[0;31m 'labels argument.'.format(lb.classes_[0]))\n\u001b[0m\u001b[1;32m 2256\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2257\u001b[0m raise ValueError('The labels array needs to contain at least two '\n","\u001b[0;31mValueError\u001b[0m: y_true contains only one label (1.0). Please provide the true labels explicitly through the labels argument."]}]},{"metadata":{},"cell_type":"markdown","source":"# Area Under ROC Curve\nArea under ROC Curve (or AUC for short) is a performance metric for binary classiffication problems. The AUC represents a model's ability to discriminate between positive and negative classes. An area of 1.0 represents a model that made all predictions perfectly. An area of 0.5 represents a model that is as good as random. ROC can be broken down into sensitivity and specificity. A binary classiffication problem is really a trade-off between sensitivity and specificity.\n\n* Sensitivity is the true positive rate also called the recall. It is the number of instances from the positive (first) class that actually predicted correctly.\n\n* Specificity is also called the true negative rate. Is the number of instances from the negative (second) class that were actually predicted correctly."},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\nkfold = KFold(n_splits=10, random_state=7)\nmodel = LogisticRegression()\nscoring = 'roc_auc'\nresults = cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\nprint(\"AUC:\", (results.mean(), results.std()))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Confusion Matrix\nThe confusion matrix is a handy presentation of the accuracy of a model with two or more classes. The table presents predictions on the x-axis and accuracy outcomes on the y-axis. The cells of the table are the number of predictions made by a machine learning algorithm. For example, a machine learning algorithm can predict 0 or 1 and each prediction may actually have been a 0 or 1. Predictions for 0 that were actually 0 appear in the cell for prediction = 0 and actual = 0, whereas predictions for 0 that were actually 1 appear in the cell for prediction = 0 and actual = 1. And so on."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.metrics import confusion_matrix\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\ntest_size = 0.30\nseed = 7\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\nrandom_state=seed)\n\nmodel = LogisticRegression()\nmodel.fit(X_train, Y_train)\n\npredicted = model.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nprint(matrix)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Classiffication Report\nThe scikit-learn library provides a convenience report when working on classiffication problems to give you a quick idea of the accuracy of a model using a number of measures. The classification report() function displays the precision, recall, F1-score and support for each class. "},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.metrics import classification_report\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\ntest_size = 0.30\nseed = 7\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\nrandom_state=seed)\nmodel = LogisticRegression()\nmodel.fit(X_train, Y_train)\npredicted = model.predict(X_test)\nreport = classification_report(Y_test, predicted)\nprint(report)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Spot-Check Classiffication Algorithms.\nSpot-checking is a way of discovering which algorithms perform well on your machine learning problem. You cannot know which algorithms are best suited to your problem beforehand. You must trial a number of methods and focus attention on those that prove themselves the most promising.\n\n1. How to spot-check machine learning algorithms on a classi\fcation problem.\n2. How to spot-check two linear classification algorithms.\n3. How to spot-check four nonlinear classification algorithms.\n\nAlgorithm Spot-Checking\nYou cannot know which algorithm will work best on your dataset beforehand. You must use trial and error to discover a shortlist of algorithms that do well on your problem that you can then double down on and tune further. I call this process spot-checking. The question is not: What algorithm should I use on my dataset? Instead it is: What algorithms should I spot-check on my dataset? You can guess at what algorithms might do well on your dataset, and this can be a good starting point. I recommend trying a mixture of algorithms and see what is good at picking out the structure in your data. Below are some suggestions when spot-checking algorithms on your dataset:\n\nTry a mixture of algorithm representations (e.g. instances and trees).\n\nTry a mixture of learning algorithms (e.g. di\u000berent algorithms for learning the same type of representation).\n\nTry a mixture of modeling types (e.g. linear and nonlinear functions or parametric and nonparametric).\n\nAlgorithms Overview\nWe are going to take a look at six classi\fcation algorithms that you can spot-check on your dataset. Starting with two linear machine learning algorithms:\n\nLogistic Regression.\nLinear Discriminant Analysis.\nThen looking at four nonlinear machine learning algorithms:\n\nk-Nearest Neighbors.\nNaive Bayes.\nClassi\fcation and Regression Trees.\nSupport Vector Machines.\nLinear Machine Learning Algorithms\nThis section demonstrates minimal recipes for how to use two linear machine learning algorithms: logistic regression and linear discriminant analysis.\n\nLogistic Regression\nLogistic regression assumes a Gaussian distribution for the numeric input variables and can model binary classiffication problems. You can construct a logistic regression model using the LogisticRegression class."},{"metadata":{"trusted":true},"cell_type":"code","source":"# Logistic Regression Classification\nfrom pandas import read_csv\nfrom sklearn.model_selection import KFold\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.linear_model import LogisticRegression\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\nnum_folds = 10\nkfold = KFold(n_splits=10, random_state=7)\nmodel = LogisticRegression()\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Linear Discriminant Analysis\nLinear Discriminant Analysis or LDA is a statistical technique for binary and multiclass classiffication. It too assumes a Gaussian distribution for the numerical input variables. You can construct an LDA model using the LinearDiscriminantAnalysis class"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\nnum_folds = 10\nkfold = KFold(n_splits=10, random_state=7)\nmodel = LinearDiscriminantAnalysis()\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Nonlinear Machine Learning Algorithms\nThis section demonstrates minimal recipes for how to use 4 nonlinear machine learning algorithms.\n\n## k-Nearest Neighbors\nThe k-Nearest Neighbors algorithm (or KNN) uses a distance metric to find the k most similar instances in the training data for a new instance and takes the mean outcome of the neighbors as the prediction. You can construct a KNN model using the KNeighborsClassifier class."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.neighbors import KNeighborsClassifier\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\nnum_folds = 10\nkfold = KFold(n_splits=10, random_state=7)\nmodel = KNeighborsClassifier()\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Naive Bayes\nNaive Bayes calculates the probability of each class and the conditional probability of each class given each input value. These probabilities are estimated for new data and multiplied together, assuming that they are all independent (a simple or naive assumption). When working with real-valued data, a Gaussian distribution is assumed to easily estimate the probabilities for input variables using the Gaussian Probability Density Function. You can construct a Naive Bayes model using the GaussianNB class4."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.naive_bayes import GaussianNB\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\nkfold = KFold(n_splits=10, random_state=7)\nmodel = GaussianNB()\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Classiffication and Regression Trees\nClassiffication and Regression Trees (CART or just decision trees) construct a binary tree from the training data. Split points are chosen greedily by evaluating each attribute and each value of each attribute in the training data in order to minimize a cost function (like the Gini index). You can construct a CART model using the DecisionTreeClassifier class"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.tree import DecisionTreeClassifier\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\nkfold = KFold(n_splits=10, random_state=7)\nmodel = DecisionTreeClassifier()\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Support Vector Machines\nSupport Vector Machines (or SVM) seek a line that best separates two classes. Those data instances that are closest to the line that best separates the classes are called support vectors and in uence where the line is placed. SVM has been extended to support multiple classes. Of particular importance is the use of di\u000berent kernel functions via the kernel parameter."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.svm import SVC\nfrom sklearn.metrics import matthews_corrcoef\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\nkfold = KFold(n_splits=10)\nmodel = SVC()\nscoring = 'acuracy'\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())\n\ntest_set = Test.values\nmodel.fit(X, Y)\noutput = model.predict(test_set)\n\nmcc = matthews_corrcoef(model.predict(X), Y)\nprint('MCC: ',mcc)\n\nfinalreport1 = pd.DataFrame(output)\nfinalreport1.columns = ['CLASS']\nfinalreport1.index.name = 'Index'\nfinalreport1['CLASS'] = finalreport1['CLASS'].map({0.0:False, 1.0:True})\n\nfinalreport1.to_csv('finalreport1_sv.csv')\n\nprint(finalreport1['CLASS'].unique())\nprint('False: ',finalreport1.groupby('CLASS').size()[0].sum())\nprint('True: ',finalreport1.groupby('CLASS').size()[1].sum())","execution_count":69,"outputs":[{"output_type":"stream","text":"0.8350280093798853\nMCC: 0.8187103751493263\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"# Spot-Check Regression Algorithms\n* Linear Regression.\n* Ridge Regression.\n* LASSO Linear Regression.\n* Elastic Net Regression.\n\n## Then looking at three nonlinear machine learning algorithms:\n\n* k-Nearest Neighbors.\n* Classification and Regression Trees.\n* Support Vector Machines.\n* Linear Regression\n\nLinear regression assumes that the input variables have a Gaussian distribution. It is also assumed that input variables are relevant to the output variable and that they are not highly correlated with each other (a problem called collinearity). You can construct a linear regression model using the LinearRegression class."},{"metadata":{"trusted":true},"cell_type":"code","source":"import pandas as pd\ndf = pd.DataFrame([0]*16)\ndf.to_csv('results.csv', index=False, header=False)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"raw","source":""}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4} \ No newline at end of file From 69f89a73465ef884bf06fbd29470177bc17e2585 Mon Sep 17 00:00:00 2001 From: Jupiter Marina Date: Thu, 12 Mar 2020 20:20:34 +0300 Subject: [PATCH 18/29] Made more predictions from more algorithms --- Assignment Colab/Jupiter Marina.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/Assignment Colab/Jupiter Marina.ipynb b/Assignment Colab/Jupiter Marina.ipynb index 2f0b44b..2a34063 100644 --- a/Assignment Colab/Jupiter Marina.ipynb +++ b/Assignment Colab/Jupiter Marina.ipynb @@ -1 +1 @@ -{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\nimport matplotlib as plot\nimport seaborn as sns\nimport sklearn\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n for filename in filenames:\n print(os.path.join(dirname, filename))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Importing data"},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"# Importing data\ntest_data = pd.read_csv(\"/kaggle/input/ace-class-assignment/Test.csv\", header=0, sep=\",\")\namp_train = pd.read_csv(\"/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\", header=0, sep=\",\")\nprint(amp_train)\n#print(test)\n\n\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"amp_train.columns","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#test_amp =amp_train[['FULL_Charge', 'FULL_AcidicMolPerc','FULL_OOBM850104','FULL_DAYM780201', 'AS_MeanAmphiMoment','CLASS']]\n#print(test_amp)\n#test_data=test_data[['FULL_Charge', 'FULL_AcidicMolPerc','FULL_OOBM850104','FULL_DAYM780201', 'AS_MeanAmphiMoment']]\n#X=test_amp.drop(\"CLASS\",axis=1)\n#Y=test_amp.CLASS\n#model=GaussianNB() \n#model.fit(X,Y)\n#kj_results=model.predict(test_data)\n\n#print(test_data2)\n#kj_results","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## General data attributes and descriptive statistics"},{"metadata":{"trusted":true},"cell_type":"code","source":"#Describing general data attributes\ntrain_dim=amp_train.shape #gets the dimensions of the tranining dataset\ntest_dim= test_data.shape #gets the dimensions of the tesing dataset\nprint(train_dim)\nprint(test_dim)\n\natr_types=amp_train.dtypes #gets the data type for each column in training dataset\nprint(atr_types)\namp_train.isnull().sum() # gets the sum of the missing values/observations in each column\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Descriptive statistics \nstats=amp_train.describe()\nprint(stats)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Class distributions\n\nSometimes, observations from the different classes may not be equal, these may need special handling, so its important to note the class distributions, as if they are uneven, they may bias our model"},{"metadata":{"trusted":true},"cell_type":"code","source":"# CLass distibutions \ncdists= amp_train.groupby('CLASS').size() # groups the observation by the column of class, and counts all the observations including null values\nprint(cdists)\n\n#plots to visualize the class distribution\namp_train.groupby('CLASS').size().plot(kind=\"pie\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"The observations from each class seem to be equal"},{"metadata":{},"cell_type":"markdown","source":"# Correlation between the different attributes\nBasically, we need to examine our attributes for correlation as highly correlated attributes present the same data to the algorithm. Removing one may speed learning of the algorithm (less dimensions more speed)"},{"metadata":{"trusted":true},"cell_type":"code","source":"# Correlation between attributes \ncorrelations = amp_train.corr(method=\"pearson\") # calculates pairwaise correlation for the attributes \nprint(correlations)\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"FULL_AURR980107 and FULL_AcidicMolPerc have a correlation coefficent of 0.79, this might mean these two attributes may be some what correlated. Same goes for AS_DAYM780201 and FULL_DAYM780201 (correlation coefficient is 0.894191)"},{"metadata":{"trusted":true},"cell_type":"code","source":"# Plots to visualize the correlations\nfrom matplotlib import rcParams\nsns.heatmap(correlations, annot=True)\nrcParams['figure.figsize'] = 11.7,8.27\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Data skewness\n\nMost machine learning algorithms assume that data from the attributes is normally distributed, so identifying attributes with data that has a left or right skew, can be important as this can be easily corrected"},{"metadata":{"trusted":true},"cell_type":"code","source":"sk = amp_train.skew() # calculates the skew for each attribute\nprint(sk)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Negative values like those of FULL_DAYM780201, FULL_OOBM850104,AS_DAYM780201, AS_FUKS010112, indicate that these attributes have values skewed more to the left\nValues closer to zero are indicative of a less or no skew, while positive values would mean that that particular attribute is skewed more to the right"},{"metadata":{},"cell_type":"markdown","source":" # Visualising data distributions with plots"},{"metadata":{"trusted":true},"cell_type":"code","source":"# Plot one, histogram to show the distributions\nimport matplotlib as plot \nfrom matplotlib import pyplot\namp_train.hist(layout=(4,3), figsize=(16,16))\nplot.pyplot.subplots_adjust(wspace=0.4, hspace=0.5)\npyplot.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Plot two density plots can show the distributions better\namp_train.plot(kind=\"density\",subplots=True,layout=(4,3),sharex=False,sharey=False, figsize=(16,16))\n#amp_train.plot(kind=\"density\",subplots=False,layout=(4,3),sharex=True,sharey=True)\npyplot.show()\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Data transformations\nUsing square roots to transform the attributes with negative values into postives"},{"metadata":{"trusted":true},"cell_type":"code","source":"\nneg1=amp_train.iloc[:,0]\nprint(neg1)\ntneg1=neg1**2\ntneg1.plot(kind=\"density\")\namp_train.iloc[:,0]=tneg1\n\n\n\nneg2=amp_train.iloc[:,5]\nprint(neg2)\ntneg2=neg2**2\ntneg2.plot(kind=\"density\")\namp_train.iloc[:,5]=tneg2\n\n## test\nneg3=test_data.iloc[:,0]\nprint(neg3)\ntneg3=neg3**2\ntneg3.plot(kind=\"density\")\ntest_data.iloc[:,0]=tneg3\n\n\n\nneg4=test_data.iloc[:,5]\nprint(neg4)\ntneg4=neg4**2\ntneg4.plot(kind=\"density\")\ntest_data.iloc[:,5]=tneg4","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"distributions for AS_MeanAmphiMoment,FULL_AcidicMolPerc and NT_EFC195 dont look so good"},{"metadata":{},"cell_type":"markdown","source":"# Feature selection\n\n\n"},{"metadata":{"trusted":true},"cell_type":"code","source":" #test one selecting out features with low variance\nfrom sklearn.feature_selection import VarianceThreshold\nsel = VarianceThreshold(threshold=(.8 * (1 - .8)))\nk=sel.fit_transform(amp_train)\nnames=amp_train.columns[sel.get_support(indices=True)]\nprint(k.shape)\namp_train2=pd.DataFrame(k,columns=names)\nprint(amp_train2)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#test two\nfrom sklearn.feature_selection import SelectKBest\nfrom sklearn.feature_selection import chi2\n\ntest_array = amp_train2.values\n\ntest_atr = test_array[:,0:7]\nclass_atr = test_array[:,7]\n\n\ntest = SelectKBest(score_func=chi2, k=5)\nfit = test.fit(test_atr, class_atr)\n\n\nprint(fit.scores_)\nfeatures = fit.transform(test_atr)\nnames2=amp_train2.columns[fit.get_support(indices=True)]\namp_train3=pd.DataFrame(features,columns=names2)\nprint(amp_train3[5:])\n\n\n\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Test three Recursive feature elimination\n\nfrom sklearn.feature_selection import RFE\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.ensemble import RandomForestClassifier\n\nmodel1 = LogisticRegression()\nmodel2=RandomForestClassifier()\n\nrfe = RFE(model1, 4)\nfit2 = rfe.fit(test_atr, class_atr)\n\nrfe2= RFE(model2, 4)\nfit3 = rfe2.fit(test_atr, class_atr)\n\n\n\n\nnames3=amp_train2.columns[fit2.get_support(indices=True)]\n\nnames4=amp_train2.columns[fit3.get_support(indices=True)]\n\nprint(names3)\nprint(names4)\nprint(names2)\nprint(amp_train.columns)\nprint(amp_train2)\n\n\n\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"test_amp =amp_train.loc[:,['FULL_Charge', 'FULL_AcidicMolPerc',\"FULL_OOBM850104\",'FULL_DAYM780201', 'AS_MeanAmphiMoment','CLASS']]\nprint(test_amp)\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import train_test_split\nfrom sklearn.model_selection import KFold\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.metrics import confusion_matrix\n\n\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.svm import SVC\nfrom sklearn.neighbors import KNeighborsClassifier\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Logistic regression using cross validation"},{"metadata":{"trusted":true},"cell_type":"code","source":"\nX=test_amp.iloc[:,0:5]\nY=test_amp.iloc[:,5]\nfolds=10\nkfold = KFold(n_splits=folds, random_state=7, shuffle=True,)\nmodel = LogisticRegression()\nresults = cross_val_score(model, X, Y, cv=kfold)\n\nprint((\"Accuracy: %.3f%% (%.3f%%)\") % (results.mean()*100.0, results.std()*100.0))\n\n\n\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"test_data = pd.read_csv(\"/kaggle/input/ace-class-assignment/Test.csv\", header=0, sep=\",\")\namp_train = pd.read_csv(\"/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\", header=0, sep=\",\")\ntest_amp =amp_train.loc[:,['FULL_Charge', 'FULL_AcidicMolPerc',\"FULL_OOBM850104\",'FULL_DAYM780201', 'AS_MeanAmphiMoment','CLASS']]","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Logistic regression with a test train split"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.metrics import matthews_corrcoef\ntest_amp=test_amp.values\n#X=test_amp.iloc[:,0:5]\nX=test_amp[:,0:5]\nY=test_amp[:,5]\n\n#Y=test_amp.iloc[:,5]\n#print(Y)\ntest_size = 0.4\nseed = 25\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\nmodel = LogisticRegression()\nmodel.fit(X_train, Y_train)\npredicted = model.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult = model.score(X_test, Y_test)\nprint(\"Accuracy: \", (result*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model.predict(X_test),Y_test))\n#print(test_data)\n\ntest_data2=test_data.loc[:,['FULL_Charge', 'FULL_AcidicMolPerc','FULL_DAYM780201', 'FULL_OOBM850104', 'AS_MeanAmphiMoment']]\ntest_data2=test_data2.values \n#model1 = LogisticRegression() \n#model1.fit(X,Y)\nkj_results=model.predict(test_data2)\n\n#print(test_data2)\nkj_results","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df = pd.DataFrame(kj_results)\ndf.columns = ['CLASS']\ndf.index.name = 'Index'\ndf['CLASS']=df['CLASS'].map({0.0:False,1.0:True})\nprint(df)\n#X=test_amp.iloc[:,0:5]\n#=test_amp.iloc[:,5]\ndf.to_csv(\"kj.csv\")\ndf[\"CLASS\"].unique()\n#print(df.groupby(\"CLASS\").size()[0].sum())\n#print(df.groupby(\"CLASS\").size()[1].sum())\ndf['CLASS'].value_counts()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Gausian/Naive Bayes"},{"metadata":{"trusted":true},"cell_type":"code","source":"model=GaussianNB()\nfrom sklearn.metrics import matthews_corrcoef\ntest_size = 0.4\nseed = 25\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\nrandom_state=seed)\nmodel.fit(X_train, Y_train)\npredicted = model.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult = model.score(X_test, Y_test)\nprint(\"Accuracy: \", (result*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model.predict(X_test),Y_test))\n#print(test_data)\n\nX=test_amp.iloc[:,0:5]\nY=test_amp.iloc[:,5]\nmodel=GaussianNB() \nmodel.fit(X,Y)\nkj_results=model.predict(test_data2)\n\n#print(test_data2)\nkj_results","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Linear Discriminant Analysis"},{"metadata":{"trusted":true},"cell_type":"code","source":"model=LinearDiscriminantAnalysis()\nfolds=10\nkfold = KFold(n_splits=folds, random_state=7, shuffle=True,)\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint((\"Accuracy: %.3f%% (%.3f%%)\") % (results.mean()*100.0, results.std()*100.0))\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Support Vector Machines"},{"metadata":{"trusted":true},"cell_type":"code","source":"model=SVC()\nfolds=10\nkfold = KFold(n_splits=folds, random_state=7, shuffle=True,)\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint((\"Accuracy: %.3f%% (%.3f%%)\") % (results.mean()*100.0, results.std()*100.0))","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4} \ No newline at end of file +{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nimport sklearn\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n for filename in filenames:\n print(os.path.join(dirname, filename))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Importing data"},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"# Importing data\ntest_data = pd.read_csv(\"/kaggle/input/ace-class-assignment/Test.csv\", header=0, sep=\",\")\namp_train = pd.read_csv(\"/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\", header=0, sep=\",\")\namp_train.head()\n\n\n\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"test_data.head()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## General data attributes and descriptive statistics"},{"metadata":{"trusted":true},"cell_type":"code","source":"#Describing general data attributes\ntrain_dim=amp_train.shape #gets the dimensions of the tranining dataset\ntest_dim= test_data.shape #gets the dimensions of the tesing dataset\nprint(train_dim)\nprint(test_dim)\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"We can see that the test data has one attribute less than the train data set"},{"metadata":{"trusted":true},"cell_type":"code","source":"atr_types=amp_train.dtypes #gets the data type for each column in training dataset\n\natr_types\n\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"amp_train.isnull().sum() # gets the sum of the missing values/observations in each column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":" All attributes have complete observations"},{"metadata":{"trusted":true},"cell_type":"code","source":"# Descriptive statistics \nstats=amp_train.describe()\nstats","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"From the summary statistics, its visible that some of the attributes like FULL_CHARGE, FULL_AcidicMolPerc and\tFULL_OOBM850104 have outlier values basing on the values of the 75% quartile and maximum values "},{"metadata":{},"cell_type":"markdown","source":"# Class distributions\n\nSometimes, observations from the different classes may not be equal, these may need special handling, so its important to note the class distributions, as if they are uneven, they may bias our model"},{"metadata":{"trusted":true},"cell_type":"code","source":"# CLass distibutions \ncdists= amp_train.groupby('CLASS').size() # groups the observation by the column of class, and counts all the observations including null values\nprint(cdists)\n\n#plots to visualize the class distribution\namp_train.groupby('CLASS').size().plot(kind=\"pie\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"The observations from each class seem8 to be equal"},{"metadata":{},"cell_type":"markdown","source":"# Correlation between the different attributes\nBasically, we need to examine our attributes for correlation as highly correlated attributes present the same data to the algorithm. Removing one may speed learning of the algorithm (less dimensions more speed) and also prevent overfitting of the algorithm"},{"metadata":{"trusted":true},"cell_type":"code","source":"# Correlation between attributes \ncorrelations = amp_train.corr(method=\"pearson\") # calculates pairwaise correlation for the attributes \ncorrelations\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"FULL_AURR980107 and FULL_AcidicMolPerc have a correlation coefficent of 0.79, this might mean these two attributes may be some what correlated. Same goes for AS_DAYM780201 and FULL_DAYM780201 (correlation coefficient is 0.894191)"},{"metadata":{"trusted":true},"cell_type":"code","source":"# Plots to visualize the correlations\nfrom matplotlib import rcParams\nsns.heatmap(correlations, annot=True)\nrcParams['figure.figsize'] = (11.7,8.27)\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Data skewness\n\nMost machine learning algorithms assume that data from the attributes is normally distributed, so identifying attributes with data that has a left or right skew, can be important as this can be easily corrected"},{"metadata":{"trusted":true},"cell_type":"code","source":"sk = amp_train.skew() # calculates the skew for each attribute\nsk","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Negative values like those of FULL_DAYM780201, FULL_OOBM850104,AS_DAYM780201, AS_FUKS010112, indicate that these attributes have values skewed more to the left\nValues closer to zero are indicative of a less or no skew, while positive values would mean that that particular attribute is skewed more to the right"},{"metadata":{},"cell_type":"markdown","source":" # Visualising data distributions with plots"},{"metadata":{"trusted":true},"cell_type":"code","source":"# Plot one, histogram to show the distributions\namp_train.hist(layout=(4,3), figsize=(16,16))\nplt.subplots_adjust(wspace=0.4, hspace=0.5)\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Plot two density plots can show the distributions better\namp_train.plot(kind=\"density\",subplots=True,layout=(4,3),sharex=False,sharey=False, figsize=(16,16))\n#amp_train.plot(kind=\"density\",subplots=False,layout=(4,3),sharex=True,sharey=True)\nplt.show()\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Distributions for AS_MeanAmphiMoment,FULL_AcidicMolPerc and NT_EFC195 dont look so good"},{"metadata":{},"cell_type":"markdown","source":"# Data transformations\nUsing squaring to transform the attributes with negative values into postives"},{"metadata":{"trusted":true},"cell_type":"code","source":"\nneg1=amp_train.iloc[:,0]\ntneg1=neg1**2\ntneg1.plot(kind=\"density\")\n\namp_train.iloc[:,0]=tneg1\n\nneg2=amp_train.iloc[:,5]\ntneg2=neg2**2\ntneg2.plot(kind=\"density\")\namp_train.iloc[:,5]=tneg2\n\n## test\nneg3=test_data.iloc[:,0]\ntneg3=neg3**2\ntneg3.plot(kind=\"density\")\ntest_data.iloc[:,0]=tneg3\n\n\n\nneg4=test_data.iloc[:,5]\ntneg4=neg4**2\ntneg4.plot(kind=\"density\")\ntest_data.iloc[:,5]=tneg4","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Feature selection\n\n\n"},{"metadata":{"trusted":true},"cell_type":"code","source":" #test one selecting out features with low variance\nfrom sklearn.feature_selection import VarianceThreshold\nsel = VarianceThreshold(threshold=(.8 * (1 - .8)))\nk=sel.fit_transform(amp_train)\nnames=amp_train.columns[sel.get_support(indices=True)]\nprint(k.shape)\namp_train2=pd.DataFrame(k,columns=names)\namp_train2.head()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"After selecting out features with low variance, only 8 attribute remained "},{"metadata":{"trusted":true},"cell_type":"code","source":"#test two using sklearn with a chi square test\n\nfrom sklearn.feature_selection import SelectKBest\nfrom sklearn.feature_selection import chi2\n\ntest_array = amp_train2.values\n\ntest_atr = test_array[:,0:7]\nclass_atr = test_array[:,7]\n\n\ntest = SelectKBest(score_func=chi2, k=5)\nfit = test.fit(test_atr, class_atr)\n\n\nprint(fit.scores_)\nfeatures = fit.transform(test_atr)\nnames2=amp_train2.columns[fit.get_support(indices=True)]\namp_train3=pd.DataFrame(features,columns=names2)\namp_train3.iloc[:5,]\nprint(names2)\n\n\n\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Test three Recursive feature elimination\n\nfrom sklearn.feature_selection import RFE\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.ensemble import RandomForestClassifier\n\nmodel1 = LogisticRegression()\nmodel2=RandomForestClassifier()\n\nrfe = RFE(model1, 5)\nfit2 = rfe.fit(test_atr, class_atr)\nfeatures2 = fit2.transform(test_atr)\n\nrfe2= RFE(model2, 5)\nfit3 = rfe2.fit(test_atr, class_atr)\n\n\n\n\nnames3= set(amp_train2.columns[fit2.get_support(indices=True)])\n\nnames4= set(amp_train2.columns[fit3.get_support(indices=True)])\n\nnames2=set(names2)\n\ncomn=names2&names3&names4 ### identifies features common to all the feature selection methods used\ncomn\n\nimport collections\n\ncomn=collections.deque(comn)\ncomn.appendleft(\"FULL_Charge\")\ncomn\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Getting the indices of the chosen attributes"},{"metadata":{"trusted":true},"cell_type":"code","source":"\nindice=[]\n\nfor index,name in enumerate(amp_train.columns):\n for sub_name in comn:\n if name==sub_name:\n indice.append(index)\nindice\n ","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Subsetting the data for the chosen attributes "},{"metadata":{"trusted":true},"cell_type":"code","source":"amp_train = pd.read_csv(\"/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\", header=0, sep=\",\")\n\n\ntest_amp =amp_train.iloc[:,[0,1,3,5,7,11]]\n\ntest_amp.head()\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import train_test_split\nfrom sklearn.model_selection import KFold\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.metrics import confusion_matrix\n\n\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.svm import SVC\nfrom sklearn.neighbors import KNeighborsClassifier\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Logistic regression using cross validation"},{"metadata":{"trusted":true},"cell_type":"code","source":"\nX=test_amp.iloc[:,0:5]\nY=test_amp.iloc[:,5]\nfolds=10\nkfold = KFold(n_splits=folds, random_state=7, shuffle=True,)\nmodel = LogisticRegression()\nresults = cross_val_score(model, X, Y, cv=kfold)\n\nprint((\"Accuracy: %.3f%% (%.3f%%)\") % (results.mean()*100.0, results.std()*100.0))\n\n\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Model one\n ## Logistic regression with a test train split using 5 features\n "},{"metadata":{"trusted":true},"cell_type":"code","source":"test_amp =amp_train.values[:,[0,1,3,5,7,11]]\nfrom sklearn.metrics import matthews_corrcoef\nX=test_amp[:,0:5]\nY=test_amp[:,5]\n\n#Training data spliting \n\ntest_size = 0.4\nseed = 42\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\n\n#model training \n\nmodel1 = LogisticRegression()\nmodel1.fit(X_train, Y_train)\n\n# predicting\n\npredicted = model1.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult1 = model1.score(X_test, Y_test)\n\n# Results accuracy \n\nprint(\"Accuracy: \", (result1*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model1.predict(X_test),Y_test))\nmcc1=matthews_corrcoef(model1.predict(X_test),Y_test)\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":" # Model two\n## Gausian/Naive Bayes using five features "},{"metadata":{"trusted":true},"cell_type":"code","source":"test_amp =amp_train.values[:,[0,1,3,5,7,11]]\nfrom sklearn.metrics import matthews_corrcoef\nX=test_amp[:,0:5]\nY=test_amp[:,5]\n\n#Training data spliting \n\ntest_size = 0.4\nseed = 42\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\n\n#model training \n\nmodel2 = GaussianNB()\nmodel2.fit(X_train, Y_train)\n\n# predicting\n\npredicted = model2.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult2 = model2.score(X_test, Y_test)\n\n# Results accuracy \n\nprint(\"Accuracy: \", (result2*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model2.predict(X_test),Y_test))\nmcc2=matthews_corrcoef(model2.predict(X_test),Y_test)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Model three\n## Linear Discriminant Analysis using five features "},{"metadata":{"trusted":true},"cell_type":"code","source":"test_amp =amp_train.values[:,[0,1,3,5,7,11]]\nfrom sklearn.metrics import matthews_corrcoef\nX=test_amp[:,0:5]\nY=test_amp[:,5]\n\n#Training data spliting \n\ntest_size = 0.4\nseed = 42\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\n\n#model training \n\nmodel3=LinearDiscriminantAnalysis()\nmodel3.fit(X_train, Y_train)\n\n# predicting\n\npredicted = model3.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult3 = model3.score(X_test, Y_test)\n\n# Results accuracy \n\nprint(\"Accuracy: \", (result3*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model3.predict(X_test),Y_test))\n\nmcc3=matthews_corrcoef(model3.predict(X_test),Y_test)\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Model four \n ## Support Vector Machines with five features"},{"metadata":{"trusted":true},"cell_type":"code","source":"test_amp =amp_train.values[:,[0,1,3,5,7,11]]\nfrom sklearn.metrics import matthews_corrcoef\nX=test_amp[:,0:5]\nY=test_amp[:,5]\n\n#Training data spliting \n\ntest_size = 0.4\nseed = 42\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\n\n#model training \n\nmodel4=SVC()\nmodel4.fit(X_train, Y_train)\n\n# predicting\n\npredicted = model4.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult4 = model4.score(X_test, Y_test)\n\n# Results accuracy \n\nprint(\"Accuracy: \", (result4*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model4.predict(X_test),Y_test))\n\n\nmcc4=matthews_corrcoef(model4.predict(X_test),Y_test)\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# model 5\n ## K-Nearest neighbours with five features\n "},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.neighbors import KNeighborsClassifier\nmodel5 = KNeighborsClassifier(n_neighbors=5)\n#Training data spliting \n\ntest_size = 0.4\nseed = 42\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\n\n#model training \n\nmodel5.fit(X_train, Y_train)\n\n# predicting\n\npredicted = model5.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult5 = model5.score(X_test, Y_test)\n\n# Results accuracy \n\nprint(\"Accuracy: \", (result5*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model5.predict(X_test),Y_test))\n\nmcc5=matthews_corrcoef(model5.predict(X_test),Y_test)\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Model six\n ## Centroid clasifier "},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.neighbors import NearestCentroid\nmodel6 = NearestCentroid()\n#Training data spliting \n\ntest_size = 0.4\nseed = 42\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\n\n#model training \n\nmodel6.fit(X_train, Y_train)\n\n# predicting\n\npredicted = model6.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult6 = model6.score(X_test, Y_test)\n\n# Results accuracy \n\nprint(\"Accuracy: \", (result6*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model6.predict(X_test),Y_test))\n\nmcc6=matthews_corrcoef(model6.predict(X_test),Y_test)\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Model seven\n\n## Decision trees with five features \n"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn import tree\n#Training data spliting \n\ntest_size = 0.4\nseed = 42\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\n\n#model training \n\nmodel7=tree.DecisionTreeClassifier()\nmodel7.fit(X_train, Y_train)\n\n# predicting\n\npredicted = model7.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult7 = model7.score(X_test, Y_test)\n\n# Results accuracy \n\nprint(\"Accuracy: \", (result7*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model7.predict(X_test),Y_test))\nmcc7=matthews_corrcoef(model7.predict(X_test),Y_test)\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Model eight \n## Randomised tree"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.ensemble import RandomForestClassifier\nmodel8 =RandomForestClassifier()\n#Training data spliting \n\ntest_size = 0.4\nseed = 42\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\n\n#model training \n\nmodel8.fit(X_train, Y_train)\n\n# predicting\n\npredicted = model8.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult8 = model8.score(X_test, Y_test)\n\n# Results accuracy \n\nprint(\"Accuracy: \", (result8*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model8.predict(X_test),Y_test))\n\n\nmcc8=matthews_corrcoef(model8.predict(X_test),Y_test)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Model nine \n ## Gradient tree boosting\n"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.ensemble import GradientBoostingClassifier\nmodel9 =GradientBoostingClassifier()\n\n#Training data spliting \n\ntest_size = 0.4\nseed = 42\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\n\n#model training \n\nmodel9.fit(X_train, Y_train)\n\n# predicting\n\npredicted = model9.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult9 = model9.score(X_test, Y_test)\n\n# Results accuracy \n\nprint(\"Accuracy: \", (result9*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model9.predict(X_test),Y_test))\n\nmcc9=matthews_corrcoef(model9.predict(X_test),Y_test)\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Model ten\n## Stochastic Gradient Descent "},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.linear_model import SGDClassifier\nmodel10 = SGDClassifier()\n\n#Training data spliting \n\ntest_size = 0.4\nseed = 42\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\n\n#model training \n\nmodel10.fit(X_train, Y_train)\n\n# predicting\n\npredicted = model10.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult10 = model10.score(X_test, Y_test)\n\n# Results accuracy \n\nprint(\"Accuracy: \", (result10*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model10.predict(X_test),Y_test))\n\n\nmcc10=matthews_corrcoef(model10.predict(X_test),Y_test)\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"compare=[result1,result2,result3,result4,result5,result6,result7,result8,result9,result10]\n\ncompare=pd.DataFrame(compare).T\n\ncompare=compare.rename(columns={0:\"LGR\", 1:\"GNB\", 2:\"LDN\", 3:\"SVM\", 4:\"KNN\", 5:\"CCL\", 6:\"DCS\", 7:\"RDT\", 8:\"GBT\", 9:\"SGD\"})\n\ncompareMCC=[mcc1,mcc2,mcc3,mcc4,mcc5,mcc6,mcc7,mcc8,mcc9,mcc10]\ncompareMCC=pd.DataFrame(compareMCC).T\ncompareMCC=compareMCC.rename(columns={0:\"LGR\", 1:\"GNB\", 2:\"LDN\", 3:\"SVM\", 4:\"KNN\", 5:\"CCL\", 6:\"DCS\", 7:\"RDT\", 8:\"GBT\", 9:\"SGD\"})\n\ncompare=compare.append(compareMCC)\n#compare.plot(kind=\"box\")\n#plt.plot(\"Mean of MCC and Accuracy\",\"Different models\", data=compare)\n\n\ncompare=compare.values\n\nfig = plt.figure()\nax = fig.add_subplot(111)\nax.boxplot(compare)\nplt.xticks([1, 2, 3,4,5,6,7,8,9,10], [\"LGR\",\"GNB\",\"LDN\",\"SVM\",\"KNN\",\"CCL\",\"DCS\",\"RDT\",\"GBT\",\"SGD\"])\n\n\n\nax.set_title('A comparison of the different Accuracies and MCC from the different Models')\nax.set_xlabel('The different Models')\nax.set_ylabel('Mean of Accuracy and MCC')\nplt.show()\n\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Predicting from the test data"},{"metadata":{"trusted":true},"cell_type":"code","source":"\ntest_data = pd.read_csv(\"/kaggle/input/ace-class-assignment/Test.csv\", header=0, sep=\",\")\ntest_data2=test_data.values[:,[0,1,3,5,7]]","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### Predictions from logistic Regression"},{"metadata":{"trusted":true},"cell_type":"code","source":"model1.fit(X,Y) ## retrains the algorithm again on the entire train data set\nkj_results=model1.predict(test_data2)\n\ndf = pd.DataFrame(kj_results)\ndf.columns = ['CLASS']\ndf.index.name = 'Index'\ndf['CLASS']=df['CLASS'].map({0.0:False,1.0:True})\ndf.to_csv(\"kjLGR.csv\")\ndf[\"CLASS\"].unique()\nprint(df.groupby(\"CLASS\").size()[0].sum())\nprint(df.groupby(\"CLASS\").size()[1].sum())\ndf['CLASS'].value_counts()\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Score from the leader board using this prediction is 0.82503"},{"metadata":{},"cell_type":"markdown","source":"## Predicting using Gausssian"},{"metadata":{"trusted":true},"cell_type":"code","source":"model2.fit(X,Y) ## retrains the algorithm again on the entire train data set\nkj_results=model2.predict(test_data2)\n\ndf = pd.DataFrame(kj_results)\ndf.columns = ['CLASS']\ndf.index.name = 'Index'\ndf['CLASS']=df['CLASS'].map({0.0:False,1.0:True})\ndf.to_csv(\"kjGNB.csv\")\ndf[\"CLASS\"].unique()\nprint(df.groupby(\"CLASS\").size()[0].sum())\nprint(df.groupby(\"CLASS\").size()[1].sum())\ndf['CLASS'].value_counts()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Score on leader board using this prediction was 0.84591"},{"metadata":{},"cell_type":"markdown","source":"# Predicting using Support Vector Machines "},{"metadata":{"trusted":true},"cell_type":"code","source":"model4.fit(X,Y) ## retrains the algorithm again on the entire train data set\nkj_results=model4.predict(test_data2)\n\ndf = pd.DataFrame(kj_results)\ndf.columns = ['CLASS']\ndf.index.name = 'Index'\ndf['CLASS']=df['CLASS'].map({0.0:False,1.0:True})\ndf.to_csv(\"kjSVM.csv\")\ndf[\"CLASS\"].unique()\nprint(df.groupby(\"CLASS\").size()[0].sum())\nprint(df.groupby(\"CLASS\").size()[1].sum())\ndf['CLASS'].value_counts()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Score on leader board using this prediction was 0.82136"},{"metadata":{},"cell_type":"markdown","source":"## Predicting using the randomised tree classifier"},{"metadata":{"trusted":true},"cell_type":"code","source":"model8.fit(X,Y) ## retrains the algorithm again on the entire train data set\nkj_results=model8.predict(test_data2)\n\ndf = pd.DataFrame(kj_results)\ndf.columns = ['CLASS']\ndf.index.name = 'Index'\ndf['CLASS']=df['CLASS'].map({0.0:False,1.0:True})\ndf.to_csv(\"kjRDT.csv\")\ndf[\"CLASS\"].unique()\nprint(df.groupby(\"CLASS\").size()[0].sum())\nprint(df.groupby(\"CLASS\").size()[1].sum())\ndf['CLASS'].value_counts()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Score on leader board using this prediction was 0.80561"},{"metadata":{},"cell_type":"markdown","source":"## Predicting using the Gradient tree boosting classifier "},{"metadata":{"trusted":true},"cell_type":"code","source":"model9.fit(X,Y) ## retrains the algorithm again on the entire train data set\nkj_results=model9.predict(test_data2)\n\ndf = pd.DataFrame(kj_results)\ndf.columns = ['CLASS']\ndf.index.name = 'Index'\ndf['CLASS']=df['CLASS'].map({0.0:False,1.0:True})\ndf.to_csv(\"kjGBT.csv\")\ndf[\"CLASS\"].unique()\nprint(df.groupby(\"CLASS\").size()[0].sum())\nprint(df.groupby(\"CLASS\").size()[1].sum())\ndf['CLASS'].value_counts()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Score on leader board using this prediction was 0.79678"},{"metadata":{},"cell_type":"markdown","source":"Random forest and Gradient boosting classifiers had the highest accuracies during training but gave the least scores on the leader board\n\nGausian gave the highest score"},{"metadata":{},"cell_type":"markdown","source":"# More with the gausian "},{"metadata":{},"cell_type":"markdown","source":"## Using gausian with more features"},{"metadata":{},"cell_type":"markdown","source":"## Using gausian with eight features "},{"metadata":{"trusted":true},"cell_type":"code","source":"amp_train = pd.read_csv(\"/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\", header=0, sep=\",\")\ntest_data = pd.read_csv(\"/kaggle/input/ace-class-assignment/Test.csv\", header=0, sep=\",\")\n\n#selecting out features with low variance\nfrom sklearn.feature_selection import VarianceThreshold\nsel = VarianceThreshold(threshold=(.8 * (1 - .8)))\nk=sel.fit_transform(amp_train)\nnames=amp_train.columns[sel.get_support(indices=True)]\nprint(k.shape)\namp_train2=pd.DataFrame(k,columns=names)\n#print(amp_train2)\n\nn=sel.fit_transform(test_data)\nnames2=test_data.columns[sel.get_support(indices=True)]\ntest_data=pd.DataFrame(n,columns=names2)\ntest_data2=test_data.values\n\n#print(test_data)\n\n### data \ntest_amp =amp_train2.values\nX=test_amp[:,0:7]\nY=test_amp[:,7]\n\n\n\n\n#model\nmodel=GaussianNB()\nfrom sklearn.metrics import matthews_corrcoef\ntest_size = 0.4\nseed = 42\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\nrandom_state=seed, shuffle=\"True\")\nmodel.fit(X_train, Y_train)\npredicted = model.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult = model.score(X_test, Y_test)\nprint(\"Accuracy: \", (result*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model.predict(X_test),Y_test)) \nmodel.fit(X,Y)\nkj_resultsg8=model.predict(test_data)\n\n\n#### results \n\ndf = pd.DataFrame(kj_resultsg8)\ndf.columns = ['CLASS']\ndf.index.name = 'Index'\ndf['CLASS']=df['CLASS'].map({0.0:False,1.0:True})\n\ndf.to_csv(\"kjGNB8.csv\")\ndf[\"CLASS\"].unique()\nprint(df.groupby(\"CLASS\").size()[0].sum())\nprint(df.groupby(\"CLASS\").size()[1].sum())\ndf['CLASS'].value_counts()\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"MCC value for the Gaussian with 8 features and that with 5 features are almost the same, but the leaderboard score using the gausian with 8 features was 0.86379, which is an improvement over the 0.84 score from the five features"},{"metadata":{},"cell_type":"markdown","source":"## Using gaussian with all attributes "},{"metadata":{"trusted":true},"cell_type":"code","source":"amp_train = pd.read_csv(\"/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\", header=0, sep=\",\")\ntest_data = pd.read_csv(\"/kaggle/input/ace-class-assignment/Test.csv\", header=0, sep=\",\")\n\n\n### data \ntest_amp =amp_train.values\nX=test_amp[:,0:11]\nY=test_amp[:,11]\n\n\n#model\nmodel=GaussianNB()\nfrom sklearn.metrics import matthews_corrcoef\ntest_size = 0.4\nseed = 42\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\nrandom_state=seed)\nmodel.fit(X_train, Y_train)\npredicted = model.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult = model.score(X_test, Y_test)\nprint(\"Accuracy: \", (result*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model.predict(X_test),Y_test)) \nmodel.fit(X,Y)\n\nkj_resultsg12=model.predict(test_data)\n\n\n#### results \n\ndf = pd.DataFrame(kj_resultsg12)\ndf.columns = ['CLASS']\ndf.index.name = 'Index'\ndf['CLASS']=df['CLASS'].map({0.0:False,1.0:True})\n\ndf.to_csv(\"kjGNB11.csv\")\ndf[\"CLASS\"].unique()\nprint(df.groupby(\"CLASS\").size()[0].sum())\nprint(df.groupby(\"CLASS\").size()[1].sum())\ndf['CLASS'].value_counts()\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Score from the leaderboard using all features was 0.99559"}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4} \ No newline at end of file From edc2d001ae21dcaa5fc17ff7949d8a48828736ae Mon Sep 17 00:00:00 2001 From: Jupiter Marina Date: Thu, 12 Mar 2020 20:32:13 +0300 Subject: [PATCH 19/29] Made more predictions from more algorithms --- Assignment Colab/.Rhistory | 0 .../Jupiter Marina-checkpoint.ipynb | 1962 +++++++++++++++++ 2 files changed, 1962 insertions(+) create mode 100644 Assignment Colab/.Rhistory create mode 100644 Assignment Colab/.ipynb_checkpoints/Jupiter Marina-checkpoint.ipynb diff --git a/Assignment Colab/.Rhistory b/Assignment Colab/.Rhistory new file mode 100644 index 0000000..e69de29 diff --git a/Assignment Colab/.ipynb_checkpoints/Jupiter Marina-checkpoint.ipynb b/Assignment Colab/.ipynb_checkpoints/Jupiter Marina-checkpoint.ipynb new file mode 100644 index 0000000..abc4341 --- /dev/null +++ b/Assignment Colab/.ipynb_checkpoints/Jupiter Marina-checkpoint.ipynb @@ -0,0 +1,1962 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", + "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" + }, + "outputs": [], + "source": [ + "# This Python 3 environment comes with many helpful analytics libraries installed\n", + "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", + "# For example, here's several helpful packages to load in \n", + "\n", + "import numpy as np # linear algebra\n", + "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", + "import matplotlib.pyplot as plot\n", + "#import seaborn as sns\n", + "import sklearn\n", + "\n", + "# Input data files are available in the \"../input/\" directory.\n", + "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", + "\n", + "import os\n", + "for dirname, _, filenames in os.walk('/kaggle/input'):\n", + " for filename in filenames:\n", + " print(os.path.join(dirname, filename))\n", + "\n", + "# Any results you write to the current directory are saved as output." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "# Importing data" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0", + "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a" + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n", + "0 4.0 3.704 0.873 73.519 \n", + "1 4.0 4.444 0.892 62.444 \n", + "2 2.0 0.000 0.901 47.000 \n", + "3 4.5 0.000 0.869 69.222 \n", + "4 -4.0 21.591 1.061 71.682 \n", + "\n", + " FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n", + "0 0.987 -4.833 0 0.382 \n", + "1 0.931 -0.584 0 0.320 \n", + "2 1.039 -5.664 0 0.164 \n", + "3 0.982 -5.423 0 2.010 \n", + "4 0.976 -2.002 0 2.758 \n", + "\n", + " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 \n", + "0 74.556 7.225 1.234 \n", + "1 56.056 4.942 1.853 \n", + "2 47.000 5.969 1.174 \n", + "3 69.222 5.462 1.138 \n", + "4 66.000 5.582 1.453 " + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "test.head()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# test_amp =amp_train[['FULL_Charge', 'FULL_AcidicMolPerc','FULL_OOBM850104','FULL_DAYM780201', 'AS_MeanAmphiMoment','CLASS']]\n", + "#print(test_amp)\n", + "#test_data=test_data[['FULL_Charge', 'FULL_AcidicMolPerc','FULL_OOBM850104','FULL_DAYM780201', 'AS_MeanAmphiMoment']]\n", + "#X=test_amp.drop(\"CLASS\",axis=1)\n", + "#Y=test_amp.CLASS\n", + "#model=GaussianNB() \n", + "#model.fit(X,Y)\n", + "#kj_results=model.predict(test_data)\n", + "\n", + "#print(test_data2)\n", + "#kj_results" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## General data attributes and descriptive statistics" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(3038, 12)\n", + "(758, 11)\n", + "FULL_Charge float64\n", + "FULL_AcidicMolPerc float64\n", + "FULL_AURR980107 float64\n", + "FULL_DAYM780201 float64\n", + "FULL_GEOR030101 float64\n", + "FULL_OOBM850104 float64\n", + "NT_EFC195 int64\n", + "AS_MeanAmphiMoment float64\n", + "AS_DAYM780201 float64\n", + "AS_FUKS010112 float64\n", + "CT_RACS820104 float64\n", + "CLASS int64\n", + "dtype: object\n" + ] + }, + { + "data": { + "text/plain": [ + "FULL_Charge 0\n", + "FULL_AcidicMolPerc 0\n", + "FULL_AURR980107 0\n", + "FULL_DAYM780201 0\n", + "FULL_GEOR030101 0\n", + "FULL_OOBM850104 0\n", + "NT_EFC195 0\n", + "AS_MeanAmphiMoment 0\n", + "AS_DAYM780201 0\n", + "AS_FUKS010112 0\n", + "CT_RACS820104 0\n", + "CLASS 0\n", + "dtype: int64" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Describing general data attributes\n", + "train_dim=amp_train.shape #gets the dimensions of the tranining dataset\n", + "test_dim= test_data.shape #gets the dimensions of the tesing dataset\n", + "print(train_dim)\n", + "print(test_dim)\n", + "\n", + "atr_types=amp_train.dtypes #gets the data type for each column in training dataset\n", + "print(atr_types)\n", + "amp_train.isnull().sum() # gets the sum of the missing values/observations in each column\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Descriptive statistics \n", + "stats=amp_train.describe()\n", + "print(stats)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Class distributions\n", + "\n", + "Sometimes, observations from the different classes may not be equal, these may need special handling, so its important to note the class distributions, as if they are uneven, they may bias our model" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# CLass distibutions \n", + "cdists= amp_train.groupby('CLASS').size() # groups the observation by the column of class, and counts all the observations including null values\n", + "print(cdists)\n", + "\n", + "#plots to visualize the class distribution\n", + "amp_train.groupby('CLASS').size().plot(kind=\"pie\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The observations from each class seem to be equal" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Correlation between the different attributes\n", + "Basically, we need to examine our attributes for correlation as highly correlated attributes present the same data to the algorithm. Removing one may speed learning of the algorithm (less dimensions more speed)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Correlation between attributes \n", + "correlations = amp_train.corr(method=\"pearson\") # calculates pairwaise correlation for the attributes \n", + "print(correlations)\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "FULL_AURR980107 and FULL_AcidicMolPerc have a correlation coefficent of 0.79, this might mean these two attributes may be some what correlated. Same goes for AS_DAYM780201 and FULL_DAYM780201 (correlation coefficient is 0.894191)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Plots to visualize the correlations\n", + "from matplotlib import rcParams\n", + "sns.heatmap(correlations, annot=True)\n", + "rcParams['figure.figsize'] = 11.7,8.27\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Data skewness\n", + "\n", + "Most machine learning algorithms assume that data from the attributes is normally distributed, so identifying attributes with data that has a left or right skew, can be important as this can be easily corrected" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sk = amp_train.skew() # calculates the skew for each attribute\n", + "print(sk)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Negative values like those of FULL_DAYM780201, FULL_OOBM850104,AS_DAYM780201, AS_FUKS010112, indicate that these attributes have values skewed more to the left\n", + "Values closer to zero are indicative of a less or no skew, while positive values would mean that that particular attribute is skewed more to the right" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " # Visualising data distributions with plots" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Plot one, histogram to show the distributions\n", + "import matplotlib as plot \n", + "from matplotlib import pyplot\n", + "amp_train.hist(layout=(4,3), figsize=(16,16))\n", + "plot.pyplot.subplots_adjust(wspace=0.4, hspace=0.5)\n", + "pyplot.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Plot two density plots can show the distributions better\n", + "amp_train.plot(kind=\"density\",subplots=True,layout=(4,3),sharex=False,sharey=False, figsize=(16,16))\n", + "#amp_train.plot(kind=\"density\",subplots=False,layout=(4,3),sharex=True,sharey=True)\n", + "pyplot.show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Data transformations\n", + "Using square roots to transform the attributes with negative values into postives" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0 5.0\n", + "1 4.0\n", + "2 5.5\n", + "3 5.0\n", + "4 7.5\n", + " ... \n", + "3033 1.0\n", + "3034 -6.5\n", + "3035 -1.5\n", + "3036 2.0\n", + "3037 -1.0\n", + "Name: FULL_Charge, Length: 3038, dtype: float64\n", + "0 -3.663\n", + "1 -4.011\n", + "2 -2.512\n", + "3 -1.362\n", + "4 -2.091\n", + " ... \n", + "3033 -2.151\n", + "3034 -1.675\n", + "3035 -0.918\n", + "3036 -2.722\n", + "3037 -2.080\n", + "Name: FULL_OOBM850104, Length: 3038, dtype: float64\n", + "0 4.0\n", + "1 4.0\n", + "2 2.0\n", + "3 4.5\n", + "4 -4.0\n", + " ... \n", + "753 -1.5\n", + "754 -1.0\n", + "755 -1.0\n", + "756 -1.0\n", + "757 -7.0\n", + "Name: FULL_Charge, Length: 758, dtype: float64\n", + "0 -4.833\n", + "1 -0.584\n", + "2 -5.664\n", + "3 -5.423\n", + "4 -2.002\n", + " ... \n", + "753 -1.987\n", + "754 -0.745\n", + "755 -1.789\n", + "756 1.141\n", + "757 -0.066\n", + "Name: FULL_OOBM850104, Length: 758, dtype: float64\n" + ] + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "neg1=amp_train.iloc[:,0]\n", + "print(neg1)\n", + "tneg1=neg1**2\n", + "tneg1.plot(kind=\"density\")\n", + "amp_train.iloc[:,0]=tneg1\n", + "\n", + "\n", + "\n", + "neg2=amp_train.iloc[:,5]\n", + "print(neg2)\n", + "tneg2=neg2**2\n", + "tneg2.plot(kind=\"density\")\n", + "amp_train.iloc[:,5]=tneg2\n", + "\n", + "## test\n", + "neg3=test_data.iloc[:,0]\n", + "print(neg3)\n", + "tneg3=neg3**2\n", + "tneg3.plot(kind=\"density\")\n", + "test_data.iloc[:,0]=tneg3\n", + "\n", + "\n", + "\n", + "neg4=test_data.iloc[:,5]\n", + "print(neg4)\n", + "tneg4=neg4**2\n", + "tneg4.plot(kind=\"density\")\n", + "test_data.iloc[:,5]=tneg4" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "distributions for AS_MeanAmphiMoment,FULL_AcidicMolPerc and NT_EFC195 dont look so good" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Feature selection\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(3038, 8)\n" + ] + }, + { + "data": { + "text/html": [ + "
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3038 rows × 8 columns

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" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_DAYM780201 FULL_OOBM850104 \\\n", + "0 25.00 0.000 74.842 13.417569 \n", + "1 16.00 5.405 71.595 16.088121 \n", + "2 30.25 5.405 73.595 6.310144 \n", + "3 25.00 4.167 66.250 1.855044 \n", + "4 56.25 8.537 64.720 4.372281 \n", + "... ... ... ... ... \n", + "3033 1.00 5.263 67.947 4.626801 \n", + "3034 42.25 21.667 75.433 2.805625 \n", + "3035 2.25 12.500 76.542 0.842724 \n", + "3036 4.00 5.000 73.750 7.409284 \n", + "3037 1.00 15.789 66.158 4.326400 \n", + "\n", + " AS_MeanAmphiMoment AS_DAYM780201 AS_FUKS010112 CLASS \n", + "0 0.282 73.444 5.661 1.0 \n", + "1 0.600 68.222 6.537 1.0 \n", + "2 0.593 69.444 4.934 1.0 \n", + "3 0.614 67.222 4.316 1.0 \n", + "4 0.616 72.944 4.540 1.0 \n", + "... ... ... ... ... \n", + "3033 16.706 68.611 5.598 0.0 \n", + "3034 16.897 73.278 6.194 0.0 \n", + "3035 16.918 82.111 5.889 0.0 \n", + "3036 17.131 74.722 6.055 0.0 \n", + "3037 17.151 67.111 5.853 0.0 \n", + "\n", + "[3038 rows x 8 columns]" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + " #test one selecting out features with low variance\n", + "from sklearn.feature_selection import VarianceThreshold\n", + "sel = VarianceThreshold(threshold=(.8 * (1 - .8)))\n", + "k=sel.fit_transform(amp_train)\n", + "names=amp_train.columns[sel.get_support(indices=True)]\n", + "print(k.shape)\n", + "amp_train2=pd.DataFrame(k,columns=names)\n", + "amp_train2" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'amp_train2' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0msklearn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfeature_selection\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mchi2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0mtest_array\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mamp_train2\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 6\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mtest_atr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtest_array\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m7\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'amp_train2' is not defined" + ] + } + ], + "source": [ + "#test two\n", + "from sklearn.feature_selection import SelectKBest\n", + "from sklearn.feature_selection import chi2\n", + "\n", + "test_array = amp_train2.values\n", + "\n", + "test_atr = test_array[:,0:7]\n", + "class_atr = test_array[:,7]\n", + "\n", + "\n", + "test = SelectKBest(score_func=chi2, k=5)\n", + "fit = test.fit(test_atr, class_atr)\n", + "\n", + "\n", + "print(fit.scores_)\n", + "features = fit.transform(test_atr)\n", + "names2=amp_train2.columns[fit.get_support(indices=True)]\n", + "amp_train3=pd.DataFrame(features,columns=names2)\n", + "print(amp_train3[5:])\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Test three Recursive feature elimination\n", + "\n", + "from sklearn.feature_selection import RFE\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.ensemble import RandomForestClassifier\n", + "\n", + "model1 = LogisticRegression()\n", + "model2=RandomForestClassifier()\n", + "\n", + "rfe = RFE(model1, 4)\n", + "fit2 = rfe.fit(test_atr, class_atr)\n", + "\n", + "rfe2= RFE(model2, 4)\n", + "fit3 = rfe2.fit(test_atr, class_atr)\n", + "\n", + "\n", + "\n", + "\n", + "names3=amp_train2.columns[fit2.get_support(indices=True)]\n", + "\n", + "names4=amp_train2.columns[fit3.get_support(indices=True)]\n", + "\n", + "print(names3)\n", + "print(names4)\n", + "print(names2)\n", + "print(amp_train.columns)\n", + "print(amp_train2)\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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FULL_ChargeFULL_AcidicMolPercFULL_OOBM850104FULL_DAYM780201AS_MeanAmphiMomentCLASS
05.00.000-3.66374.8420.2821
14.05.405-4.01171.5950.6001
25.55.405-2.51273.5950.5931
35.04.167-1.36266.2500.6141
47.58.537-2.09164.7200.6161
.....................
30331.05.263-2.15167.94716.7060
3034-6.521.667-1.67575.43316.8970
3035-1.512.500-0.91876.54216.9180
30362.05.000-2.72273.75017.1310
3037-1.015.789-2.08066.15817.1510
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3038 rows × 6 columns

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" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_OOBM850104 FULL_DAYM780201 \\\n", + "0 5.0 0.000 -3.663 74.842 \n", + "1 4.0 5.405 -4.011 71.595 \n", + "2 5.5 5.405 -2.512 73.595 \n", + "3 5.0 4.167 -1.362 66.250 \n", + "4 7.5 8.537 -2.091 64.720 \n", + "... ... ... ... ... \n", + "3033 1.0 5.263 -2.151 67.947 \n", + "3034 -6.5 21.667 -1.675 75.433 \n", + "3035 -1.5 12.500 -0.918 76.542 \n", + "3036 2.0 5.000 -2.722 73.750 \n", + "3037 -1.0 15.789 -2.080 66.158 \n", + "\n", + " AS_MeanAmphiMoment CLASS \n", + "0 0.282 1 \n", + "1 0.600 1 \n", + "2 0.593 1 \n", + "3 0.614 1 \n", + "4 0.616 1 \n", + "... ... ... \n", + "3033 16.706 0 \n", + "3034 16.897 0 \n", + "3035 16.918 0 \n", + "3036 17.131 0 \n", + "3037 17.151 0 \n", + "\n", + "[3038 rows x 6 columns]" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\n", + "test_amp =amp_train.loc[:,['FULL_Charge', 'FULL_AcidicMolPerc',\"FULL_OOBM850104\",'FULL_DAYM780201', 'AS_MeanAmphiMoment','CLASS']]\n", + "test_amp\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.metrics import confusion_matrix\n", + "\n", + "\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", + "from sklearn.naive_bayes import GaussianNB\n", + "from sklearn.svm import SVC\n", + "from sklearn.neighbors import KNeighborsClassifier\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Logistic regression using cross validation" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "X=test_amp.iloc[:,0:5]\n", + "Y=test_amp.iloc[:,5]\n", + "folds=10\n", + "kfold = KFold(n_splits=folds, random_state=7, shuffle=True,)\n", + "model = LogisticRegression()\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "\n", + "print((\"Accuracy: %.3f%% (%.3f%%)\") % (results.mean()*100.0, results.std()*100.0))\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "ename": "FileNotFoundError", + "evalue": "[Errno 2] File /kaggle/input/ace-class-assignment/AMP_TrainSet.csv does not exist: '/kaggle/input/ace-class-assignment/AMP_TrainSet.csv'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mamp_train\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheader\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msep\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\",\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mtest_amp\u001b[0m \u001b[0;34m=\u001b[0m\u001b[0mamp_train\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'FULL_Charge'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'FULL_AcidicMolPerc'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\"FULL_OOBM850104\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'FULL_DAYM780201'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'AS_MeanAmphiMoment'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'CLASS'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/lib/python3.7/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36mparser_f\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, dialect, error_bad_lines, warn_bad_lines, delim_whitespace, low_memory, memory_map, float_precision)\u001b[0m\n\u001b[1;32m 674\u001b[0m )\n\u001b[1;32m 675\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 676\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 677\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 678\u001b[0m \u001b[0mparser_f\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/lib/python3.7/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m 446\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 447\u001b[0m \u001b[0;31m# Create the parser.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 448\u001b[0;31m \u001b[0mparser\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTextFileReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfp_or_buf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 449\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 450\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mchunksize\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0miterator\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/lib/python3.7/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m 878\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"has_index_names\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"has_index_names\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 879\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 880\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 881\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 882\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/lib/python3.7/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_make_engine\u001b[0;34m(self, engine)\u001b[0m\n\u001b[1;32m 1112\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mengine\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"c\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1113\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"c\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1114\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mCParserWrapper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1115\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1116\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"python\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/lib/python3.7/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, src, **kwds)\u001b[0m\n\u001b[1;32m 1889\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"usecols\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0musecols\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1890\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1891\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reader\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mparsers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTextReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msrc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1892\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munnamed_cols\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reader\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munnamed_cols\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1893\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader.__cinit__\u001b[0;34m()\u001b[0m\n", + "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._setup_parser_source\u001b[0;34m()\u001b[0m\n", + "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] File /kaggle/input/ace-class-assignment/AMP_TrainSet.csv does not exist: '/kaggle/input/ace-class-assignment/AMP_TrainSet.csv'" + ] + } + ], + "source": [ + "\n", + "#amp_train = pd.read_csv(\"/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\", header=0, sep=\",\")\n", + "#test_amp =amp_train.loc[:,['FULL_Charge', 'FULL_AcidicMolPerc',\"FULL_OOBM850104\",'FULL_DAYM780201', 'AS_MeanAmphiMoment','CLASS']]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Logistic regression with a test train split" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", + " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", + " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", + " 'CLASS'],\n", + " dtype='object')" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "amp_train = pd.read_csv(\"/media/jupiter/Marina/MASTERS-SECOND-SEMESTER/BIG-BIO-DATA/assignment/AMP_TrainSet.csv\", header=0, sep=\",\")\n", + "amp_train.columns" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 91.77631578947368\n", + "[[571 44]\n", + " [ 56 545]]\n", + "MCC: 0.8356300090704967\n" + ] + } + ], + "source": [ + "\n", + "\n", + "test_amp =amp_train.values[:,[0,1,3,5,7,11]]\n", + "from sklearn.metrics import matthews_corrcoef\n", + "X=test_amp[:,0:5]\n", + "Y=test_amp[:,5]\n", + "\n", + "#Y=test_amp.iloc[:,5]\n", + "#print(Y)\n", + "test_size = 0.4\n", + "seed = 25\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\n", + "model = LogisticRegression()\n", + "model.fit(X_train, Y_train)\n", + "predicted = model.predict(X_test)\n", + "matrix = confusion_matrix(Y_test, predicted)\n", + "result = model.score(X_test, Y_test)\n", + "print(\"Accuracy: \", (result*100.0))\n", + "print(matrix)\n", + "print('MCC: ', matthews_corrcoef(model.predict(X_test),Y_test))\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0., 0., 1., 1., 0., 0., 1., 0., 1., 1., 1., 1., 0., 0., 0., 0., 0.,\n", + " 1., 0., 1., 0., 1., 1., 1., 0., 0., 1., 1., 1., 0., 1., 1., 0., 1.,\n", + " 0., 0., 1., 1., 1., 1., 1., 1., 0., 1., 0., 0., 1., 1., 0., 1., 1.,\n", + " 0., 0., 1., 0., 1., 0., 1., 0., 1., 0., 0., 1., 1., 1., 1., 1., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 1., 0., 1., 1., 1., 1., 1., 1., 1., 1.,\n", + " 0., 0., 1., 1., 1., 0., 1., 1., 1., 1., 0., 1., 1., 1., 1., 0., 1.,\n", + " 1., 1., 1., 1., 1., 1., 1., 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"source": [ + "test_data=pd.read_csv(\"/media/jupiter/Marina/MASTERS-SECOND-SEMESTER/BIG-BIO-DATA/assignment/Test.csv\", header=0, sep=\",\")\n", + "test_data2=test_data.values[:,[0,1,3,5,7]]\n", + "#test_data2=test_data.loc[:,['FULL_Charge', 'FULL_AcidicMolPerc','FULL_DAYM780201', 'FULL_OOBM850104', 'AS_MeanAmphiMoment']]\n", + "#test_data2=test_data2.values \n", + "model.fit(X,Y)\n", + "kj_results=model.predict(test_data2)\n", + "kj_results" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " CLASS\n", + "Index \n", + "0 False\n", + "1 False\n", + "2 True\n", + "3 True\n", + "4 False\n", + "... ...\n", + "753 False\n", + "754 False\n", + "755 False\n", + "756 False\n", + "757 False\n", + "\n", + "[758 rows x 1 columns]\n" + ] + }, + { + "data": { + "text/plain": [ + "False 388\n", + "True 370\n", + "Name: CLASS, dtype: int64" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.DataFrame(kj_results)\n", + "df.columns = ['CLASS']\n", + "df.index.name = 'Index'\n", + "df['CLASS']=df['CLASS'].map({0.0:False,1.0:True})\n", + "print(df)\n", + "#X=test_amp.iloc[:,0:5]\n", + "#=test_amp.iloc[:,5]\n", + "df.to_csv(\"kj.csv\")\n", + "df[\"CLASS\"].unique()\n", + "#print(df.groupby(\"CLASS\").size()[0].sum())\n", + "#print(df.groupby(\"CLASS\").size()[1].sum())\n", + "df['CLASS'].value_counts()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Gausian/Naive Bayes" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 93.17434210526315\n", + "[[567 48]\n", + " [ 35 566]]\n", + "MCC: 0.8636997578586827\n" + ] + }, + { + "data": { + "text/plain": [ + "array([1., 1., 1., 1., 0., 0., 1., 0., 1., 1., 1., 1., 0., 0., 0., 0., 1.,\n", + " 1., 0., 1., 1., 1., 1., 1., 0., 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"\n", + "\n", + "#print(test_data2)\n", + "kj_results1" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " CLASS\n", + "Index \n", + "0 True\n", + "1 True\n", + "2 True\n", + "3 True\n", + "4 False\n", + "... ...\n", + "753 False\n", + "754 False\n", + "755 False\n", + "756 False\n", + "757 False\n", + "\n", + "[758 rows x 1 columns]\n" + ] + }, + { + "data": { + "text/plain": [ + "False 380\n", + "True 378\n", + "Name: CLASS, dtype: int64" + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.DataFrame(kj_results1)\n", + "df.columns = ['CLASS']\n", + "df.index.name = 'Index'\n", + "df['CLASS']=df['CLASS'].map({0.0:False,1.0:True})\n", + "print(df)\n", + "#X=test_amp.iloc[:,0:5]\n", + "#=test_amp.iloc[:,5]\n", + "df.to_csv(\"kjg.csv\")\n", + "df[\"CLASS\"].unique()\n", + "#print(df.groupby(\"CLASS\").size()[0].sum())\n", + "#print(df.groupby(\"CLASS\").size()[1].sum())\n", + "df['CLASS'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(3038, 8)\n", + " FULL_Charge FULL_AcidicMolPerc FULL_DAYM780201 FULL_OOBM850104 \\\n", + "0 5.0 0.000 74.842 -3.663 \n", + "1 4.0 5.405 71.595 -4.011 \n", + "2 5.5 5.405 73.595 -2.512 \n", + "3 5.0 4.167 66.250 -1.362 \n", + "4 7.5 8.537 64.720 -2.091 \n", + "... ... ... ... ... \n", + "3033 1.0 5.263 67.947 -2.151 \n", + "3034 -6.5 21.667 75.433 -1.675 \n", + "3035 -1.5 12.500 76.542 -0.918 \n", + "3036 2.0 5.000 73.750 -2.722 \n", + "3037 -1.0 15.789 66.158 -2.080 \n", + "\n", + " AS_MeanAmphiMoment AS_DAYM780201 AS_FUKS010112 CLASS \n", + "0 0.282 73.444 5.661 1.0 \n", + "1 0.600 68.222 6.537 1.0 \n", + "2 0.593 69.444 4.934 1.0 \n", + "3 0.614 67.222 4.316 1.0 \n", + "4 0.616 72.944 4.540 1.0 \n", + "... ... ... ... ... \n", + "3033 16.706 68.611 5.598 0.0 \n", + "3034 16.897 73.278 6.194 0.0 \n", + "3035 16.918 82.111 5.889 0.0 \n", + "3036 17.131 74.722 6.055 0.0 \n", + "3037 17.151 67.111 5.853 0.0 \n", + "\n", + "[3038 rows x 8 columns]\n", + "Accuracy: 93.25657894736842\n", + "[[567 48]\n", + " [ 34 567]]\n", + "MCC: 0.8653788401444746\n", + " CLASS\n", + "Index \n", + "0 True\n", + "1 True\n", + "2 True\n", + "3 True\n", + "4 False\n", + "... ...\n", + "753 False\n", + "754 False\n", + "755 False\n", + "756 False\n", + "757 False\n", + "\n", + "[758 rows x 1 columns]\n", + "380\n", + "378\n" + ] + }, + { + "data": { + "text/plain": [ + "False 380\n", + "True 378\n", + "Name: CLASS, dtype: int64" + ] + }, + "execution_count": 58, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "amp_train = pd.read_csv(\"/media/jupiter/Marina/MASTERS-SECOND-SEMESTER/BIG-BIO-DATA/assignment/AMP_TrainSet.csv\", header=0, sep=\",\")\n", + "test_data=pd.read_csv(\"/media/jupiter/Marina/MASTERS-SECOND-SEMESTER/BIG-BIO-DATA/assignment/Test.csv\", header=0, sep=\",\")\n", + "\n", + "#selecting out features with low variance\n", + "from sklearn.feature_selection import VarianceThreshold\n", + "sel = VarianceThreshold(threshold=(.8 * (1 - .8)))\n", + "k=sel.fit_transform(amp_train)\n", + "names=amp_train.columns[sel.get_support(indices=True)]\n", + "print(k.shape)\n", + "amp_train2=pd.DataFrame(k,columns=names)\n", + "print(amp_train2)\n", + "\n", + "n=sel.fit_transform(test_data)\n", + "names2=test_data.columns[sel.get_support(indices=True)]\n", + "test_data=pd.DataFrame(n,columns=names2)\n", + "test_data2=test_data.values\n", + "\n", + "#print(test_data)\n", + "\n", + "### data \n", + "test_amp =amp_train2.values\n", + "X=test_amp[:,0:7]\n", + "Y=test_amp[:,7]\n", + "\n", + "\n", + "\n", + "\n", + "#model\n", + "model=GaussianNB()\n", + "from sklearn.metrics import matthews_corrcoef\n", + "test_size = 0.4\n", + "seed = 25\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", + "random_state=seed)\n", + "model.fit(X_train, Y_train)\n", + "predicted = model.predict(X_test)\n", + "matrix = confusion_matrix(Y_test, predicted)\n", + "result = model.score(X_test, Y_test)\n", + "print(\"Accuracy: \", (result*100.0))\n", + "print(matrix)\n", + "print('MCC: ', matthews_corrcoef(model.predict(X_test),Y_test)) \n", + "model.fit(X,Y)\n", + "kj_resultsg8=model.predict(test_data)\n", + "\n", + "\n", + "#### results \n", + "\n", + "df = pd.DataFrame(kj_resultsg8)\n", + "df.columns = ['CLASS']\n", + "df.index.name = 'Index'\n", + "df['CLASS']=df['CLASS'].map({0.0:False,1.0:True})\n", + "print(df)\n", + "#X=test_amp.iloc[:,0:5]\n", + "#=test_amp.iloc[:,5]\n", + "df.to_csv(\"kjg8.csv\")\n", + "df[\"CLASS\"].unique()\n", + "print(df.groupby(\"CLASS\").size()[0].sum())\n", + "print(df.groupby(\"CLASS\").size()[1].sum())\n", + "df['CLASS'].value_counts()\n", + "\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 93.33881578947368\n", + "[[578 37]\n", + " [ 44 557]]\n", + "MCC: 0.866798468739703\n", + " CLASS\n", + "Index \n", + "0 True\n", + "1 True\n", + "2 True\n", + "3 True\n", + "4 False\n", + "... ...\n", + "753 False\n", + "754 False\n", + "755 False\n", + "756 False\n", + "757 False\n", + "\n", + "[758 rows x 1 columns]\n", + "370\n", + "388\n" + ] + }, + { + "data": { + "text/plain": [ + "True 388\n", + "False 370\n", + "Name: CLASS, dtype: int64" + ] + }, + "execution_count": 56, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "amp_train = pd.read_csv(\"/media/jupiter/Marina/MASTERS-SECOND-SEMESTER/BIG-BIO-DATA/assignment/AMP_TrainSet.csv\", header=0, sep=\",\")\n", + "test_data=pd.read_csv(\"/media/jupiter/Marina/MASTERS-SECOND-SEMESTER/BIG-BIO-DATA/assignment/Test.csv\", header=0, sep=\",\")\n", + "\n", + "#selecting out features with low variance\n", + "#from sklearn.feature_selection import VarianceThreshold\n", + "#sel = VarianceThreshold(threshold=(.8 * (1 - .8)))\n", + "#k=sel.fit_transform(amp_train)\n", + "#names=amp_train.columns[sel.get_support(indices=True)]\n", + "#print(k.shape)\n", + "#amp_train2=pd.DataFrame(k,columns=names)\n", + "#print(amp_train2)\n", + "\n", + "#n=sel.fit_transform(test_data)\n", + "#names2=test_data.columns[sel.get_support(indices=True)]\n", + "#test_data=pd.DataFrame(n,columns=names2)\n", + "#test_data2=test_data.values\n", + "\n", + "#print(test_data)\n", + "\n", + "### data \n", + "test_amp =amp_train.values\n", + "X=test_amp[:,0:11]\n", + "Y=test_amp[:,11]\n", + "\n", + "\n", + "\n", + "\n", + "#model\n", + "model=GaussianNB()\n", + "from sklearn.metrics import matthews_corrcoef\n", + "test_size = 0.4\n", + "seed = 25\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", + "random_state=seed)\n", + "model.fit(X_train, Y_train)\n", + "predicted = model.predict(X_test)\n", + "matrix = confusion_matrix(Y_test, predicted)\n", + "result = model.score(X_test, Y_test)\n", + "print(\"Accuracy: \", (result*100.0))\n", + "print(matrix)\n", + "print('MCC: ', matthews_corrcoef(model.predict(X_test),Y_test)) \n", + "model.fit(X,Y)\n", + "kj_resultsg12=model.predict(test_data)\n", + "\n", + "\n", + "#### results \n", + "\n", + "df = pd.DataFrame(kj_resultsg2)\n", + "df.columns = ['CLASS']\n", + "df.index.name = 'Index'\n", + "df['CLASS']=df['CLASS'].map({0.0:False,1.0:True})\n", + "print(df)\n", + "#X=test_amp.iloc[:,0:5]\n", + "#=test_amp.iloc[:,5]\n", + "df.to_csv(\"kjg11.csv\")\n", + "df[\"CLASS\"].unique()\n", + "print(df.groupby(\"CLASS\").size()[0].sum())\n", + "print(df.groupby(\"CLASS\").size()[1].sum())\n", + "df['CLASS'].value_counts()\n", + "\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Linear Discriminant Analysis" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "model=LinearDiscriminantAnalysis()\n", + "folds=10\n", + "kfold = KFold(n_splits=folds, random_state=7, shuffle=True,)\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print((\"Accuracy: %.3f%% (%.3f%%)\") % (results.mean()*100.0, results.std()*100.0))\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Support Vector Machines" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 91.013% (1.817%)\n" + ] + } + ], + "source": [ + "model=SVC()\n", + "folds=10\n", + "kfold = KFold(n_splits=folds, random_state=7, shuffle=True,)\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print((\"Accuracy: %.3f%% (%.3f%%)\") % (results.mean()*100.0, results.std()*100.0))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "celltoolbar": "Tags", + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.4" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} From 42654887b4921aabc3d1e9304e7f493281c2e9b8 Mon Sep 17 00:00:00 2001 From: Tendo1434 <58722184+Tendo1434@users.noreply.github.com> Date: Thu, 12 Mar 2020 16:01:39 -0400 Subject: [PATCH 20/29] Add files via upload --- Assignment Colab/nsangi-olga-tendo.ipynb | 1016 +++++++++++----------- 1 file changed, 530 insertions(+), 486 deletions(-) diff --git a/Assignment Colab/nsangi-olga-tendo.ipynb b/Assignment Colab/nsangi-olga-tendo.ipynb index 2d52262..6a01977 100644 --- a/Assignment Colab/nsangi-olga-tendo.ipynb +++ b/Assignment Colab/nsangi-olga-tendo.ipynb @@ -4,8 +4,17 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "
\n", - " Please look out for these cells for corrections." + "# **ACE Class competition**\n", + "#### By Nsangi Olga Tendo\n", + "## Machine Learning Process:\n", + "#### 1. Have a peek of raw data\n", + "#### 2. Review of dimensions of thedataset.\n", + "#### 3. Review of attribues in the data set\n", + "#### 4. Review the data types of attributes in your data.\n", + "#### 5. Review of missing data(NAs)\n", + "#### 6. Summary of data using descriptive statistics.\n", + "#### 7. Understand the relationships in your data using correlations.\n", + "#### 8. Review the skew of the distributions of each attribute." ] }, { @@ -52,7 +61,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Naming the Training and test dataset using." + "#### Naming the Training and test dataset using." ] }, { @@ -72,7 +81,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Confirming that the data has been read in and assigned to variables Train and Test" + "#### Confirming that the data has been read in and assigned to variables Train and Test" ] }, { @@ -321,18 +330,8 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Dimensions of the data train set\n", - "### Checking for the number of rows and columns in the data sets\n", - "\n", - "
\n", - " \n", - " ## ??\n", - " \n", - " When you see these: \n", - " - I want to know if you understand the concept\n", - " - Why are you applying the concept\n", - " - What did you learn?\n", - " - I want to see that you know what you are doing." + "#### Dimensions of the train and test data set\n", + "#### This helps in knowing the size of your data set and also give an intiution on what algorithms you could use incase the size is big or small." ] }, { @@ -343,7 +342,7 @@ { "data": { "text/plain": [ - "(3038, 12)" + "((3038, 12), (758, 11))" ] }, "execution_count": 4, @@ -352,14 +351,14 @@ } ], "source": [ - "Train.shape" + "Train.shape, Test.shape" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Establishing the attributes in the train data set" + "#### Establishing the attributes in the train and test data set" ] }, { @@ -370,11 +369,16 @@ { "data": { "text/plain": [ - "Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", - " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", - " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", - " 'CLASS'],\n", - " dtype='object')" + "(Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", + " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", + " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", + " 'CLASS'],\n", + " dtype='object'),\n", + " Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", + " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", + " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112',\n", + " 'CT_RACS820104'],\n", + " dtype='object'))" ] }, "execution_count": 5, @@ -383,19 +387,14 @@ } ], "source": [ - "Train.columns" + "Train.columns, Test.columns" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Establishing the data types for each attribute in the train data set. This helps in finding out which column has data types like strings that may need to be converted to foating points or integers to represent categorical or ordinal values. This can be done using df.dtype method or the df.info() method as shown in the two cells below, tho the df.info() is more informative.\n", - "\n", - "
\n", - " \n", - " Why is everything so big? \n", - "

like this?" + "#### Establishing the data types for each attribute in the train data set. This helps in finding out which columns have data types like strings that may need to be converted to foating points or integers to represent categorical or ordinal values since most machine learning algorithms take in integers or floats for inputs. This can be done using df.dtype method or the df.info() method as shown in the two cells below, tho the df.info() is more informative as its also tells the total number of instances for each column." ] }, { @@ -406,19 +405,31 @@ { "data": { "text/plain": [ - "FULL_Charge float64\n", - "FULL_AcidicMolPerc float64\n", - "FULL_AURR980107 float64\n", - "FULL_DAYM780201 float64\n", - "FULL_GEOR030101 float64\n", - "FULL_OOBM850104 float64\n", - "NT_EFC195 int64\n", - "AS_MeanAmphiMoment float64\n", - "AS_DAYM780201 float64\n", - "AS_FUKS010112 float64\n", - "CT_RACS820104 float64\n", - "CLASS int64\n", - "dtype: object" + "(FULL_Charge float64\n", + " FULL_AcidicMolPerc float64\n", + " FULL_AURR980107 float64\n", + " FULL_DAYM780201 float64\n", + " FULL_GEOR030101 float64\n", + " FULL_OOBM850104 float64\n", + " NT_EFC195 int64\n", + " AS_MeanAmphiMoment float64\n", + " AS_DAYM780201 float64\n", + " AS_FUKS010112 float64\n", + " CT_RACS820104 float64\n", + " CLASS int64\n", + " dtype: object,\n", + " FULL_Charge float64\n", + " FULL_AcidicMolPerc float64\n", + " FULL_AURR980107 float64\n", + " FULL_DAYM780201 float64\n", + " FULL_GEOR030101 float64\n", + " FULL_OOBM850104 float64\n", + " NT_EFC195 int64\n", + " AS_MeanAmphiMoment float64\n", + " AS_DAYM780201 float64\n", + " AS_FUKS010112 float64\n", + " CT_RACS820104 float64\n", + " dtype: object)" ] }, "execution_count": 6, @@ -427,7 +438,7 @@ } ], "source": [ - "Train.dtypes" + "Train.dtypes, Test.dtypes" ] }, { @@ -467,8 +478,8 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Statistical summary of the data in each column.\n", - "### This helps understand the distribution of each column as this method returns values like percentiles,standard deviation, minimum and maximum values of each attribute. This way you can also find out if you have negative values in any attribute. This also helps in understanding the scales at which each attribute is at." + "#### Descriptive statistics summary of the data in each column.\n", + "#### This includes measures of central tendencies like teh mean, median and measures of spread like standard, variance, range and interquatile range. The smallest and largest values of each column are also returned. This helps in understanding the distribution of data in each column. This way you can also find out if you have negative values in any attribute. This also helps in understanding the scales at which each attribute is at." ] }, { @@ -681,22 +692,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### From the values above, there are no missing values since all counts in each column is equal. We can also observe that there are negative values in some attributes have a minimum values in negatives.\n", - "\n", - "
\n", - " \n", - " ## ??" + "#### From the values above, there are no missing values since all counts in each column is equal. We can also observe that there are negative values in some attributes have a minimum values in negatives." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Since this is a classification problem, its important to check out the propotions of the values in the class to be predicted as its possible one class may have more values as compared to the others.\n", - "\n", - "
\n", - " \n", - " ## ??" + "#### Since this is a classification problem, its important to check out the propotions of the values in the class to be predicted as its possible one class may have more values as compared to the others. Incases where one class is higher than another class we could employe methods likes smote to over sample the least represented class so as to have an un biased algorithm." ] }, { @@ -764,18 +767,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### From above, the entries in the class attribute are equal." + "#### From above, the entries in the class attribute are equal." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Establishing if there are any missing values in the attributes of the data set. This helps to give an insight on how to handle the missing values, whether to remove rows that have missing values or establishing a method like the mean,median ect to impute the NAs. \n", - "\n", - "
\n", - " \n", - " Good explanation." + "#### Establishing if there are any missing values in the attributes of the data set. This helps to give an insight on how to handle the missing values, whether to remove rows that have missing values or establishing a method like the mean,median ect to impute the NAs. " ] }, { @@ -814,8 +813,8 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Correlation between attributes.\n", - "## This is done to establish the relationship between variables and how they may change or may not change each other. The pearson's correlation method is going to be used since it assumes normal distribution on attributes involved. A value of 0 shows no correlation between the attributes, while a correlation of -1 or 1 shows full negative or positive correlation between variables." + "#### Correlation between attributes.\n", + "#### This is done to establish the relationship between variables and how they may change or may not change each other. The pearson's correlation method is going to be used since it assumes normal distribution on attributes involved. A value of 0 shows no correlation between the attributes, while a correlation of -1 or 1 shows full negative or positive correlation between variables." ] }, { @@ -1114,7 +1113,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## From the summary above, AS_DAYM780201 and FULL_DAYM780201 are the strongest positively correlated with a correlation of 0.894191 while FULL_AcidicMolPerc and FULL_Charge are the strongest negatively correlated attributes. This correlation can further be observed by plotting a heat map using seaborn to show the correlation of attributes with each other as shown below" + "#### From the summary above, AS_DAYM780201 and FULL_DAYM780201 are the strongest positively correlated with a correlation of 0.894191 while FULL_AcidicMolPerc and FULL_Charge are the strongest negatively correlated attributes. This correlation can further be observed by plotting a heat map using seaborn to show the correlation of attributes with each other as shown below" ] }, { @@ -1125,7 +1124,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 13, @@ -1154,19 +1153,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Using visualisation to understand the data at hand. Histograms, Density plots and Box and whisker plots are some of the plots used to understand the attribute distribution.\n", - "## Histograms were used.\n", - "\n", - "
\n", - " \n", - " ## ??" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Using Histograms" + "#### Using visualisation to understand the data at hand. Histograms, Density plots and Box and whisker plots are some of the plots used to understand the attribute distribution. Histograms were used. They're used to summarize discrete or continuous data by showing the number(frequency) of data points that fall within a specified range of values. Histograms graphically show center) of the data, spread (i.e., the scale) of the data, skewness of the data, presence of outliers and presence of multiple modes in the data" ] }, { @@ -1192,23 +1179,25 @@ "plt.show()" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## From the histograms above, we can observe that attributes AS_MeanAmphiMoment, AS_DAYM780201, AS_FUKS010112, FULL_DAYM780201, FULL_GEOR030101, FULL_AURR980107,FULL_CHARGE have a normal. We can also tell from these plots that attribute CT_RACS820104 and FULL_AcidicMolPerc are skewed to the right. We can also tell that attributes NT_EFC195 and CLASS are categorical attributes. This can also be observed using density plots as shown below.\n", - "\n", - "
\n", - " \n", - " ## ??" + "#### From the histograms above, we can observe that attributes AS_MeanAmphiMoment, AS_DAYM780201, AS_FUKS010112, FULL_DAYM780201, FULL_GEOR030101, FULL_AURR980107,FULL_CHARGE have a normal. We can also tell from these plots that attribute CT_RACS820104 and FULL_AcidicMolPerc are skewed to the right. We can also tell that attributes NT_EFC195 and CLASS are categorical attributes. This can also be observed using density plots as shown below." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Using Density plots\n", - "### With the density plot, we can easily make comparisons between variables in each column because the plot is less cluttered." + "#### Using Density plots. Density plots are used to observe the distribution of a variable in a dataset. The peaks of a Density Plot help display where values are concentrated over the interval. Density plots give a more precise location and also gives a continuous distribution view. " ] }, { @@ -1248,12 +1237,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Checking for the skewness of the data. Since many machine learning algorithms assume normal distribution,this allows one to know what attributes need to be corrected of skewness to improve the accuracy of the model. Skewness can be observed with bar plots of .skew().\n", - "\n", - "
\n", - " Good explanation.\n", - " \n", - " So what did you findout?" + "#### From the above plots, FULL_Charge, FULL_AURR980107, FULL_DAYM780201, FULL_GEOR030101, CT_RACS820104, FULL_OOBM850104, AS_FUKS010112, AS_DAYM780201 show a normal distribution of variables. CLASS and NT_EFC195 are categorical data CLASS having equal number of instances while NT_EFC195 has a category that has almost all instances. \tFULL_AcidicMolPerc and AS_MeanAmphiMoment have more than one peak meaning that the data points are distribute at 2 peak for FULL_AcidicMolPerc and 3 peaks for AS_MeanAmphiMoment\t" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Checking for the skewness of the data. Skewness is deviation from a normal distribution. The data may be skewed to the left or to the right of the normal distribution curve (bell shaped). Since many machine learning algorithms assume normal distribution,this allows one to know what attributes need to be corrected of skewness to improve the accuracy of the model. Skewness can be observed with bar plots of .skew()." ] }, { @@ -1264,7 +1255,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 16, @@ -1316,35 +1307,20 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Separating the train data set into output and input components" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [], - "source": [ - "A = Train.values\n", - "X = A[:, 0:11]\n", - "Y = A[:,11]" + "#### From the check above, attribute NT_EFC195 has skewed data and this could alter final results of the model. The data could be transformed or the attributed drop(not used in building a classifier." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Spot checking classification algorithms since its a classification problem at hand.\n", - "### This is done to know which algorithm is best suited for the problem at hand. Two linear machine learning algorithms(Logistic regression and Linear discriminant analysis) and four non-linear machine learning algorithm were used(k-nearest neighbors, naive bayes, support vector machines and classific regression tress. \n", - "\n", - "
\n", - " \n", - " ## Less than 10 algorithms!!!" + "#### Spot checking classification algorithms since its a classification problem at hand.\n", + "#### This is done to know which algorithm is best suited for the problem at hand. Two linear machine learning algorithms(Logistic regression and Linear discriminant analysis) and four non-linear machine learning algorithm were used(k-nearest neighbors, naive bayes, support vector machines and classific regression tress. " ] }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 18, "metadata": {}, "outputs": [ { @@ -1356,12 +1332,13 @@ "('KNN', 0.8690586462107053)\n", "('CART', 1.0)\n", "('NB', 0.8407203694376205)\n", - "('SVM', 0.8187103751493263)\n" + "('SVM', 0.8187103751493263)\n", + "('ABC', 0.8848771929251248)\n" ] }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -1373,7 +1350,6 @@ } ], "source": [ - "from pandas import read_csv\n", "from matplotlib import pyplot\n", "from sklearn.model_selection import KFold\n", "from sklearn.model_selection import cross_val_score\n", @@ -1383,10 +1359,11 @@ "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", "from sklearn.naive_bayes import GaussianNB\n", "from sklearn.svm import SVC\n", + "from sklearn.ensemble import AdaBoostClassifier\n", "from sklearn.metrics import matthews_corrcoef\n", "\n", "#split the dataset \n", - "#A = Train.values\n", + "A = Train.values\n", "# Separating A into output and input components\n", "X = A[:, 0:11]\n", "Y = A[:, 11]\n", @@ -1398,6 +1375,8 @@ "models.append(('CART', DecisionTreeClassifier()))\n", "models.append(('NB', GaussianNB()))\n", "models.append(('SVM', SVC()))\n", + "models.append(('ABC', AdaBoostClassifier()))\n", + "\n", "#print(models)\n", "\n", "# evaluate each model in turn\n", @@ -1429,20 +1408,20 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### From these results, it would suggest that both DecisionTreeClassifier, KNeighborsClassifier and GaussianNB are worthy of further study on this problem." + "#### From these results, it would suggest that both DecisionTreeClassifier, KNeighborsClassifier and GaussianNB are worthy of further study on this problem." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Data Preparation.\n", - "### This is important because this finds a way to best expose the structure of the problem to machine learning algorithim intended to be used. Since the data has attributes of varying scales, its important to use one of the methods for data preparation like rescaling, standardization, normalization or binarization for better prediction. Here, rescaling is used to have all the attribute on the same scale." + "#### **Data Preparation.**\n", + "#### This is important because this finds a way to best expose the structure of the problem to machine learning algorithim intended to be used. Since the data has attributes of varying scales, its important to use one of the methods for data preparation like rescaling, standardization, normalization or binarization for better prediction. Here, rescaling is used to have all the attribute on the same scale." ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 19, "metadata": {}, "outputs": [ { @@ -1477,13 +1456,13 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Standardization\n", - "### It is a useful technique to transform attributes with a Gaussian distribution and differing means and standard deviations to a standard Gaussian distribution with a mean of 0 and a standard deviation of 1" + "#### Standardization\n", + "#### It is a useful technique to transform attributes with a Gaussian distribution and differing means and standard deviations to a standard Gaussian distribution with a mean of 0 and a standard deviation of 1" ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 20, "metadata": {}, "outputs": [ { @@ -1521,13 +1500,13 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Feature selection\n", - "### Statistical tests can be used to select those features that have the strongest relationship with the output variable. Feature selection is done on non transformed data using select k best using he univariate statistic F was used since it can work best with data containg negative values as opposed to chi2 that doesnt take in negative values." + "#### **Feature selection**\n", + "#### Statistical tests can be used to select those features that have the strongest relationship with the output variable. Feature selection is done on non transformed data using select k best using he univariate statistic F was used since it can work best with data containg negative values as opposed to chi2 that doesnt take in negative values." ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 21, "metadata": {}, "outputs": [ { @@ -1605,6 +1584,18 @@ " 234.274197\n", " 5.329249e-51\n", " \n", + " \n", + " 6\n", + " NT_EFC195\n", + " 221.390853\n", + " 2.189203e-48\n", + " \n", + " \n", + " 4\n", + " FULL_GEOR030101\n", + " 220.967065\n", + " 2.669597e-48\n", + " \n", " \n", "\n", "
" @@ -1618,10 +1609,12 @@ "0 FULL_Charge 1214.902838 3.404241e-224\n", "5 FULL_OOBM850104 785.124798 7.441087e-154\n", "8 AS_DAYM780201 717.317408 4.911002e-142\n", - "10 CT_RACS820104 234.274197 5.329249e-51" + "10 CT_RACS820104 234.274197 5.329249e-51\n", + "6 NT_EFC195 221.390853 2.189203e-48\n", + "4 FULL_GEOR030101 220.967065 2.669597e-48" ] }, - "execution_count": 22, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } @@ -1629,40 +1622,43 @@ "source": [ "from sklearn.feature_selection import SelectKBest, f_classif\n", "from numpy import set_printoptions\n", - "\n", + "# Separating A into output and input components\n", + "A = Train.values\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", "#Feature Extraction\n", - "bestfeat = SelectKBest(score_func=f_classif, k=8)\n", - "fit = bestfeat.fit(X,Y)\n", + "bestfeat = SelectKBest(score_func=f_classif, k=10)\n", + "fit = bestfeat.fit(X,Y) #fitting f_classif test on predictors to get features that best predict\n", "\n", "set_printoptions(precision=3) # This sets the number of floating point output after rescaling the data\n", "selected_features = fit.transform(X)\n", - "\n", + "#Creating a dataframe to represent the order features selected starting from the best feature\n", "scores = pd.DataFrame(fit.scores_)\n", "pvalues = pd.DataFrame(fit.pvalues_)\n", "columns = pd.DataFrame(Train.columns[0:11])\n", "\n", - "selected_features = pd.concat([columns,scores, pvalues,], axis=1)\n", - "selected_features.columns = ['features', 'scores', 'pvalue']\n", - "selected_features.nlargest(8, \"scores\")" + "selected_features_dataframe = pd.concat([columns,scores, pvalues,], axis=1)\n", + "selected_features_dataframe.columns = ['features', 'scores', 'pvalue']\n", + "selected_features_dataframe.nlargest(10, \"scores\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### SelectKBest using the f statistic, gives scores to each attribute and takes the specified number of attributes with the highest scores. Attributes AS_MeanAmphiMoment, FULL_AcidicMolPerc, FULL_AURR980107, FULL_DAYM780201, FULL_Charge, FULL_OOBM850104, AS_DAYM780201 and CT_RACS820104 were the selected features." + "#### SelectKBest using the f statistic, gives scores to each attribute and takes the specified number of attributes with the highest scores. Attributes AS_MeanAmphiMoment, FULL_AcidicMolPerc, FULL_AURR980107, FULL_DAYM780201, FULL_Charge, FULL_OOBM850104, AS_DAYM780201 and CT_RACS820104 were the selected features." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Chi2 statistical test was used to since there were no negative values in the attributes after rescaling with the minmax scaler." + "#### Feature selection using SelectKBest, Chi2 statistical test since there are no negative values in the attributes after rescaling with the minmax scaler." ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 22, "metadata": {}, "outputs": [ { @@ -1740,23 +1736,37 @@ " 15.245249\n", " 9.441397e-05\n", " \n", + " \n", + " 10\n", + " CT_RACS820104\n", + " 15.146775\n", + " 9.946804e-05\n", + " \n", + " \n", + " 4\n", + " FULL_GEOR030101\n", + " 4.788691\n", + " 2.864719e-02\n", + " \n", " \n", "\n", "
" ], "text/plain": [ - " features scores pvalue\n", - "7 AS_MeanAmphiMoment 244.227728 4.708742e-55\n", - "6 NT_EFC195 188.197026 7.868482e-43\n", - "1 FULL_AcidicMolPerc 157.617513 3.751602e-36\n", - "2 FULL_AURR980107 54.231448 1.782118e-13\n", - "3 FULL_DAYM780201 37.311780 1.006747e-09\n", - "8 AS_DAYM780201 26.156224 3.148806e-07\n", - "5 FULL_OOBM850104 16.231433 5.605627e-05\n", - "0 FULL_Charge 15.245249 9.441397e-05" + " features scores pvalue\n", + "7 AS_MeanAmphiMoment 244.227728 4.708742e-55\n", + "6 NT_EFC195 188.197026 7.868482e-43\n", + "1 FULL_AcidicMolPerc 157.617513 3.751602e-36\n", + "2 FULL_AURR980107 54.231448 1.782118e-13\n", + "3 FULL_DAYM780201 37.311780 1.006747e-09\n", + "8 AS_DAYM780201 26.156224 3.148806e-07\n", + "5 FULL_OOBM850104 16.231433 5.605627e-05\n", + "0 FULL_Charge 15.245249 9.441397e-05\n", + "10 CT_RACS820104 15.146775 9.946804e-05\n", + "4 FULL_GEOR030101 4.788691 2.864719e-02" ] }, - "execution_count": 23, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -1766,328 +1776,186 @@ "from sklearn.feature_selection import chi2\n", "\n", "#Feature Extraction\n", - "test = SelectKBest(score_func=chi2, k=8)\n", - "fit = test.fit(rescaledX,Y)\n", + "test = SelectKBest(score_func=chi2, k=10)\n", + "fit = test.fit(rescaledX,Y) # fitting chi2 test on predictors to get features that best predict\n", "\n", "# Summary of scores \n", "set_printoptions(precision=3) # This sets the number of floating point output after rescaling the data\n", "#print(fit.scores_)\n", "selected_features1 = fit.transform(rescaledX)\n", - "\n", + "#Creating a dataframe to represent the order features selected starting from the best feature\n", "scores = pd.DataFrame(fit.scores_)\n", "pvalues = pd.DataFrame(fit.pvalues_)\n", "columns = pd.DataFrame(Train.columns[0:11])\n", "\n", - "selected_features1 = pd.concat([columns,scores, pvalues,], axis=1)\n", + "selected_features1 = pd.concat([columns,scores, pvalues], axis=1)\n", "selected_features1.columns = ['features', 'scores', 'pvalue']\n", - "selected_features1.nlargest(8, \"scores\")" + "selected_features1.nlargest(10, \"scores\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Feature selection using the recursive feature selection method with LG" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'rescaledX2' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mmodel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mLogisticRegression\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mrfe\u001b[0m\u001b[0;34m=\u001b[0m \u001b[0mRFE\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0mfit\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrfe\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrescaledX2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 6\u001b[0m \u001b[0mselectedfeaturesRFE\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrescaledX2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msupport_\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mNameError\u001b[0m: name 'rescaledX2' is not defined" - ] - } - ], - "source": [ - "from sklearn.feature_selection import RFE\n", - "from sklearn.linear_model import LogisticRegression\n", - "model = LogisticRegression()\n", - "rfe= RFE(model,5)\n", - "fit = rfe.fit(rescaledX2, Y)\n", - "selectedfeaturesRFE = rescaledX2[:, fit.support_]\n", - "\n", - "print(\"Num_Feature:\", fit.n_features_)\n", - "print(\"Selected Features:\", fit.support_)\n", - "print(\"Feature Ranking:\", fit.ranking_)" + "#### From the dataframe above, AS_MeanAmphiMoment has the highest score of 244.227728 followed by NT_EFC195, then FULL_AcidicMolPerc and like that till the last attribute in dataframe, FULL_GEOR030101 that has lowwest score of 4.788691." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Evaluating Machine learning Alogorithms\n", - "## K-fold Cross Validation\n", - "### Cross validation is an approach that you can use to estimate the performance of a machine learning algorithm with less variance than a single train-test set split. It works by splitting the dataset into k-parts (e.g. k = 5 or k = 10). Each split of the data is called a fold. The algorithm is trained on k1 folds with one held back and tested on the held back fold. This is repeated so that each fold of the dataset is given a chance to be the held back test set. The choice of k must allow the size of each test partition to be large enough to be a reasonable sample of the problem, whilst allowing enough repetitions of the train-test evaluation of the algorithm to provide a fair estimate of the algorithms performance on unseen data. For modest sized datasets in the thousands or tens of thousands of records, k values of 3, 5 and 10 are common. In the example below we use 10-fold cross validation." + "#### Feature selection using the recursive feature selection method with LogisticRegression - it works by recursively removing attributes and building a model on those attributes that remain. It uses the model accuracy to identify which attributes (and combination of attributes) contribute the most to predicting the target attribute" ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 23, "metadata": {}, "outputs": [ { - "ename": "NameError", - "evalue": "name 'selected_features_train' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mkfold\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mKFold\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn_splits\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnum_folds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrandom_state\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mseed\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mmodel11\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mLogisticRegression\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mmodel11\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mselected_features_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcross_val_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel11\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mselected_features\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcv\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkfold\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mNameError\u001b[0m: name 'selected_features_train' is not defined" - ] + "data": { + "text/html": [ + "
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Selected_FeaturesRFEFeature_Ranking
2FULL_AURR9801072
0FULL_Charge1
1FULL_AcidicMolPerc1
3FULL_DAYM7802011
4FULL_GEOR0301011
5FULL_OOBM8501041
6NT_EFC1951
7AS_MeanAmphiMoment1
8AS_DAYM7802011
9AS_FUKS0101121
\n", + "
" + ], + "text/plain": [ + " Selected_FeaturesRFE Feature_Ranking\n", + "2 FULL_AURR980107 2\n", + "0 FULL_Charge 1\n", + "1 FULL_AcidicMolPerc 1\n", + "3 FULL_DAYM780201 1\n", + "4 FULL_GEOR030101 1\n", + "5 FULL_OOBM850104 1\n", + "6 NT_EFC195 1\n", + "7 AS_MeanAmphiMoment 1\n", + "8 AS_DAYM780201 1\n", + "9 AS_FUKS010112 1" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "from sklearn.model_selection import KFold\n", - "from sklearn.model_selection import cross_val_score\n", + "from sklearn.feature_selection import RFE\n", "from sklearn.linear_model import LogisticRegression\n", + "model = LogisticRegression()\n", + "rfe= RFE(model,10)\n", + "fit = rfe.fit(standardizedX, Y) # fitting logistic regression on predictors to get features that best predict\n", + "selectedfeaturesRFE = standardizedX[:, fit.support_]\n", + "\n", + "#Creating a dataframe to represent the order features selected starting from the best feature\n", + "#Num_Features = pd.DataFrame(fit.n_features_)\n", + "Selected_FeaturesRFE = pd.DataFrame(fit.support_)\n", + "Feature_Ranking = pd.DataFrame(fit.ranking_)\n", + "columns = pd.DataFrame(Train.columns[0:11])\n", "\n", - "num_folds = 10\n", - "seed = 11\n", - "kfold = KFold(n_splits=num_folds, random_state=seed)\n", - "model11 = LogisticRegression()\n", - "model11.fit(selected_features_train, Y_train)\n", - "\n", - "results = cross_val_score(model11, selected_features, Y, cv=kfold)\n", - "Prediction = model11.predict(selected_features_train)\n", - "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", - "print(\"Accuracy:\", (results.mean()*100.0))\n", - "#Assigning the preditions of the model to variable AssignmentOutPut\n", - "AssignmentOutPut11 = model11.predict(Test.values) \n", - "#Converting AssignmentOutPut to a dataframe since its output is an array\n", - "AssignmentOutPut11 = pd.DataFrame(AssignmentOutPut11)\n", - "\n", - "AssignmentOutPut11.columns = ['Class'] # Naming the output column\n", - "AssignmentOutPut11.index.name = \"Index\" #Creating a column called index\n", - "AssignmentOutPut11['Class'] = AssignmentOutPut11['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", - "\n", - "#Printing the number of False and Trues\n", - "print(AssignmentOutPut11.groupby('Class').size()[0].sum())\n", - "print(AssignmentOutPut11.groupby('Class').size()[1].sum())\n", - "\n", - "AssignmentOutPut11.to_csv('AssignmentOutPut1.csv') # Writing AssignmentOutPut1 to a csv file" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'selected_features_train' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mkfold\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mKFold\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn_splits\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnum_folds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrandom_state\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mseed\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mmodel22\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mGaussianNB\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mmodel22\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mselected_features_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcross_val_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel22\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mselected_features\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcv\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkfold\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mNameError\u001b[0m: name 'selected_features_train' is not defined" - ] - } - ], - "source": [ - "from sklearn.model_selection import KFold\n", - "from sklearn.model_selection import cross_val_score\n", - "from sklearn.naive_bayes import GaussianNB\n", - "\n", - "num_folds = 10\n", - "seed = 22\n", - "kfold = KFold(n_splits=num_folds, random_state=seed)\n", - "model22 = GaussianNB()\n", - "model22.fit(selected_features_train, Y_train)\n", - "\n", - "results = cross_val_score(model22, selected_features, Y, cv=kfold)\n", - "Prediction = model22.predict(selected_features_train)\n", - "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", - "print(\"Accuracy:\", (results.mean()*100.0))\n", - "\n", - "#Assigning the preditions of the model to variable AssignmentOutPut\n", - "AssignmentOutPut22 = model22.predict(Test.values) \n", - "#Converting AssignmentOutPut to a dataframe since its output is an array\n", - "AssignmentOutPut22 = pd.DataFrame(AssignmentOutPut22)\n", - "\n", - "AssignmentOutPut22.columns = ['Class'] # Naming the output column\n", - "AssignmentOutPut22.index.name = \"Index\" #Creating a column called index\n", - "AssignmentOutPut22['Class'] = AssignmentOutPut22['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", - "\n", - "#Printing the number of False and Trues\n", - "print(AssignmentOutPut22.groupby('Class').size()[0].sum())\n", - "print(AssignmentOutPut22.groupby('Class').size()[1].sum())\n", - "\n", - "AssignmentOutPut22.to_csv('AssignmentOutPut22.csv') # Writing AssignmentOutPut1 to a csv file" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'selected_features_train' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mkfold\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mKFold\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn_splits\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnum_folds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrandom_state\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mseed\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mmodel33\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mKNeighborsClassifier\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mmodel33\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mselected_features_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcross_val_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel33\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mselected_features\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcv\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkfold\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mNameError\u001b[0m: name 'selected_features_train' is not defined" - ] - } - ], - "source": [ - "from sklearn.model_selection import KFold\n", - "from sklearn.model_selection import cross_val_score\n", - "from sklearn.neighbors import KNeighborsClassifier\n", - "\n", - "num_folds = 10\n", - "seed = 33\n", - "kfold = KFold(n_splits=num_folds, random_state=seed)\n", - "model33 = KNeighborsClassifier()\n", - "model33.fit(selected_features_train, Y_train)\n", - "\n", - "results = cross_val_score(model33, selected_features, Y, cv=kfold)\n", - "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", - "print(\"Accuracy:\", (results.mean()*100.0))\n", - "\n", - "#Assigning the preditions of the model to variable AssignmentOutPut\n", - "AssignmentOutPut33 = model33.predict(Test.values) \n", - "#Converting AssignmentOutPut to a dataframe since its output is an array\n", - "AssignmentOutPut33 = pd.DataFrame(AssignmentOutPut33)\n", - "\n", - "AssignmentOutPut33.columns = ['Class'] # Naming the output column\n", - "AssignmentOutPut33.index.name = \"Index\" #Creating a column called index\n", - "AssignmentOutPut33['Class'] = AssignmentOutPut33['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", - "\n", - "#Printing the number of False and Trues\n", - "print(AssignmentOutPut33.groupby('Class').size()[0].sum())\n", - "print(AssignmentOutPut33.groupby('Class').size()[1].sum())\n", - "\n", - "AssignmentOutPut33.to_csv('AssignmentOutPut33.csv') # Writing AssignmentOutPut1 to a csv file" + "selected_features2 = pd.concat([columns, Feature_Ranking], axis=1)\n", + "selected_features2.columns = ['Selected_FeaturesRFE', 'Feature_Ranking']\n", + "selected_features2.nlargest(10, \"Feature_Ranking\")" ] }, { - "cell_type": "code", - "execution_count": 28, + "cell_type": "markdown", "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'selected_features_train' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mkfold\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mKFold\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn_splits\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnum_folds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrandom_state\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mseed\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mmodel44\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mDecisionTreeClassifier\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mmodel44\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mselected_features_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcross_val_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel44\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mselected_features\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcv\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkfold\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mNameError\u001b[0m: name 'selected_features_train' is not defined" - ] - } - ], "source": [ - "from sklearn.model_selection import KFold\n", - "from sklearn.model_selection import cross_val_score\n", - "from sklearn.tree import DecisionTreeClassifier\n", - "\n", - "num_folds = 10\n", - "seed = 44\n", - "kfold = KFold(n_splits=num_folds, random_state=seed)\n", - "model44 = DecisionTreeClassifier()\n", - "model44.fit(selected_features_train, Y_train)\n", - "\n", - "results = cross_val_score(model44, selected_features, Y, cv=kfold)\n", - "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", - "print(\"Accuracy:\", (results.mean()*100.0))\n", - "\n", - "#Assigning the preditions of the model to variable AssignmentOutPut\n", - "AssignmentOutPut44 = model44.predict(Test.values) \n", - "#Converting AssignmentOutPut to a dataframe since its output is an array\n", - "AssignmentOutPut44 = pd.DataFrame(AssignmentOutPut44)\n", - "\n", - "AssignmentOutPut44.columns = ['Class'] # Naming the output column\n", - "AssignmentOutPut44.index.name = \"Index\" #Creating a column called index\n", - "AssignmentOutPut44['Class'] = AssignmentOutPut44['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", - "\n", - "#Printing the number of False and Trues\n", - "print(AssignmentOutPut44.groupby('Class').size()[0].sum())\n", - "print(AssignmentOutPut44.groupby('Class').size()[1].sum())\n", - "\n", - "AssignmentOutPut44.to_csv('AssignmentOutPut44.csv') # Writing AssignmentOutPut1 to a csv file" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'selected_features_train' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mkfold\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mKFold\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn_splits\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnum_folds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrandom_state\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mseed\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mmodel55\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mSVC\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mmodel55\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mselected_features_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY_train\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcross_val_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel55\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mselected_features\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mY\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcv\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkfold\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mNameError\u001b[0m: name 'selected_features_train' is not defined" - ] - } - ], - "source": [ - "from sklearn.model_selection import KFold\n", - "from sklearn.model_selection import cross_val_score\n", - "from sklearn.svm import SVC\n", - "\n", - "num_folds = 55\n", - "seed = 6\n", - "kfold = KFold(n_splits=num_folds, random_state=seed)\n", - "model55 = SVC()\n", - "model55.fit(selected_features_train, Y_train)\n", - "\n", - "results = cross_val_score(model55, selected_features, Y, cv=kfold)\n", - "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", - "print(\"Accuracy:\", (results.mean()*100.0))\n", - "\n", - "#Assigning the preditions of the model to variable AssignmentOutPut\n", - "AssignmentOutPut55 = model55.predict(Test.values) \n", - "#Converting AssignmentOutPut to a dataframe since its output is an array\n", - "AssignmentOutPut55 = pd.DataFrame(AssignmentOutPut55)\n", - "\n", - "AssignmentOutPut55.columns = ['Class'] # Naming the output column\n", - "AssignmentOutPut55.index.name = \"Index\" #Creating a column called index\n", - "AssignmentOutPut55['Class'] = AssignmentOutPut55['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", - "\n", - "#Printing the number of False and Trues\n", - "print(AssignmentOutPut55.groupby('Class').size()[0].sum())\n", - "print(AssignmentOutPut55.groupby('Class').size()[1].sum())\n", - "\n", - "AssignmentOutPut55.to_csv('AssignmentOutPut55.csv') # Writing AssignmentOutPut1 to a csv file" + "#### From the dataframe above, FULL_AURR980107 has the highest rank of 2 followed by FULL_Charge, then FULL_AcidicMolPerc and like that till the last attribute in dataframe, AS_FUKS010112." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Evaluating Machine learning Alogorithms\n", - "## Split into Train and Test set" + "#### **Evaluating Machine learning Alogorithms** - the best way to evaluate the performance of an algorithm would be to make predictions for new data to which you already know the answers. Evaluation shoud be done on data that is not used to train the algorithm. The evaluation is an estimate that we can use to talk about how well we think the algorithm may actually do in practice.\n", + "#### **Split into Train and Test set**\n", + "#### It's the simplest method that we can use to evaluate the performance of a machine learning algorithm is to use dierent training and testing datasets. The train dataset is split it into two parts. The algorithm is trained on one part and predictions are made on the second part and evaluate the predictions against the expected results. The size of the split can depend on the size of your dataset, although it is common to use 67% of the data for training and the remaining 33% for testing. This algorithm evaluation technique is very fast. It is ideal for large datasets (millions of records) where there is strong evidence that both splits of the data are representative of the underlying problem. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Non rescaled data" + "#### **LogisticRegression** - Logistic regression is basically a supervised classification algorithm. Supervised learning is when a model learns from data that is already labeled. A supervised learning model takes in a set of input objects and output values. The model then trains on that data to learn how to map the inputs to the desired output so it can learn to make predictions on unseen data. In a classification problem, the target variable(or output), y, can take only discrete values for given set of features(or inputs), X. Logistic regression is a classification algorithm used to assign observations to a discrete set of classes. It is based on the concept of probability." ] }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 24, "metadata": {}, "outputs": [ { @@ -2121,9 +1989,8 @@ "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", "print(\"Accuracy:\", (result*100.0))\n", "\n", - "#Assigning the preditions of the model to variable AssignmentOutPut\n", - "AssignmentOutPut1 = my_model1.predict(Test.values) \n", - "#Converting AssignmentOutPut to a dataframe since its output is an array\n", + "#Assigning the preditions of the model to variable AssignmentOutPut1\n", + "AssignmentOutPut1 = my_model1.predict(Test.values) #Converting AssignmentOutPut1 to a dataframe since its output is an array\n", "AssignmentOutPut1 = pd.DataFrame(AssignmentOutPut1)\n", "\n", "AssignmentOutPut1.columns = ['Class'] # Naming the output column\n", @@ -2137,9 +2004,16 @@ "AssignmentOutPut1.to_csv('AssignmentOutPut1.csv') # Writing AssignmentOutPut1 to a csv file" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### **KNeighborsClassifier** - k-Nearest-Neighbors (k-NN) is a supervised machine learning model. KNN models work by taking a data point and looking at the ‘k’ closest labeled data points. The data point is then assigned the label of the majority of the ‘k’ closest points. For example, if k = 5, and 3 of points are ‘green’ and 2 are ‘red’, then the data point in question would be labeled ‘green’, since ‘green’ is the majority " + ] + }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 25, "metadata": {}, "outputs": [ { @@ -2173,12 +2047,11 @@ "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", "print(\"Accuracy:\", (result*100.0))\n", "\n", - "#Assigning the preditions of the model to variable AssignmentOutPut\n", + "#Assigning the preditions of the model to variable AssignmentOutPut2\n", "AssignmentOutPut2 = my_model2.predict(Test.values) \n", "#Converting AssignmentOutPut to a dataframe since its output is an array\n", - "AssignmentOutPut2 = pd.DataFrame(AssignmentOutPut2)\n", - "# Converting AssignmentOutPut to a dataframe since its output is an array\n", - "AssignmentOutPut2.columns = ['Class'] # Naming the out\n", + "AssignmentOutPut2 = pd.DataFrame(AssignmentOutPut2)# Converting AssignmentOutPut2 to a dataframe since its output is an array\n", + "AssignmentOutPut2.columns = ['Class'] # Naming the out put column\n", "AssignmentOutPut2.index.name = \"Index\" #Creating a column called index\n", "AssignmentOutPut2['Class'] = AssignmentOutPut2['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", "\n", @@ -2186,12 +2059,19 @@ "print(AssignmentOutPut2.groupby('Class').size()[0].sum())\n", "print(AssignmentOutPut2.groupby('Class').size()[1].sum())\n", "\n", - "AssignmentOutPut2.to_csv('AssignmentOutPut2.csv') # Writing AssignmentOutPut1 to a csv file" + "AssignmentOutPut2.to_csv('AssignmentOutPut2.csv') # Writing AssignmentOutPut2 to a csv file" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### **DecisionTreeClassifier** - its also a supervised learning algorithm that identifies ways to split a data set based on different conditions." ] }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 26, "metadata": {}, "outputs": [ { @@ -2199,9 +2079,9 @@ "output_type": "stream", "text": [ "MCC: 1.0\n", - "Accuracy: 90.72781655034895\n", - "387\n", - "371\n" + "Accuracy: 89.43170488534396\n", + "390\n", + "368\n" ] } ], @@ -2226,9 +2106,8 @@ "print(\"Accuracy:\", (result*100.0))\n", "AssignmentOutPut3 = my_model3.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut\n", "\n", - "AssignmentOutPut3 = pd.DataFrame(AssignmentOutPut3)\n", - "# Converting AssignmentOutPut to a dataframe since its output is an array\n", - "AssignmentOutPut3.columns = ['Class'] # Naming the out\n", + "AssignmentOutPut3 = pd.DataFrame(AssignmentOutPut3)# Converting AssignmentOutPut3 to a dataframe since its output is an array\n", + "AssignmentOutPut3.columns = ['Class'] # Naming the out put column\n", "AssignmentOutPut3.index.name = \"Index\" #Creating a column called index\n", "AssignmentOutPut3['Class'] = AssignmentOutPut3['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", "\n", @@ -2236,12 +2115,19 @@ "print(AssignmentOutPut3.groupby('Class').size()[0].sum())\n", "print(AssignmentOutPut3.groupby('Class').size()[1].sum())\n", "\n", - "AssignmentOutPut1.to_csv('AssignmentOutPut3.csv') # Writing AssignmentOutPut1 to a csv file\n" + "AssignmentOutPut1.to_csv('AssignmentOutPut3.csv') # Writing AssignmentOutPut3 to a csv file\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### **GaussianNB** - its a classification algorithm for binary (two-class) and multi-class classification problems. Naive Bayes calculates the probability of each class and the conditional probability of each class given each input value. These probabilities are estimated for new data and multiplied together, assuming that they are all independent" ] }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 27, "metadata": {}, "outputs": [ { @@ -2275,33 +2161,39 @@ "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", "print(\"Accuracy:\", (result*100.0))\n", "\n", - "AssignmentOutPut4 = my_model4.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut\n", + "AssignmentOutPut4 = my_model4.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut4\n", "\n", - "AssignmentOutPut4 = pd.DataFrame(AssignmentOutPut4)\n", - "# Converting AssignmentOutPut to a dataframe since its output is an array\n", - "AssignmentOutPut4.columns = ['Class'] # Naming the out\n", + "AssignmentOutPut4 = pd.DataFrame(AssignmentOutPut4)# Converting AssignmentOutPut4 to a dataframe since its output is an array\n", + "AssignmentOutPut4.columns = ['Class'] # Naming the out put column\n", "AssignmentOutPut4.index.name = \"Index\" #Creating a column called index\n", "AssignmentOutPut4['Class'] = AssignmentOutPut4['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", "\n", - "AssignmentOutPut4.to_csv('AssignmentOutPut4.csv') # Writing AssignmentOutPut1 to a csv file\n", + "AssignmentOutPut4.to_csv('AssignmentOutPut4.csv') # Writing AssignmentOutPut4 to a csv file\n", "#Printing the number of False and Trues\n", "print(AssignmentOutPut4.groupby('Class').size()[0].sum())\n", "print(AssignmentOutPut4.groupby('Class').size()[1].sum())" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### **Support Vector Machines** - its also a supervised machine learning algorithm capable of performing classification, regression and outlier detection. They draw a line that best separates two classes. Data instances closest to the line that best separates the classes are called support vectors. " + ] + }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 28, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "MCC: 0.8164151115601915\n", - "Accuracy: 91.12662013958126\n", - "405\n", - "353\n" + "MCC: 0.8399582732206575\n", + "Accuracy: 92.82153539381855\n", + "379\n", + "379\n" ] } ], @@ -2317,30 +2209,36 @@ "test_size = 0.33\n", "seed = 5\n", "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", - "my_model5 = SVC()\n", + "my_model5 = SVC(kernel = 'linear')\n", "my_model5.fit(selected_features_train, Y_train)\n", "result = my_model5.score(selected_features_test, Y_test)\n", "\n", "Prediction = my_model5.predict(selected_features_train)\n", "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", "print(\"Accuracy:\", (result*100.0))\n", - "AssignmentOutPut5 = my_model5.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut\n", + "AssignmentOutPut5 = my_model5.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut5\n", "\n", - "AssignmentOutPut5 = pd.DataFrame(AssignmentOutPut5)\n", - "# Converting AssignmentOutPut to a dataframe since its output is an array\n", - "AssignmentOutPut5.columns = ['Class'] # Naming the out\n", + "AssignmentOutPut5 = pd.DataFrame(AssignmentOutPut5)# Converting AssignmentOutPut5 to a dataframe since its output is an array\n", + "AssignmentOutPut5.columns = ['Class'] # Naming the out put column\n", "AssignmentOutPut5.index.name = \"Index\" #Creating a column called index\n", "AssignmentOutPut5['Class'] = AssignmentOutPut5['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", "\n", - "AssignmentOutPut1.to_csv('AssignmentOutPut5.csv') # Writing AssignmentOutPut1 to a csv file\n", + "AssignmentOutPut1.to_csv('AssignmentOutPut5.csv') # Writing AssignmentOutPut5 to a csv file\n", "#Printing the number of False and Trues\n", "print(AssignmentOutPut5.groupby('Class').size()[0].sum())\n", "print(AssignmentOutPut5.groupby('Class').size()[1].sum())" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### **LinearDiscriminantAnalysis** - it is a dimensionality reduction technique used for the supervised classification problems. It too assumes a Gaussian distribution for the numerical input variables.It is used to project the features in higher dimension space into a lower dimension space." + ] + }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 29, "metadata": {}, "outputs": [ { @@ -2373,19 +2271,194 @@ "Prediction = my_model6.predict(selected_features_train)\n", "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", "print(\"Accuracy:\", (result*100.0))\n", - "AssignmentOutPut6 = my_model6.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut\n", "\n", - "AssignmentOutPut6 = pd.DataFrame(AssignmentOutPut6)\n", - "# Converting AssignmentOutPut to a dataframe since its output is an array\n", - "AssignmentOutPut6.columns = ['Class'] # Naming the out\n", + "AssignmentOutPut6 = my_model6.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut\n", + "AssignmentOutPut6 = pd.DataFrame(AssignmentOutPut6)# Converting AssignmentOutPut6 to a dataframe since its output is an array\n", + "AssignmentOutPut6.columns = ['Class'] # Naming the out put column\n", "AssignmentOutPut6.index.name = \"Index\" #Creating a column called index\n", "AssignmentOutPut6['Class'] = AssignmentOutPut6['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", "\n", - "AssignmentOutPut6.to_csv('AssignmentOutPut6.csv') # Writing AssignmentOutPut1 to a csv file\n", + "AssignmentOutPut6.to_csv('AssignmentOutPut6.csv') # Writing AssignmentOutPut6 to a csv file\n", "#Printing the number of False and Trues\n", "print(AssignmentOutPut6.groupby('Class').size()[0].sum())\n", "print(AssignmentOutPut6.groupby('Class').size()[1].sum())" ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### **Ada Boost** - it trains predictors sequentially, each trying to correct its predecessor. It works by weighting instances in the dataset by how easy or difficult they are to classify, allowing the algorithm to pay or less attention to them in the construction of subsequent models" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MCC: 0.8546905980754327\n", + "Confusion_matrix: [[475 30]\n", + " [ 43 455]]\n", + "385\n", + "373\n" + ] + } + ], + "source": [ + "from sklearn.ensemble import AdaBoostClassifier\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import matthews_corrcoef\n", + "from sklearn.metrics import confusion_matrix\n", + "\n", + "A = Train.values\n", + "# Separating A into output and input components\n", + "\n", + "test_size = 0.33\n", + "seed = 6\n", + "# Split data into training and test sets to evaluate the model’s performance.\n", + "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", + "# Construct and fit a model to the training set. max_depth=1 is used to tell the model that the forest to be composed of trees with a\n", + "# single decision node and two leaves. n_estimators is used to specify the total number of trees in the forest.\n", + "Model7 = AdaBoostClassifier(DecisionTreeClassifier(max_depth=1),n_estimators=200) \n", + "Model7.fit(selected_features_train, Y_train)\n", + "predictions = Model7.predict(selected_features_test)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_test, predictions)))\n", + "print(\"Confusion_matrix:\", confusion_matrix(Y_test, predictions))\n", + "\n", + "AssignmentOutPut7 = Model7.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut7\n", + "AssignmentOutPut7 = pd.DataFrame(AssignmentOutPut7)# Converting AssignmentOutPut7 to a dataframe since its output is an array\n", + "AssignmentOutPut7.columns = ['Class'] # Naming the out put column\n", + "AssignmentOutPut7.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut7['Class'] = AssignmentOutPut7['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "AssignmentOutPut7.to_csv('AssignmentOutPut7.csv') # Writing AssignmentOutPut7 to a csv file\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut7.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut7.groupby('Class').size()[1].sum())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### **Principle component analysis** - PCA is a common way of speeding up a machine learning algorithm. Its mostly used when a machine learning algorithm is too slow because the input dimension is too high, then PCA is used to speed it up can be a reasonable choice. PCA can also be used for data visualization." + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Using PCA for visualization of data.\n", + "from sklearn.decomposition import PCA\n", + "#A = Train.values\n", + "# Separating A into output and input components\n", + "features = ['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107', 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104']\n", + "x =Train.loc[:, features].values\n", + "y =Train.loc[:,['CLASS']].values\n", + "pca = PCA(n_components=2)\n", + "principalComponents = pca.fit_transform(x)\n", + "principalDf = pd.DataFrame(principalComponents, columns = ['principal_component1', 'principal_component2'])\n", + "FinalDf = pd.concat([principalDf, Train[['CLASS']]], axis = 1)\n", + "FinalDf\n", + "\n", + "#The plot\n", + "fig = plt.figure(figsize = (8,8))\n", + "ax = fig.add_subplot(1,1,1) \n", + "ax.set_xlabel('Principal_Component1', fontsize = 10)\n", + "ax.set_ylabel('Principal_Component2', fontsize = 10)\n", + "ax.set_title('2 component PCA', fontsize = 15)\n", + "plt.scatter(FinalDf.iloc[:, 0], FinalDf.iloc[:, 1], c = FinalDf.iloc[:, 2], cmap ='Spectral') \n", + "#classes = [\"1.0\", \"0.0\"]\n", + "#colors = ['r','g', 'b']\n", + "#for CLASS, color in (classes,colors):\n", + "# indicesToKeep = FinalDf['CLASS'] == CLASS\n", + "# ax.scatter(FinalDf.loc[indicesToKeep, 'principal_component1'], FinalDf.loc[indicesToKeep, 'principal_component2'], c =color )\n", + "ax.legend()\n", + "ax.grid()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### **Using principle component analysis for machine learning**" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MCC: 0.7507336393432698\n", + "Socre: 0.8753738783649053\n", + "506\n", + "497\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.decomposition import PCA\n", + "A= Train.values\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "#Make an instance of the Model\n", + "pca = PCA(.95)\n", + "#Splitting data\n", + "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", + "pca = PCA(n_components=2)\n", + "principalComponents = pca.fit_transform(selected_features_train)\n", + "fit_train = pca.fit(selected_features_train) #Fit PCA on training set\n", + "\n", + "#Apply the mapping (transform) to both the training set and the test set.\n", + "selected_features_trainF = pca.transform(selected_features_train)\n", + "selected_features_testF = pca.transform(selected_features_test)\n", + "\n", + "#Importing the model\n", + "from sklearn.linear_model import LogisticRegression\n", + "Model8 = LogisticRegression()\n", + "Model8.fit(selected_features_trainF, Y_train)\n", + "\n", + "#Predicting new data\n", + "Pred = Model8.predict(selected_features_testF)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_test, Pred)))\n", + "print(\"Socre:\", Model8.score(selected_features_testF, Y_test))\n", + "\n", + "AssignmentOutPut8 = Model8.predict(selected_features_testF) #Assigning the preditions of the model to variable AssignmentOutPut8\n", + "AssignmentOutPut8 = pd.DataFrame(AssignmentOutPut8)# Converting AssignmentOutPut8 to a dataframe since its output is an array\n", + "AssignmentOutPut8.columns = ['Class'] # Naming the out put column\n", + "AssignmentOutPut8.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut8['Class'] = AssignmentOutPut8['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "AssignmentOutPut8.to_csv('AssignmentOutPut8.csv') # Writing AssignmentOutPut8 to a csv file\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut8.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut8.groupby('Class').size()[1].sum())" + ] } ], "metadata": { @@ -2404,36 +2477,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" - }, - "varInspector": { - "cols": { - "lenName": 16, - "lenType": 16, - "lenVar": 40 - }, - "kernels_config": { - "python": { - "delete_cmd_postfix": "", - "delete_cmd_prefix": "del ", - "library": "var_list.py", - "varRefreshCmd": "print(var_dic_list())" - }, - "r": { - "delete_cmd_postfix": ") ", - "delete_cmd_prefix": "rm(", - "library": "var_list.r", - "varRefreshCmd": "cat(var_dic_list()) " - } - }, - "types_to_exclude": [ - "module", - "function", - "builtin_function_or_method", - "instance", - "_Feature" - ], - "window_display": false + "version": "3.6.6" } }, "nbformat": 4, From eb4fb322c8afb3a2a4fa725a0e3b7acd36b725ba Mon Sep 17 00:00:00 2001 From: Tendo1434 <58722184+Tendo1434@users.noreply.github.com> Date: Fri, 13 Mar 2020 05:37:39 -0400 Subject: [PATCH 21/29] Add files via upload --- Assignment Colab/nsangi-olga-tendo(1).ipynb | 2491 +++++++++++++++++++ 1 file changed, 2491 insertions(+) create mode 100644 Assignment Colab/nsangi-olga-tendo(1).ipynb diff --git a/Assignment Colab/nsangi-olga-tendo(1).ipynb b/Assignment Colab/nsangi-olga-tendo(1).ipynb new file mode 100644 index 0000000..d89b5b1 --- /dev/null +++ b/Assignment Colab/nsangi-olga-tendo(1).ipynb @@ -0,0 +1,2491 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# **ACE Class competition**\n", + "#### By Nsangi Olga Tendo\n", + "## Machine Learning Process:\n", + "#### 1. Have a peek of raw data\n", + "#### 2. Review of dimensions of thedataset.\n", + "#### 3. Review of attribues in the data set\n", + "#### 4. Review the data types of attributes in your data.\n", + "#### 5. Review of missing data(NAs)\n", + "#### 6. Summary of data using descriptive statistics.\n", + "#### 7. Understand the relationships in your data using correlations.\n", + "#### 8. Data Visualisation\n", + "#### 9. Review the skew of the distributions of each attribute.\n", + "#### 10.Spot checking classification algorithms\n", + "#### 11.Data preparation\n", + "#### 12.Feature selection\n", + "#### 13. Machine learning" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", + "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\n", + "/kaggle/input/ace-class-assignment/Test.csv\n" + ] + } + ], + "source": [ + "# This Python 3 environment comes with many helpful analytics libraries installed\n", + "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", + "# For example, here's several helpful packages to load in \n", + "\n", + "#Importing the necessary libraries that are going to be used in the pipeline\n", + "import numpy as np # linear algebra\n", + "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "\n", + "\n", + "# Input data files are available in the \"../input/\" directory.\n", + "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", + "\n", + "import os\n", + "for dirname, _, filenames in os.walk('/kaggle/input'):\n", + " for filename in filenames:\n", + " print(os.path.join(dirname, filename))\n", + "# Any results you write to the current directory are saved as output.\n", + "import warnings\n", + "warnings.filterwarnings('ignore')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 1. Naming the Training and test dataset using." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0", + "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a" + }, + "outputs": [], + "source": [ + "Train = pd.read_csv(\"../input/ace-class-assignment/AMP_TrainSet.csv\")\n", + "Test = pd.read_csv(\"../input/ace-class-assignment/Test.csv\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Confirming that the data has been read in and assigned to variables Train and Test" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Dimensions of the train and test data set\n", + "#### This helps in knowing the size of your data set and also give an intiution on what algorithms you could use incase the size is big or small." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "((3038, 12), (758, 11))" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Train.shape, Test.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 3. Establishing the attributes in the train and test data set" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", + " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", + " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", + " 'CLASS'],\n", + " dtype='object'),\n", + " Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", + " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", + " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112',\n", + " 'CT_RACS820104'],\n", + " dtype='object'))" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Train.columns, Test.columns" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 4. Establishing the data types for each attribute in the train data set. This helps in finding out which columns have data types like strings that may need to be converted to foating points or integers to represent categorical or ordinal values since most machine learning algorithms take in integers or floats for inputs. This can be done using df.dtype method or the df.info() method as shown in the two cells below, tho the df.info() is more informative as its also tells the total number of instances for each column." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(FULL_Charge float64\n", + " FULL_AcidicMolPerc float64\n", + " FULL_AURR980107 float64\n", + " FULL_DAYM780201 float64\n", + " FULL_GEOR030101 float64\n", + " FULL_OOBM850104 float64\n", + " NT_EFC195 int64\n", + " AS_MeanAmphiMoment float64\n", + " AS_DAYM780201 float64\n", + " AS_FUKS010112 float64\n", + " CT_RACS820104 float64\n", + " CLASS int64\n", + " dtype: object,\n", + " FULL_Charge float64\n", + " FULL_AcidicMolPerc float64\n", + " FULL_AURR980107 float64\n", + " FULL_DAYM780201 float64\n", + " FULL_GEOR030101 float64\n", + " FULL_OOBM850104 float64\n", + " NT_EFC195 int64\n", + " AS_MeanAmphiMoment float64\n", + " AS_DAYM780201 float64\n", + " AS_FUKS010112 float64\n", + " CT_RACS820104 float64\n", + " dtype: object)" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Train.dtypes, Test.dtypes" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 3038 entries, 0 to 3037\n", + "Data columns (total 12 columns):\n", + "FULL_Charge 3038 non-null float64\n", + "FULL_AcidicMolPerc 3038 non-null float64\n", + "FULL_AURR980107 3038 non-null float64\n", + "FULL_DAYM780201 3038 non-null float64\n", + "FULL_GEOR030101 3038 non-null float64\n", + "FULL_OOBM850104 3038 non-null float64\n", + "NT_EFC195 3038 non-null int64\n", + "AS_MeanAmphiMoment 3038 non-null float64\n", + "AS_DAYM780201 3038 non-null float64\n", + "AS_FUKS010112 3038 non-null float64\n", + "CT_RACS820104 3038 non-null float64\n", + "CLASS 3038 non-null int64\n", + "dtypes: float64(10), int64(2)\n", + "memory usage: 284.9 KB\n" + ] + } + ], + "source": [ + "Train.info()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 5. Establishing if there are any missing values in the attributes of the data set. This helps to give an insight on how to handle the missing values, whether to remove rows that have missing values or establishing a method like the mean,median ect to impute the NAs. " + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "FULL_Charge 0\n", + "FULL_AcidicMolPerc 0\n", + "FULL_AURR980107 0\n", + "FULL_DAYM780201 0\n", + "FULL_GEOR030101 0\n", + "FULL_OOBM850104 0\n", + "NT_EFC195 0\n", + "AS_MeanAmphiMoment 0\n", + "AS_DAYM780201 0\n", + "AS_FUKS010112 0\n", + "CT_RACS820104 0\n", + "CLASS 0\n", + "dtype: int64" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Train.isna().sum()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 6. Descriptive statistics summary of the data in each column.\n", + "#### This includes measures of central tendencies like teh mean, median and measures of spread like standard, variance, range and interquatile range. The smallest and largest values of each column are also returned. This helps in understanding the distribution of data in each column. This way you can also find out if you have negative values in any attribute. This also helps in understanding the scales at which each attribute is at." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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We can also observe that there are negative values in some attributes have a minimum values in negatives." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Since this is a classification problem, its important to check out the propotions of the values in the class to be predicted as its possible one class may have more values as compared to the others. Incases where one class is higher than another class we could employe methods likes smote to over sample the least represented class so as to have an un biased algorithm." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0, 0.5, 'Distirbution')" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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CLASS0.534602-0.598816-0.584111-0.554838-0.260470-0.4532870.2607020.693552-0.4371680.0334320.2676521.000000
\n", + "
" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 \\\n", + "FULL_Charge 1.000000 -0.612996 -0.490977 \n", + "FULL_AcidicMolPerc -0.612996 1.000000 0.794796 \n", + "FULL_AURR980107 -0.490977 0.794796 1.000000 \n", + "FULL_DAYM780201 -0.434603 0.541481 0.548253 \n", + "FULL_GEOR030101 -0.058725 0.115201 0.346139 \n", + "FULL_OOBM850104 -0.283758 0.513344 0.462712 \n", + "NT_EFC195 0.088068 -0.143168 -0.169540 \n", + "AS_MeanAmphiMoment 0.355477 -0.431590 -0.426097 \n", + "AS_DAYM780201 -0.365374 0.449621 0.456260 \n", + "AS_FUKS010112 -0.090570 0.002334 0.032958 \n", + "CT_RACS820104 0.232929 -0.213543 -0.403599 \n", + "CLASS 0.534602 -0.598816 -0.584111 \n", + "\n", + " FULL_DAYM780201 FULL_GEOR030101 FULL_OOBM850104 \\\n", + "FULL_Charge -0.434603 -0.058725 -0.283758 \n", + "FULL_AcidicMolPerc 0.541481 0.115201 0.513344 \n", + "FULL_AURR980107 0.548253 0.346139 0.462712 \n", + "FULL_DAYM780201 1.000000 0.010118 0.334778 \n", + "FULL_GEOR030101 0.010118 1.000000 0.319157 \n", + "FULL_OOBM850104 0.334778 0.319157 1.000000 \n", + "NT_EFC195 -0.090058 -0.230417 -0.230561 \n", + "AS_MeanAmphiMoment -0.408793 -0.160269 -0.336297 \n", + "AS_DAYM780201 0.894191 -0.029085 0.275640 \n", + "AS_FUKS010112 0.055915 0.040480 -0.452769 \n", + "CT_RACS820104 -0.326792 -0.151935 0.155304 \n", + "CLASS -0.554838 -0.260470 -0.453287 \n", + "\n", + " NT_EFC195 AS_MeanAmphiMoment AS_DAYM780201 \\\n", + "FULL_Charge 0.088068 0.355477 -0.365374 \n", + "FULL_AcidicMolPerc -0.143168 -0.431590 0.449621 \n", + "FULL_AURR980107 -0.169540 -0.426097 0.456260 \n", + "FULL_DAYM780201 -0.090058 -0.408793 0.894191 \n", + "FULL_GEOR030101 -0.230417 -0.160269 -0.029085 \n", + "FULL_OOBM850104 -0.230561 -0.336297 0.275640 \n", + "NT_EFC195 1.000000 0.178683 -0.036844 \n", + "AS_MeanAmphiMoment 0.178683 1.000000 -0.322378 \n", + "AS_DAYM780201 -0.036844 -0.322378 1.000000 \n", + "AS_FUKS010112 0.145924 0.025580 0.045562 \n", + "CT_RACS820104 0.080898 0.171524 -0.256060 \n", + "CLASS 0.260702 0.693552 -0.437168 \n", + "\n", + " AS_FUKS010112 CT_RACS820104 CLASS \n", + "FULL_Charge -0.090570 0.232929 0.534602 \n", + "FULL_AcidicMolPerc 0.002334 -0.213543 -0.598816 \n", + "FULL_AURR980107 0.032958 -0.403599 -0.584111 \n", + "FULL_DAYM780201 0.055915 -0.326792 -0.554838 \n", + "FULL_GEOR030101 0.040480 -0.151935 -0.260470 \n", + "FULL_OOBM850104 -0.452769 0.155304 -0.453287 \n", + "NT_EFC195 0.145924 0.080898 0.260702 \n", + "AS_MeanAmphiMoment 0.025580 0.171524 0.693552 \n", + "AS_DAYM780201 0.045562 -0.256060 -0.437168 \n", + "AS_FUKS010112 1.000000 -0.445284 0.033432 \n", + "CT_RACS820104 -0.445284 1.000000 0.267652 \n", + "CLASS 0.033432 0.267652 1.000000 " + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Train.corr(method='pearson')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### From the summary above, AS_DAYM780201 and FULL_DAYM780201 are the strongest positively correlated with a correlation of 0.894191 while FULL_AcidicMolPerc and FULL_Charge are the strongest negatively correlated attributes. This correlation can further be observed by plotting a heat map using seaborn to show the correlation of attributes with each other as shown below" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize= (10,10))\n", + "sns.heatmap(Train.corr(method = 'pearson'), cmap='Purples', robust=True, square=True, annot= True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 8. Using visualisation to understand the data at hand. Histograms, Density plots and Box and whisker plots are some of the plots used to understand the attribute distribution. Histograms were used. They're used to summarize discrete or continuous data by showing the number(frequency) of data points that fall within a specified range of values. Histograms graphically show center) of the data, spread (i.e., the scale) of the data, skewness of the data, presence of outliers and presence of multiple modes in the data" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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KI74melO3fraRpJGmM2B5rJwZpMEQHyGNk3FgjU0rNVy1Ru9dp/YrIk4HTgeYNm1aTJgwoStPciO69QIZTq/GDb0du5mZrT9auQvyraQpFB6INBHmxaRxeiYWBhncjuenDRgAtoc0MCFpoLmHMTMzM1vPtJIBuwvYS9KmedTmfYFbSSOsH5q3mU0alBDSCLSV+Q0PBa4eqv+XmZmZ2VjVSh+wayVdRBpqYhC4kdR0eDmwUNKJedkZeZczgO9JWkqq+ZrZSuBW35T5lze13/IFB49yJGbtNdJrfd7UQebMv9zXuj1nyT2rmePvTOuAlu6CjIjPkuY1LFoG7FFj27+QJoE2MzMzW695JHwzMzOzkrU6Dpi1UbNNiWZmZtbdXANmZmZmVjJnwMzMzMxK5gyYmZmZWcmcATNrM0kfk3SLpN9LOl/SxpJ2lHStpDskXSBpw7ztRvn10rx+SmejNzOzdnAGzKyNJE0GPgxMi4hXAeNIY+CdBJwSETsBq4Cj8i5HAasi4mXAKXk7MzMbY5wBM2u/8cAmeQquTYEVwFuAi/L6s4FD8vMZ+TV5/b55pgkzMxtDPAyFWRtFxD2SvkiauutJ4OfA9cAjETGYNxsAJufnk4G7876DklYDWwEPFo8raS4wF6Cvr4/+/v5Ri3nNmjWjerx2mjd1cPiNCvo2Sfv0yucbiV76v5mZM2BmbSVpS1Kt1o7AI8APgANrbFqZF7VWbdc6c6ZGxOmkqb+YNm1aTJ8+fTTCBaC/v5/RPF47jXQKmXlTBzl5yXiWHzG9PQF1UC/938zMTZBm7fZW4M6IeCAingEuBl4PTMxNkgDbAffm5wPA9gB5/QtJc6eamdkY4gyYWXvdBewladPcl2tf4FbgGuDQvM1s4NL8fFF+TV5/dUSsUwNmZma9zRkwszaKiGtJnelvAJaQ0tzpwHHAxyUtJfXxOiPvcgawVV7+cWB+6UGblUzSREkXSfqDpNskvU7SJElX5qFarszN+Sj5Sh6q5WZJu3c6frNmuA+YWZtFxGeBz1YtXgbsUWPbvwCHlRGXWRc5FfhpRByax8TbFPg0cFVELJA0n1QYOY7Uh3Kn/NgTOC3/NesprgEzM7OOkbQF8CZyLXBEPB0Rj7D2kCzVQ7WcE8liUn/KbUsO26xlrgEzM7NOeinwAPBdSbuShmn5CNAXESsAImKFpG3y9s8N1ZJVhnFZUTxoo0O1VIYmaUa3D/sxlocmGQufzRkwM1vvTBnh8BVFyxccPIqRGOl3aHfgQxFxraRTGbrv46gO1fLVcy/l5CXN/RR2+3AmY3lokrHw2dwEaWZmnTQADOQbViDdtLI7cH+laTH/XVnYfvvC/sVhXMx6RksZMN+5YmZmrYiI+4C7Jb08L6oM1VIckqV6qJZZ+TdlL2B1panSrJe02gTpO1fMzKxVHwLOzb8jy4D3kSoILpR0FGk8vcrdwVcABwFLgSfytmY9p+kMWOHOlTmQ7lwBnpY0A5ieNzsb6CdlwJ67cwVYnGvPtnXJxcxs/RYRNwHTaqzat8a2ARzT9qDM2qyVGrBS7lzp5TsdWo292TtzmlWJdX0+52ZmZmVoJQNWyp0rEyZM6Nk7HVq9S2OkEw23qnJHTy/fXdLLsZuZ2fqjlU74vnPFzMzMrAlNZ8B854qZmZlZc1q9C9J3rpiZmZmNUEsZMN+5YmZmZjZyHgnfzMzMrGTOgJmZmZmVzJNxm7WZpInAd4BXkYZeeT9wO3ABMAVYDrwrIlZJEmmGiYNIfSXnRMQNHQjbzIbR7KTuntDdwDVgZmWoTNn1CmBX4DbSmHlXRcROwFU8P4ZeccquuaQpu8zMbIxxBsysjQpTdp0BacquiHiENDXX2Xmzs4FD8vPnpuyKiMXAxMq4emZmNna4CdKsvUqZsms0p1/qxHROS+5Z3dR+86aObPu+TVqf4qtbp7ryNFxmvcUZMHtOpT/DvKmDI5oGyf0ZhlTKlF2jOf1SJ6ZzKmvarXlTBzl5SWtfe5Upu7qNp+Ey6y1ugjRrL0/ZZWZm63AGzKyNPGWXmZnV4iZIs/bzlF1mZrYWZ8DM2sxTdpmZWTU3QZqZmZmVzBkwMzMzs5K5CdLMzMzW4amW2ss1YGZmZmYlcw1YCZotRZiZrS8kjQOuA+6JiLdL2hFYCEwCbgCOjIinJW0EnAO8BngIeHdELO9Q2GZNcw2YmZl1g4+QJqqvOAk4JU9Yvwo4Ki8/ClgVES8DTsnbmfUcZ8DMzKyjJG0HHAx8J78W8BbSzBGw7oT1lYnsLwL2zdub9RQ3QZqZWad9GfgksHl+vRXwSERUZk6vTEoPhQnrI2JQ0uq8/YPFAzY6Yf1oTNA+UmVNmt7qBO3NnpcyPt9YmHy+5QyY2+3NzKxZkt4OrIyI6yVNryyusWk0sO75BQ1OWP/Vcy9teYL2EVvyeFO7jfTuwlYnaJ/T7F2QJUxYPxYmnx+NJki325uZWbP2Bt4haTmp8P4WUo3YREmVnFFxUvrnJqzP618IPFxmwGajoaUMmNvtzcysFRHxqYjYLiKmADOBqyPiCOAa4NC8WfWE9ZWJ7A/N269TA2bW7Vqtd217u30vt/NWYi+7f0GrRtonopv+P718vZjZWo4DFko6EbgROCMvPwP4nqSlpJqvmR2Kr3QjHdJo3tRB5sy/3AOjdqmmM2BltdtPmDChZ9t5K23Uzbajd8q8qYMj6hNRRnt/o8ZCvwCz9VVE9AP9+fkyYI8a2/wFOKzUwMzaoJUasEq7/UHAxsAWFNrtcy1YrXb7Abfbm5mZ2fqs6T5gbrc3MzMza047BmI9Dvh4bp/firXb7bfKyz8OzG/De5t1JUnjJN0o6bL8ekdJ10q6Q9IFkjbMyzfKr5fm9VM6GbeZmbXHqGTAIqI/It6eny+LiD0i4mURcVhEPJWX/yW/fllev2w03tusR3i4FjMze46nIjJrMw/XYmZm1TwVkVn7dWyalWZ0YiiPsoZqGY1pZ7p1mBMPwWLWW5wBM2ujTk+z0oxODOVR1lAtIx1ipZZuGnalyEOwmPUWZ8DM2svDtZiZ2TrcB8ysjTxci5mZ1eIaMLPO8DQrPWqk08FUeDoYMytyBsysJJ5mxczWBy6kNMZNkGZmZmYlcwbMzMzMrGTOgJmZmZmVzBkwMzMzs5K5E76ZmdkY1myneGsv14CZmZmZlcwZMDMzM7OSOQNmZmZmVjJnwMzMzMxK5k741jKPemxmzZK0PXAO8DfAX4HTI+JUSZOAC4ApwHLgXRGxSpKAU4GDgCeAORFxQydiN2uFM2BmNmp8t5U1YRCYFxE3SNocuF7SlcAc4KqIWCBpPjCfNIfqgcBO+bEncFr+a9ZTmm6ClLS9pGsk3SbpFkkfycsnSbpS0h3575Z5uSR9RdJSSTdL2n20PoSZmfWmiFhRqcGKiMeA24DJwAzg7LzZ2cAh+fkM4JxIFgMTJW1bcthmLWulBsylFjMzGzWSpgCvBq4F+iJiBaRMmqRt8maTgbsLuw3kZSuqjjUXmAvQ19dHf39/zffs2wTmTR0ctc/QTXrts9X7H9WyZs2aEW3fjZrOgOWEUUkcj0kqllqm583OBvpJGbDnSi3AYkkTJW1bSWBmZrb+kjQB+CHw0Yh4NHX1qr1pjWWxzoKI04HTAaZNmxbTp0+vebCvnnspJy8Zm71x5k0d7KnPtvyI6Q1v29/fT73/aa8Ylf9MO0stvZzLrcTeSyUQKK/U1I7/ay9fL2brK0kbkDJf50bExXnx/ZVCem5iXJmXDwDbF3bfDri3vGjNRkfLGbB2l1omTJjQs7ncSg59To91TC6r1DSS0k6juq1U5Du8zIaWr/kzgNsi4kuFVYuA2cCC/PfSwvJjJS0kdWNZ7ZYU60UtjQM2VKklr3epxdZ3lb6SrwT2Ao6RtDOpb+RVEbETcFV+DWv3lZxL6itpNpbtDRwJvEXSTflxECnjtZ+kO4D98muAK4BlwFLg28AHOxCzWcuaruZwqcVseO4raTa0iPgltVtIAPatsX0Ax7Q1KLMStNLOVCm1LJF0U172aVLG60JJRwF3AYfldVeQmlWWkppW3tfCe3fESMc4mjd1sOeaH619OnGHVzNa6UfX7f0dO3lXWLv7Jrr/o1lvaeUuSJdazBrUqTu8mtFKP7puL3B08q6wdvR5LOq2/o9mNjTPBWnWZu4raWZm1ZwBM2ujBvpKwrp9JWflmSP2wn0lzczGpN4Zoc2sN613fSXNzGx4zoCZtZH7SpqZWS1ugjQzMzMrmTNgZmZmZiVzBszMzMysZM6AmZmZmZXMGTAzMzOzkjkDZmZmZlYyD0NhZlaCkc4lW7F8wcGjHImZdQPXgJmZmZmVzBkwMzMzs5K5CdI6xk0yZma2vnIGzMzW0Wzm2MzMGuMMmJmZmXXcSAp+86YOMidv36utIu4DZmZmZlay9bIGzM0rZmZm1kmuATMzMzMrWek1YJIOAE4FxgHfiYgFzRzHtVg2Vo1WGjEby5xOrKJX76gvNQMmaRzwdWA/YAD4raRFEXFrmXFYbxsqsRU7ZlbrdGJrxGinkWa+mOZNHWQ97Z1gPcK/JTYaOp1xK/tbdg9gaUQsA5C0EJgBONGYJU4jtpZGfySqCx+9UOBogdOJ9TxFRHlvJh0KHBARR+fXRwJ7RsSxhW3mAnPzy5cDDwEPlhbk6Nqa3oy9V+OG5mPfISJeNNrBjFQjaSQvr04nt49iGL38/x+OP1treiadjCCN+JroTd362RpOI2XXgKnGsrVygBFxOnD6cztI10XEtHYH1g69Gnuvxg29HXs2bBqBddPJqAbQ++ewLn+2MWPEvyV1DzSGz5s/W3cr+y7IAWD7wuvtgHtLjsGsmzmNmA3P6cR6XtkZsN8CO0naUdKGwExgUckxmHUzpxGz4TmdWM8rtQkyIgYlHQv8jHTr8JkRccswu7WlmaUkvRp7r8YNvR17s2lktPX0ORyGP9sYMMrpZCyfN3+2LlZqJ3wzMzMz80j4ZmZmZqVzBszMzMysZF2XAZM0TtKNki7Lr3eUdK2kOyRdkDtcdh1JEyVdJOkPkm6T9DpJkyRdmWO/UtKWnY6zFkkfk3SLpN9LOl/Sxt163iWdKWmlpN8XltU8z0q+ImmppJsl7d65yHtDdfobK2qlz07HNFpqpd9Ox9QrJB0g6fb8HTG/0/G0QtL2kq7J1/ctkj6Sl/fE71AjejV/UE/XZcCAjwC3FV6fBJwSETsBq4CjOhLV8E4FfhoRrwB2JX2G+cBVOfar8uuuImky8GFgWkS8itShdSbde97PAg6oWlbvPB8I7JQfc4HTSoqxl1Wnv7GiVvrseUOkXxtGYTqjA4GdgcMl7dzZqFoyCMyLiFcCewHH5M/T9b9DI9Cr+YOauioDJmk74GDgO/m1gLcAF+VNzgYO6Ux09UnaAngTcAZARDwdEY+QpsY4O2/WlbFn44FNJI0HNgVW0KXnPSJ+ATxctbjeeZ4BnBPJYmCipG3LibT3VKe/sWKI9DlWVKdfj4fVmOemM4qIp4HKdEY9KSJWRMQN+fljpIzKZHrnd2hIvZo/GEpXZcCALwOfBP6aX28FPBIRg/n1AOmC6jYvBR4AvpurR78jaTOgLyJWQEocwDadDLKWiLgH+CJwFynjtRq4nt447xX1zvNk4O7Cdt3+OTqtOv2NFfXSZ8+rlX4j4uedjapnjNnvB0lTgFcD19IDv0MN6tX8QV1dkwGT9HZgZURcX1xcY9NuHDdjPLA7cFpEvBp4nB6p5s39AWYAOwIvBjYjVclX68bzPpxeuX46rk76Gyt6Nn0Op1b6lfTezkbVM8bk94OkCcAPgY9GxKOdjmc09Hj+oK6uyYABewPvkLScVBX8FlKOd2KuWofunW5iABiIiGvz64tIX/j3V5q88t+VHYpvKG8F7oyIByLiGeBi4PX0xnmvqHeePV1J49ZJf5K+39mQRk299DkW1Eu/Nrwx9/0gaQNS5uvciLg4L+6F36Hh9HL+oK6uyYBFxKciYruImELqRHp1RBwBXAMcmjebDVzaoRDrioj7gLslvTwv2he4lTQ1xuy8rCtjJzVd7CVp09ymXom96897Qb3zvAiYle+G3IvUPLOiEwF2uzrpb0zUpAyRPsdO5eeqAAAgAElEQVSCWul3TNxgUIIxNZ1R/v+fAdwWEV8qrOqF36Eh9XL+YCilTkXUpOOAhZJOBG4kd6TtQh8Czs0JeRnwPlIG90JJR5G+KA/rYHw1RcS1ki4CbiDdRXMjaYqHy+nC8y7pfGA6sLWkAeCzwAJqn+crgIOApcATpP+JrZ9qpc+eN0T6tWF0ybRfo2lv4EhgiaSb8rJPU//7cSzolfxBTZ6KyMzMzKxkXdMEaWZmZra+cAbMzMzMrGTOgHUZSe+RdJ2kNZJWSPqJpDdIOn64u9Ik9UtaJWmjquXbSfqhpAclrZa0RNKcwvqj8hQtj0m6X9LlkjZv00c0MzNb7zkD1kUkfZx0a+1/AX3AS4Bv0MDozHngvTeSxkF5R9Xq75EGHNyBNHjdLOD+vN8++f0Oj4jNgVcCF7b8YWzMq1NY+H/59RpJT0t6pvD6J0Mca4qkKGy7XHXm5qtX0Mjr9pB0haRHJD0s6TeS3ldY/2lJd+b3GJB0QWHdJKX55B7Mj3OVRtFH0jZK8yzemwsxv5K0Z43z8WdJj0u6RNKkwrpj87l6StJZNeLeNxeCnlCaz2+HGttMkvSApF/WO49WrnydPlm4btfk62Cgxrb9ko7Oz+sWqPMx39pELDtK+qukb1Qtr6St8VXLz8qd15E0R9KzOf5HJf1Oaeyt6mPUTZ+SXinp6pw+lkp6Z9X6dynNU/mYpFslHVK1/mOS7sv7n1lM35JOyBUHg5KOr/HZh0p7a6oez0r66ohObps4A9YlJL0Q+BxwTERcHBGPR8QzEfHjiPhEA4eYBSwmzZU4u2rda4Gz8jEHI+LGiPhJYd2vI+JGgIh4OCLOzlNZmNWk+oWFGyNiQkRMyOsuqLyOiFoD/FabmPc9FPh3SftVve8U6hQ0lCbYvhr4/4CXkQob/0IeWFjSbNJdYm/N7zGNNDdexYnAlqSR8/82f67j87oJpGELXgNMIk17crnSoJdI2gX4Vj5+H+mu2+IP4b35+GdWf2BJW5PG7/r3fOzrgAuqtyPNe+chJrrPPxSu8Ql0biyqWaT5EGfWKpw04Nc5/omka3ehpIlV29RMnzlzdylwGekangt8X9Lf5fWTge8DHwe2AD4BnCdpm7x+f9LgyPsCU0hp8D8L77uUNAr+5dVBD5f2qv43fcCTwA+aOD+jzhmw7vE6YGPgR03uPws4Nz/2l9RXWLcY+LqkmZJeUrXftXn7/5S0d5MJ19Yjo1BYGFZEXAfcAuxWtWqogsZ/A2dHxEkR8WCeA/T6iHhXXv9a4GcR8af8HvdFRHHIhh2BSyLi0YhYTUqLu+Rtl0XEl/J8e8/m/TYEKmOLHQH8OCJ+ERFrSJmpf1Ruys/n6RLgoRof9x+BWyLiBxHxF1Kmb1dJr6hskDOXrwK+O+zJs/XVLODfgGeAf2j2IBHxV1KryWbATnW2qU6fryDNxHBKTh9XA78iZYogDZL6SET8JKfLy0kzUvxtXj8bOCMibomIVcAJwJzC+52dKw1qVQwMmfaqHEoaiPZ/GjgVbecMWPfYCniwMK9VwyS9gdS8eGGequFPwHsKmxxGuuD+HbhT0k2SXgsQEf9D+gHYnVS6eEjSlySNa+nT2FjWamFhWEoD576KVPItqlnQkLRpjusi6ltMGpj3E5Km1bjGvw68XdKWSlP8/BNQs9lU0m6kDFglvl2A31XW50ze08DfDfdZa+z7OCkN75Lfa1yO7Vh6bKoVK4ekN5IyOQtJXUhmtXCscaRx8p4B/lxnm+r0WWtaIOVtINXq3ibpHZLG5ebHp4Cb8/q10kB+3idpqwZCHknamw2cE10y/pYzYN3jIdLgos0Mjjsb+HlEPJhfn0ehdiAiVkXE/IjYhVQFexNwiSTl9T+JiH8gVR3PIJU8jm76k9hY13RhoQEPSnoS+DWpGeGSyophChpbkr7P6s50EBHfJw3Iuj+pmXJlVT+WG0iZqofy41nWbkasxLEFqYbgP3NNGaQmytVVm64GGrmZZbh9PwxcO0bn6RwLLlHqc/iIpEuG37wtZgM/ybVH5wEHVpr3RmAvSY8AfyFN8P7eiKietqhe+vwDqWbpE5I2kPQ2YB9gU4CIeBY4J8f2VP77gVzYgHXTQOX5aKQfAHLrzz6k7gNdwRmw7vFr0oV/yHAbFknaBHgXsE/uwHgf8DFSE8au1dvnTNoXSdXFk6rW/TUiriL1o3lV9b5mWSuFheFsTfpC/VfSjAcbFNYNVdBYBfwV2Haog0fEuRHxVlI/l38GPpf7n0DqF/JH0hf3FqQM3lodpXN6+zGwOCL+b2HVmrxP0RbUbjKpVndfSS8mZcA+08BxrDMOiYiJ+XEIaUaCDWpstwGpVmlU5WvyMFKtMBHxa9KI95XCSaWgVB1TdTyLI2IiqTCziNTXslrN9BlpHtJDgIOB+4B5pJq4gRzjW4Ev5H02JGWEvpNrkmHdNFB53lL6qVo2C/hlRNzZwDFL4QxYl8gl6f8g9dU6RGlutw0kHSjpC3mzF0jauPDYiHTRPwvsTGqP3410J+P/kKuhJZ0k6VWSxud28X8BlkbEQ5Jm5L5hWyrZg5Q4Fpd6AqyXNFVYaFTuQ3Jyfo8PwvAFjYh4Isf1Tw2+xzMR8QNSE0ilsLEr8K3cp20N8E3SVFbkGDYilfjvAT5Qdchb8v6VbV8KbETK0A2net/NSH1jbgH2IGUqb82f+VRgj3wO3E2gO91FKqBMqCzIrQ07UKdJr0XvJGU4vlFIG5N5vhlyBSmjNaVqvx1rxZOv/Q8CR0p6dY3166TPvPzmiNgnIraKiP1JHel/k1fvBvwiIq7LBf3fkvofV+72XCsN5Of3R0StPpPVGk17s+ii2i8AIsKPLnqQOhReR+qgeB+pX9brSR1zo+oxAPwUOLnGcd6V9x8PfBW4g1RSeIB0p8or83ZvIt0J9iCpxPBH4JOdPg9+dPeDdDfT/aRM2KakkvCBwBcK2xwPfL/B403J1/T4wrK3k+4o2xg4HHiYdLfl3xQev6hc/zmdrCHdYbVVXrYrsDA/n0MqoW9OKnweSLoj6g15/TU5rWySH98AfpXXbUCq+bqkGGMh1l2AR0m1BpuRas4WFtaPz5/j/5KaLzeuHAd4EanJ5J/y8pNItRGQfkiKn/cjpB+uv+n0NeBHACwn3VVbvfx/Sf32JuT/4SfzthsX0sZ5+f9deWxUOOaBVevWueYK7/Uz0hyIxevkNaQa4al5m/NJd9pula/lw4FHgL5C2vhl1XG/CPwoPx8yfebXf59j3ZRUQ3Zn4TPtQ/qN2S2/fjWpJv1t+fUBpN+rnUk1cFcDCwrvtUE+9nmku4k3BsY1kvbyNq8n/aZu3ulrZq24Oh2AH3740ZsP6hQWCuuPp7UMmEil2w/RQEEjv96D1HF+NSnDdi0wK6/7R9KdWavyF/YSYE7hWDuSMlkP5X1/CuyU1+2T43uClMmrPN5Y2P89pNqPx0m35E+qOhfVBajjC+vfSupH8yTQD0ypc57mUPVD6UdH08ByamfAtic1ad+XMx4/A3Ye5noYKByzet2Jdd5/MqmJcWqNdVcAX8zPtwS+Q6q9XZXTwd5DXVekTv1PkTJWQ6bP/Pq/87HX5DT4sqrjHUvqtP8YsAyYV7W+Uqh7lHS370aFdWfVOCfFtFs37eX13wK+1+nrpfrhybjNzMzMSuY+YGZmZmYlcwbMzEoh6Yga04KskXRLp2Mz62ZKU2jVSjt1p/ey7ucmSDMzM7OStWMcn1Gz9dZbx5QpU2que/zxx9lss83KDWgI3RSPY6ltqFiuv/76ByPiRSWHNCqGSift0k3/11b4c4xMr6YTp5Gk22Lqtnig9ZhGlEY6fRfAUI/XvOY1Uc8111xTd10ndFM8jqW2oWIBrosuuOabeQyVTtqlm/6vrfDnGJleTSdOI0m3xdRt8US0HtNI0oj7gJmZmZmVzBkwMzMzs5INmwGTdKaklZJ+X1h2vKR7JN2UH8XpOj4laamk2wtzrCHpgLxsadUEuGZmZmbrlUZqwM4iTRNQ7ZSI2C0/rgCQtDMwkzQ1wAGkuanG5TnLvk6aXmFn4PC8rZmZmdl6Z9i7ICPiF5KmNHi8GaQ5mJ4C7pS0lDQ1CKTJn5cBSFqYt711xBFnS+5ZzZz5lze17/IFBzf7ttYFpjT5fz/rgPbdbSPpTNLcaCsj4lV52STgAtI0HsuBd0XEqjwx76mkiZ6fIE2pcUPeZzbwb/mwJ0ZEd00eO4xm/zdOk2bDc/oaW1oZhuJYSbNIc8HNi4hVpHmpFhe2GcjLAO6uWr5nrYNKmgvMBejr66O/v7/mm/dtAvOmDjYVeL1jtmLNmjVtOW4zxnoszf7f23xezgK+BpxTWDYfuCoiFuRm9/nAcaSa4J3yY0/gNGDPnGH7LDCNNNfZ9ZIW5bRlNmZJ+hhwNOm6XwK8D9gWWAhMAm4AjoyIpyVtREpnryHN2/nuiFjeibjNWtFsBuw04ARSYjkBOBl4P2lyzmpB7abOmiPARsTpwOkA06ZNi+nTp9cM4KvnXsrJS5oLf/kRtY/Ziv7+furFWraxHkuzNZ9nHbBZ285LnZriGUDlDc8mTbJ8XF5+Tr5lebGkiZK2zdteGREPA0i6ktSUf35bgjbrApImAx8mTVb9pKQLSV1ZDiJ1dVko6ZvAUaTfnqOAVRHxMkkzgZOAd3cofLOmNZWDiYj7K88lfRu4LL8cIM0CX7EdcG9+Xm+52VjVFxErACJihaRt8vLJrFsjPHmI5etotKa4XerVJnZTrXQjuqm2uBVj4HOMBzaR9AywKbACeAvwnrz+bOB4UgZsRn4OcBHwNUnKBRqzntFUBkzStpUfFuCdQOUOyUXAeZK+BLyY1MTyG1LN2E6SdgTuIZVu3oPZ+qleTXG95esubLCmuF3q1Ww23S+zDbXSjeim2uJW9PLniIh7JH0RuAt4Evg5cD3wSERUcvTFwshzBZWIGJS0GtgKeLB43G4tpLSi1QJOt2XUuy0eKDemYTNgks4nNY1sLWmA1EdluqTdSD8Oy4EPAETELbn6+FZgEDgmIp7NxzkW+BkwDjgzIjwBr41191cKK7mJcWVeXq+meIDnmywry/tLiNOsYyRtSarV2hF4BPgBqZ9ktUphpKGCSrcWUlrRagGn2zLq3RYPlBtTI3dBHl5j8RlDbP954PM1ll8BXDGi6Mx62yJgNrAg/720sPzYfDfwnsDqnEn7GfBf+QcJ4G3Ap0qO2axsbwXujIgHACRdDLwemChpfK4FK3ZbqRRgBiSNB14IPFx+2Gat8Uj4ZqMg1xT/Gni5pAFJR5EyXvtJugPYL7+GVBBZBiwFvg18ECB3vj8B+G1+fK7SId9sDLsL2EvSpnmIln1JrSjXAIfmbaoLMLPz80OBq93/y3pRK8NQmFlWp6YY0o9J9bYBHFPnOGcCZ45iaGZdLSKulXQRaaiJQeBGUtPh5cBCSSfmZZWWlzOA7+VxJh8m9Sk26znOgJmZWUdFxGdJ/YuLlvH8QN7Fbf8CHFZGXGbt5CZIMzMzs5I5A2ZmZmZWMmfAzMzMzErmDJiZmZlZyZwBMzMzMyuZM2BmZmZmJXMGzMzMzKxkzoCZmZmZlcwDsZqZmZVoSpOTatvY4howMzMzs5I5A2ZmZmZWMmfAzMzMzErmPmBmZmZjWKXP2bypg8wZQf+z5QsObldIhmvAzMzMzErnDJiZmZlZyZwBMzMzMyuZM2BmbSTp5ZJuKjwelfRRScdLuqew/KDCPp+StFTS7ZL272T8ZmbWHs6AmbVRRNweEbtFxG7Aa4AngB/l1adU1kXEFQCSdgZmArsABwDfkDSuE7GblUXSREkXSfqDpNskvU7SJElXSroj/90ybytJX8mFlJsl7d7p+M2a4QyYWXn2Bf4UEX8eYpsZwMKIeCoi7gSWAnuUEp1Z55wK/DQiXgHsCtwGzAeuioidgKvya4ADgZ3yYy5wWvnhmrXOw1CYlWcmcH7h9bGSZgHXAfMiYhUwGVhc2GYgL1uLpLmkHx/6+vro7+9vV8w1rVmzpuZ7zps62NTxyo6/ot7n6DW9/DkkbQG8CZgDEBFPA09LmgFMz5udDfQDx5EKKedERACLc+3ZthGxouTQzVriDJhZCSRtCLwD+FRedBpwAhD578nA+wHV2D3WWRBxOnA6wLRp02L69OmjH/QQ+vv7qfWeIxljqGj5Eeseqwz1Pkev6fHP8VLgAeC7knYFrgc+AvRVMlURsULSNnn7ycDdhf0rhZS1MmDdWkiB5gsqrerbZGTv3e5z1o0FhzJjcgbMrBwHAjdExP0Alb8Akr4NXJZfDgDbF/bbDri3rCDNOmA8sDvwoYi4VtKpPN/cWEtPF1Kg+YJKq+ZNHeTkJY3/7Le7YNSNBYcyY3IfMLNyHE6h+VHStoV17wR+n58vAmZK2kjSjqR+Lr8pLUqz8g0AAxFxbX59ESlDdn8lneS/Kwvbu5BiPW/YDJikMyWtlPT7wrIR350iaXbe/g5Js9vzccy6j6RNgf2AiwuLvyBpiaSbgTcDHwOIiFuAC4FbgZ8Cx0TEsyWHbFaaiLgPuFvSy/OifUnX/yKg8lsxG7g0P18EzMq/N3sBq93/y3pRI3WRZwFfA84pLKvcnbJA0vz8+jjWvjtlT1I/lz0lTQI+C0wjVRVfL2lR7nRsNqZFxBPAVlXLjhxi+88Dn293XGZd5EPAubmv5DLgfaQKggslHQXcBRyWt70COIh0h/ATeVuznjNsBiwifiFpStXiEd2dkre9MiIeBpB0JWmMo/MxM7P1WkTcRCqgV9u3xrYBHNP2oMzarNlO+CO9O6Xe8nU0eufKSO/mKGrHHQ7ddDfHWI+l2f97N50XMzNbv432XZD17k5p6K4VaPzOla+ee+mI7uYoasedHd10N8dYj6XZO4jOOmCzrjkvZma2fmv2LsiR3p3iu1bMzMzMsmYzYCO9O+VnwNskbZnvmHxbXmZmZma23hm2DU/S+aRO9FtLGiDdzbiAEdydEhEPSzoB+G3e7nOVDvlmZmZm65tG7oI8vM6qEd2dEhFnAmeOKDozMzOzMcgj4ZuZmZmVzBkwMzMzs5I5A2ZmZmZWstEeB8zMxoApw4y1Nm/qYNPjsTXzfvUsX3DwqMVgZlYm14CZmZmZlcwZMDMzM7OSOQNmZmZmVjJnwMzMzMxK5gyYmZmZWcmcATNrM0nLJS2RdJOk6/KySZKulHRH/rtlXi5JX5G0VNLNknbvbPRmZtYOzoCZlePNEbFbREzLr+cDV0XETsBV+TXAgcBO+TEXOK30SM06QNI4STdKuiy/3lHStbmQcoGkDfPyjfLrpXn9lE7GbdYsZ8DMOmMGcHZ+fjZwSGH5OZEsBiZK2rYTAZqV7CPAbYXXJwGn5ELKKuCovPwoYFVEvAw4JW9n1nM8EKtZ+wXwc0kBfCsiTgf6ImIFQESskLRN3nYycHdh34G8bEXxgJLmkmrI6Ovro7+/f1QDnjd1cMj1fZsMv00ZWv3ca9asGfVz1wm9/jkkbQccDHwe+LgkAW8B3pM3ORs4nlQjPCM/B7gI+JokRUSUGbNZq5wBM2u/vSPi3pzJulLSH4bYVjWWrfPDkjNxpwNMmzYtpk+fPiqBVgw3yv28qYOcvKTzXx/Lj5je0v79/f2M9rnrhDHwOb4MfBLYPL/eCngkIiq5/EpBBAqFlIgYlLQ6b/9g8YDtLqQMZ6hMcacKLyMtOLX7nHVjwaHMmDr/DWo2xkXEvfnvSkk/AvYA7pe0ba792hZYmTcfALYv7L4dcG+pAZuVSNLbgZURcb2k6ZXFNTaNBtY9v6DNhZThDJUpHs1pvEZipAWnVgs4w+nGgkOZMTkDZtZGkjYDXhARj+XnbwM+BywCZgML8t9L8y6LgGMlLQT2BFZXmirNxqi9gXdIOgjYGNiCVCM2UdL4XAtWLIhUCikDksYDLwQeLj/ssc9ztLaXO+GbtVcf8EtJvwN+A1weET8lZbz2k3QHsF9+DXAFsAxYCnwb+GD5IZuVJyI+FRHbRcQUYCZwdUQcAVwDHJo3qy6kzM7PD83bu/+X9RzXgJm1UUQsA3atsfwhYN8aywM4poTQzLrdccBCSScCNwJn5OVnAN+TtJRU8zWzQ/GZtcQZMDMz6woR0Q/05+fLSP0lq7f5C3BYqYGZtYGbIM3MzMxK5gyYmZmZWcmcATMzMzMrmTNgZmZmZiVzBszMzMysZM6AmZmZmZXMGTAzMzOzkrWUAZO0XNISSTdJui4vmyTpSkl35L9b5uWS9BVJSyXdLGn30fgAZmZmZr1mNAZifXNEFGehnw9cFRELJM3Pr48DDgR2yo89gdPyXzOzpniuOjPrVe1ogpwBnJ2fnw0cUlh+TiSLSROtbtuG9zczMzPraq3WgAXwc0kBfCsiTgf6ImIFQESskLRN3nYycHdh34G8bEXxgJLmAnMB+vr66O/vr/nGfZvAvKmDTQVd75itWLNmTVuO24yxHkuz//duOi9mZrZ+azUDtndE3JszWVdK+sMQ26rGsnVmsM+ZuNMBpk2bFtOnT695sK+eeyknL2ku/OVH1D5mK/r7+6kXa9nGeixzmmx2OuuAzbrmvJiZ2fqtpSbIiLg3/10J/Ig0cer9labF/Hdl3nwA2L6w+3bAva28v5mZmVkvaroGTNJmwAsi4rH8/G3A54BFwGxgQf57ad5lEXCspIWkzverK02VZmZmvWaom0DmTR1surbe1g+tNEH2AT+SVDnOeRHxU0m/BS6UdBRwF3BY3v4K4CBgKfAE8L4W3tvMzMysZzWdAYuIZcCuNZY/BOxbY3kAxzT7fmZmZmZjhUfCN2sjSdtLukbSbZJukfSRvPx4SffkQYxvknRQYZ9P5QGLb5e0f+eiN2u/IdKIB/W2Mc0ZMLP2GgTmRcQrgb2AYyTtnNedEhG75ccVAHndTGAX4ADgG5LGdSJws5LUSyOVQb13Aq7Kr2HtQb3nkgb1Nus5zoCZtVFErIiIG/Lzx4DbSOPf1TMDWBgRT0XEnaQ+k3u0P1KzzhgijXhQbxvTRmMqIjNrgKQpwKuBa4G9SXcFzwKuI9UArCL98Cwu7FYZsLj6WA0NWNys4Qa7bWUg5G7w1XPTzdl9mzz/vFFTJ7+wHSG1ZKwMMlyVRkoZ1LsVQ6WBbkwjZcXU6Lnuxuu2zJicATMrgaQJwA+Bj0bEo5JOA04gDUZ8AnAy8H5GecDiZg13+/y8qYNND4TcTZr5HO0YyLlV3TT4crNqpJG6m9ZYVnoagaHTSTemkbJiajSNdON1W2ZMboI0azNJG5B+WM6NiIsBIuL+iHg2Iv4KfJvnmxk9YLGtd2qlETyot41xzoCZtZFSMf4M4LaI+FJhebHPyjuB3+fni4CZkjaStCOpo/FvyorXrGz10gjPD+oN6w7qPSvfDbkXHtTbelR31Y+ajT17A0cCSyTdlJd9Gjhc0m6kppPlwAcAIuIWSRcCt5LuDjsmIp4tPWqz8tRLIwvwoN42hjkDZtZGEfFLavdZuWKIfT4PfL5tQZl1kSHSCHhQbxvD3ARpZmZmVjJnwMzMzMxK5gyYmZmZWcmcATMzMzMrmTvhm5mZ2aiZMsxAzhXzpg6uNZjt8gUHtyukruQaMDMzM7OSOQNmZmZmVjJnwMzMzMxK5gyYmZmZWcncCd/MbAQa7WBcbX3rYGxmQ3MNmJmZmVnJnAEzMzMzK5kzYGZmZmYlcwbMzMzMrGTuhG82hjXbYdzMzNrLGTAzsxL47snu5EJK91jf0kjpTZCSDpB0u6SlkuaX/f5m3c5pxGx4TifW60qtAZM0Dvg6sB8wAPxW0qKIuLXMOMy6ldOI2fCcTqyoV2vOym6C3ANYGhHLACQtBGYATjRmidOIraWRH5d5UweZU7Vdp39c2szpxHpe2RmwycDdhdcDwJ7FDSTNBebml2sk3V7nWFsDDzYThE5qZq9hNR1PGziWGt580pCx7FBmLEMYNo3AiNJJW3y4i/6vrRjLn6NN33M9k06cRtbVbTF1Op46aaTVmBpOI2VnwFRjWaz1IuJ04PRhDyRdFxHTRiuwVnVTPI6ltm6KZQjDphFoPJ20S4+cy2H5c/SsUfstaZdu/J90W0zdFg+UG1PZnfAHgO0Lr7cD7i05BrNu5jRiNjynE+t5ZWfAfgvsJGlHSRsCM4FFJcdg1s2cRsyG53RiPa/UJsiIGJR0LPAzYBxwZkTc0uThOla1XEc3xeNYauumWGoa5TTSTl1/Lhvkz9GDeiSddOP/pNti6rZ4oMSYFLFO9xIzMzMzayPPBWlmZmZWMmfAzMzMzErWlRmw4aaYkLSRpAvy+mslTSms+1Refruk/UuI5eOSbpV0s6SrJO1QWPespJvyY1Q6iDYQzxxJDxTe9+jCutmS7siP2SXEckohjj9KeqSwbtTOjaQzJa2U9Ps66yXpKznOmyXtXlg3qudkLGnlvHaTBj7HdEmrC9fjf5Qd43AkbS/pGkm3SbpF0kdqbNMT/4+xpoHvwZfk/92N+f9yUJvj6ap020A8R+Q4bpb0v5J2bWc8jcRU2O61+bfq0LYEEhFd9SB1qPwT8FJgQ+B3wM5V23wQ+GZ+PhO4ID/fOW+/EbBjPs64NsfyZmDT/PxfKrHk12s6cG7mAF+rse8kYFn+u2V+vmU7Y6na/kOkjrKjfm6ANwG7A7+vs/4g4CeksYP2Aq5txzkZa49mz2u3PRr4HNOByzod5zCfYVtg9/x8c+CPNdJ+T/w/xtKjwe/k04F/yc93Bpa3OaauSrcNxPP6yvcucGAZ1+1wMRX+t1cDVwCHtiOObqwBe26KiYh4GqhMMVE0Azg7P78I2FeS8vKFEfFURNwJLM3Ha1ssEXFNRDyRXy4mjUfTLo2cm3r2B66MiIcjYhVwJXBAibEcDpzfwvvVFRG/AB4eYpMZwDmRLAYmStqW0T8nY0oL57WrNPA5ul5ErGX/YEIAACAASURBVIiIG/Lzx4DbSKPBF/XE/2OMaeR7MIAt8vMX0ubxyrot3Q4XT0T8b/7+hfb/hjYUU/Yh4IfAynbF0Y0ZsFpTTFR/0Ty3TUQMAquBrRrcd7RjKTqKVLKo2FjSdZIWSzqkhThGGs8/5erciyRVBivs2LnJzbI7kkoTFaN9boZSL9bRPifrm7F0/l4n6XeSfiJpl04HMxSlLhevBq6tWjWW/h+9opFzfjzwXkkDpNqUD5UTWl3dfJ1U/4Z2hKTJwDuBb7bzfcqeiqgRjUzFUm+bhqZxGeVY0obSe4FpwD6FxS+JiHslvRS4WtKSiPhTm+P5MXB+RDwl6Z9JNYVvaXDf0Y6lYiZwUUQ8W1g22udmKGVdL+ubsXL+bgB2iIg1uX/OJcBOHY6pJkkTSKXyj0bEo9Wra+zSi/+PXtLIOT8cOCsiTpb0OuB7kl4VEX9tf3g1deV1IunNpAzYGzodC/Bl4LiIeDY1rrVHN9aANTLFxHPbSBpPqtZ9uMF9RzsWJL0V+Azwjoh4qrI8Iu7Nf5cB/aRSayuGjSciHirE8G3gNY3uO9qxFMykqvmxDedmKPVi9XQmrRkT5y8iHo2INfn5FcAGkrbucFjrkLQBKfN1bkRcXGOTMfH/6DGNnPOjgAsBIuLXwMakCZ87peuuE0l/D3wHmBERD3UylmwasFDScuBQ4BvtaKnpxgxYI1NMLAIqd6wdClwdqdfcImCm0l2SO5JKsb9pZyySXg18i5T5WllYvqWkjfLzrYG9gVtbiKXReIpt+e8g9RWBNGL023JcWwJvy8vaFkuO5+WkDu6/Lixrx7kZyiJgVr77Zy9gdUSsYPTPyfqm3nntKZL+JvchRdIepO/FbvgReE6O7wzgtoj4Up3NxsT/o8c08j14F/8/e3ceb0dR5///9YawBwwQjRiQ4IgLmAExAygzTpQdHQMjOEEkicLgdwQ34gI6IwgyP/ALIrgwgjAQZVhElIwgGJD7RWYEWUTCIhAhQCCELQQCigY+vz+qDumcnHvvuWfps9z38/E4j3tOdXV3dd+ururu6irYFUDSW0kVsCdKTeWquuo4kfR64FLg4Ii4t1PpKIqIrSJiUkRMIrUz/0RE/LTV6+m6R5AxyBATko4Dbo6IuaQT0Q8kLSDd+Zqe571T0sWkwnwFcHjVY692pOX/AmOBH+Vz+EMR8QHgrcD3JL1MOqGfGBFNVTLqTM+nJH2AtP1Pk96KJCKelnQ86YQBcFxENNwwuc60QLr9fmGuIFe0dN9IuoD0Jtv43M7iGGCtnM7/ILW72If0UsYLwEfztJbuk37T6H7tNnVsx/7Av0haAfwRmF51vHaDXYCDgfmSbsthXwJeD731/+gndZ4HZwNnSfos6VHfrHYeX92Wb+tIz1dIbbi/m8vQFRExpcNpKoWHIjIzMzMrWTc+gjQzMzPra66AmZmZmZXMFTAzM0DSwvxGs5lZ27kC1mMkfUnS94eY/kohMlzcFqdrkqTI3YKYvSIfk3+UtLzw+XBu/Fodd0B5/FJJx0r64RDLHFFlSdJGkr4p6aGchgX5d9d1OWFm/W/UVcC6pTDI820l6WVJ3613noj494g4dPiY9ceVdG6uPH2gKvybOXxWvekrzDsg6U95/z4p6VJ5WJTR7B8iYmzlQ8n9DuUuAq4BtiUNN7URaQy6p2huuLJa65KkUXduHW26oSxRGkj+5cL6F0m6WNLf1IgrSfdLuqsq/ARJ11SFvUnSs5ImS5qVy4FvVMXZN4efm3//XdW+WJ6nf7Cw/q9JekTSsrxPti0sbx2lQbKflfSYpCML03aWNE/S05KekPSjYnmSl32SpKfy5+vSyh5UJZ2pNGD6y42UZ+0yWk8SHS0MCmYAS8l9l3UoDRX3srJvtUoHtweQBppt1BF5/74JGAecOtIFyHfUrDVmkLps2C8i7oqIlyPi8Yg4Pne+WrG90jBeyyRdJGldeKXvup/lk//S/P2VMetyYXKCpP8hvdr/hnyBdZ2k5yRdLek7xYI3Fyr/K+kZpWGQppazK6yFuqEseTSve0PS4Nq/B34ladeqeO8GXkM6NosVtOOA10r6Z3ilz7mzgG9ExPwc5w/AP1Wdj2eQyg0AIuJXVfvi/cBy4Moc5QDgY8DfAZuQ+ob8QWF5x5L67twSeA/wBUmVsXk3Jg1qPilPfw74z8K8hwH7AtsBf53X/fHC9N8BnyCNetE1RmsFrFvMAP4V+AvwD8UJkrYt1PiXSPpSDj+26iR+sKQHc63/y1XLqI77t4UT/sNVVwL/Deyi1CEppLsEtwOPFeZfQ9K/5vU9LmmOpFcNt5G5b60fA2/Ly1lH0slKj4KWSPoPSevlaVOVruK+KOkxciaTNE3Sbfnq6A+FjGlWj92AKys93g/hQ6RjfyvSiXxWDl+DdCxuSarI/RH4dtW8B5MKgg2BB4H/InUEvSmpcDm4ElFprLnLga+RCqPPAT+W9OpGNs4sD669KCK+QupV/qSqKDOBy0j9gM0szPciqWJ0Yj4uDyNVeE4ozPsYMB/YE0DSJqQ7yKt1vl21vksi4vn8eyvg+jxw+UvAD4FtCvFnAMdHxNKIuJtUCZyV0/jziPhRHrXiBVLe26VqXafk7X8EOIWVeZeI+E5EXAP8aYj0ls4VsA6R9HekISAuJA1TMaMwbUPgatKVw+uAN5Ien1QvYxvgDNKJ/XWkE33NkeSVehv+OfAt4NXA9sBthSh/Io8kkH/PAOZULWZW/rwHeAOpA9rqQqjWuscDHwR+m4NOIt0V2z5v20RSZ3wVryUVSlsChyn1Tj4H+DzpTtq7gYXDrde6yk9zxf8ZSS3vUboOmwL19PZ9ekQ8mi8a/pt0jFaG+PpxRLwQEc+RCqe/r5r33Ii4MyJWAJsBfwN8JSL+HBHXs2ph9RHgioi4It+NmwfcTOog06xZlwI7SNoAQNL6pA6Hz8+f6UqP5QGIiBuBc0nn2ROAj0XEX6qWOYeV5dR0UmXuRWoorO+8QvCFwBuVHm+uRao0XZnjb0wqw35XiP87UpOBWt4N3Fn4ve0I5u0ao7UC1unCANLB9/OIWEq6Ut5b0mvytPcDj0XEKRHxp4h4LmeQavsDP4uI6/JVzL8Bgw3wehBwdURcEBF/yQXKbVVx5pCGqHgVqXCp3jcHkW5L35/vJBxNysiDPSY8XdIzpMywGDgy397+Z+CzEfF0Lsz+nZUVP/I2HBMRL0bEH0ljqZ0TEfNyYfVIRPx+kHVad9o3Isblz76kkRrWqhFvLdId4VZ7ilQpGs5jhe8vkC4ykLS+pO/lu7/PAtcB4yStWYj/cOH764Cn89V6relbAgcUzkPPkAYhdjvJ3tINZUktj5IG3R6Xf/8jqbL0C+BnpFFw3lc1z7+SLoh/EBE311jmT4CpuXyodYFe9EHgSeD/FcIWA78C7iHdQT4A+GyeNjb/XVaIv4x0N3kVSuNGfoV0QV4xtsa8Y4vtwLrRaK2AdbQwyI/bDiBdiVQGaH0I+HCOsgX1tb16HYWTer7VO9gYdsMuM1+lv5qUEX+WKz/V63uw8PtBUkaeMMgiP5X38cSIOCginsjLXx+4pVDwXJnDK56IiOKt4nr3h/WOh0jDgFROvJW2J1uy6jHWKlcDe1buCDRgNvBmYKeI2Ih0BQ6pkKsoDiuyGNgk3wmoKA6A/DCpoBtX+GwQESc2mD7rjE5fWAxmIul4fCb/nglcHBEr8sX6pRQeQwLk8/0DrHpnqXr65aTyYXxE/M8Q658JzKkacukY0l3hLUjjYX4V+GXOI5WmARsV4m9Eauv1CklvJD3J+XRE/KowaXmNeZe3c8inVhitFbBqZRcG+5EOkO8qve3xGCnDVG7vPgz8VR3LWUzhpJ4P5E0HiVvvMn9IKmxqXd08StonFa8nnXCW1LHciidJVz/bFk5cr8qNNiuqM029abceEREPATcCJ0kaq/QSyudJx9MNhahrSFq38Cm+rLJW1bShXtj4Aek4+rGkt+T2jJsqddVSz2O/DUnH7TO5/csxw2zfg6RHisdKWlvSO1m1necPgX+QtKekNXP6p6rQsN96UtllyWD2A26NiOfzMfVe4COF8mZ/YB+NvAuWOaTy4QeDRZC0BWmcxeoyZDvgotxOa0VEnEtqa7ZNfhK0OMcpxn+lMihpS9KF1PERUb3+O4eat1u5AkZHCoOZwDnAZFIbk+1JDQq3lzSZdIv4tZI+kxusbyhppxrLuQR4v1Lj+rVJb7MM9j89H9hN0ockjcmFz/Y14p0O7E56xFLtAuCzSm93jSU9Orwot3mpS0S8TGpceWrlkaukiZL2HGK2s4GPSto1F5wTJb2l3nVa1/on0ltZC4BHgF2Bfarufh5IqvhUPsU7oVdUTTt2sBXlq/7dSG+IzQOeJTWQH0/K+8P5JrAe6QLiBla+2TWUg4B3ku5Kfw24iNxmJiIeBqaRBtR+glQ5/Dw+J/e0DpQlr1AyUdIxwKGkYwtSG+F7SXdwK+XNm4BFpPw1Ev+PVD58a4g4BwP/GxHVTy1uIj12n5DP4weT7gwuyNPnAP+q9MbxW0hNVc7N2zYR+CXwnag9WPYcUhOXiZJeR6oknluZmC+C1iXdsa7s387ntYgYVR9S4+3daoRvAfyI1AbkSdLo9tsUph9LujNT/CwqLLN62tcGWf9EUmacXGPaFcDJ+fvbSA3vl+Y0HVVIxw8L88wkXXU9BXy5uH014v4d6eTwLOmEPzOHnztEeq8HZuXva5CevT9MKjR+CGycp03K2z0m/x4ADh1kmeuSKm/357TcTXpcCenKaVGNefYjvZX5HCnD7tnpY8kff0byIVXAvtrpdPjTsv9nR8uSHH8qqc3scuB50lOKS4CdC3F+D3yyxrxfAG6uClvtvE168er6Qdb/NdLLJ1St75AacdcFvkO60/UsqUuIvQrT1yHdmHiW9FTlyMK0Y/K+WF78FKYL+DrwdP58HVDVdlXv16mdPoaUE2dmZi2k1NfS06R2NXuQXmp5Z0T8dsgZzWxU6PwtOLM+oNSD8+OS7iiEHavU6/Nt+bNPYdrRSkPh3FN8/Cpprxy2QNJRZW9HL8vtuap74l4u6ecdStJrSVfey0mP9v/FlS8zq/AdsDZR6jj1SzUm/Soi9i47PdZekt5NKmjnRESlw9ljSbfJT66Kuw2pPd2OpDdLrya1yYDUVmN3UvuMm4ADI2KVoUPMbPRwWdK/PMxLm0TEv5PaOdkoEBHXSZpUZ/RpwIWRGoY/IGkBK8cjXBAR9wNIujDHdQXMbJRyWdK/uroCNn78+Jg0aVLNac8//zwbbNBolz69abRtc5nbe8sttzwZEe0YBuYISTNIXRLMjvS69URWfSNqUQ6DVTvrXATUevsVSYeRhgxhvfXWe8cWW2xRK1pfePnll1ljjdHVWqJbt/nee+9tVz5pq/Hjx8erX/3qnj5/9vr5v5fTP5K0j6Qs6eoK2KRJk7j55lod8sLAwABTp04tN0EdNtq2ucztldSOPnrOAI4nvXFzPGl8so+xauedFUHtNpk12whExJmkwWmZMmVKDJZP+sFoO+6he7e5Tfmk7SZNmsTJJ5/clfu0Xt16TNSrl9M/krSPJI90dQXMrJdFxCsd1Eo6i9S/G6Q7W8VbVpuTXh9niHAzM+sj3XeP26xPSCqO67cfUHlDci5pDM11JG0FbE3qFPQmYOvc0e3apPExiwM4m5lZn/AdMLMWkHQBqVPE8ZIWkToOnJpHGwhSB4sfB4iIOyVdTGpcvwI4PCJeyss5gtRx45qkAci7fjgNMzMbuZ6tgM1/ZBmzjrq8oXkXnlg9CLxZcyKi1pAeZw8R/wTghBrhV5BGRBhVJg2Rl2dPXjFoXndeNmufofLlUJwv6+NHkGZmZmYlcwXMzMzMrGSugJmZmZmVzBUwMzMzs5K5AmZmZh0l6bOS7pR0h6QLJK2bu2O5UdJ9ki7KXbOQu2+5KA9Yf+MIhgAz6yrDVsAknSPpcUl3FMI2kTQvZ4x5kjbO4ZJ0es4Yt0vaoTDPzBz/Pkkz27M5ZmbWSyRNBD4FTMkD2a9J6gPvJODUiNgaWAockmc5BFgaEW8ETs3xzHpOPXfAzgX2qgo7CrgmZ4xr8m+AvUmdSm5NGqfuDEgVNlK/SDuRBh0+plJpMzOzUW8MsJ6kMcD6wGLgvcAlefp5wL75+7T8mzx9V0m1hvcy62rD9gMWEdfVuMU7jdTpJKSMMAB8MYfPiYgAbpA0LvcGPhWYFxFPA0iaR6rUXdD0FpiZWc+KiEcknQw8BPwR+AVwC/BMRKzI0YoD1k8kD1ofESskLQM2BZ4sLrc4YP2ECRNYvnw5AwMDbd6a9ulE+mdPXjF8pBpqpbOX93+70t5oR6wTImIxQEQslvSaHP5KxsgqmWaw8NVUZ5rBNnrCeq09OHpBLx/AjRht22s2GuWnIdOArYBngB+RnqZUqwxMP9hg9qsGVA1YP3bs2J4dDBo6M5h1w52dHzR1tbDRMhj3SLS6J/zBMkZdGQZWzzSDbfS3zr+MU+Y3lvxaB0cv6OUDuBGjbXvNRqndgAci4gkASZcC7wLGSRqT74IVB6avDGa/KD+yfBXwdPnJNmtOo29BLqkMNJz/Pp7DKxmjopJpBgs3M7PR7SFgZ0nr57Zcu5LGSb0W2D/HmQlclr/Pzb/J03+Zm72Y9ZRGK2DFDFCdMWbktyF3BpblR5VXAXtI2jjfbt4jh5mZ2SgWETeSGtPfCswnlUtnktoVHylpAamNV2Vs1bOBTXP4kax8Ccyspwz7DE/SBaRG9OMlLSK9zXgicLGkQ0hXLwfk6FcA+wALgBeAjwJExNOSjgduyvGOqzTINzOz0S0ijiGVLUX3k96ar477J1aWOWY9q563IA8cZNKuNeIGcPggyzkHOGdEqTMzMzPrQ+4J38zMzKxkroCZmZmZlcwVMDMzM7OSuQJmZmZmVjJXwMzMzMxK5gqYmZmZWclcATMzMzMrmStgZmZmZiVr9WDcZmZm1kUmHXV5p5NgNfgOmJmZmVnJXAEzMzMzK5krYGZmZmYlcwXMzMzMrGSugJmZmZmVzBUwsxaQdI6kxyXdUQjbRNI8SfflvxvncEk6XdICSbdL2qEwz8wc/z5JMzuxLWZm1n4Nd0Mh6c3ARYWgNwBfAcYB/ww8kcO/FBFX5HmOBg4BXgI+FRFXNbp+sy5zLvBtYE4h7Cjgmog4UdJR+fcXgb2BrfNnJ+AMYCdJmwDHAFOAAG6RNDcilpa2FT2m0dfrF574vhanxJohaRzwfeBtpGP/Y8A9pDJmErAQ+FBELJUk4DRgH+AFYFZE3NqBZJs1peEKWETcA2wPIGlN4BHgJ8BHgVMj4uRifEnbANOBbYHXAVdLelNEvNRoGsy6RURcJ2lSVfA0YGr+fh4wQKqATQPmREQAN0gaJ2mzHHdeRDwNIGkesBdwQZuTb9ZppwFXRsT+ktYG1ge+xAguYDqTbKul1oXR7MkrmDXMBdNouzBqVUesuwJ/iIgH08VJTdOACyPiReABSQuAHYFftygNZt1mQkQsBoiIxZJek8MnAg8X4i3KYYOFr0bSYcBhABMmTGBgYKC1KS/Z7MkrBp02Yb2hpzei2/fX8uXLuz6NrSJpI+DdwCyAiPgz8GdJI7qAqeQ1s17RqgrYdFa9Sj9C0gzgZmB2foQyEbihEKdm4VJvwdLMSblXT2yj6aQMfb29ta5SYojw1QMjzgTOBJgyZUpMnTq1ZYnrhKGujGdPXsEp81s7aMfCg6a2dHmtNjAwQK//T0fgDaQmK/8paTvgFuDTjPwCZpUKWHVZ0uvnk2bS3+oLmEbUU2Z36/+nXcdO02e1fLv4A8DROegM4HhSwXE8cArpeX5dhUu9Bcu3zr+s8ZPy/Ocbmq3Tt0dH2Um5H7Z3SeXKPD9ifDyHLwK2KMTbHHg0h0+tCh8oIZ1mnTQG2AH4ZETcKOk00uPGwTRUlowdO7anzyfNnA+He/RXhnoupLr1wqhdZVEr3oLcG7g1IpYARMSSiHgpIl4GziI9ZoTBCx2zfjUXqLzJOBO4rBA+I78NuTOwLF/pXwXsIWnj/MbkHjnMrJ8tAhZFxI359yWkCtmSfOFCnRcwZj2lFRWwAyk8fqxkmGw/oPJa/lxguqR1JG1FakD5mxas36zjJF1Aas/4ZkmLJB0CnAjsLuk+YPf8G+AK4H5gAeki5RMAufH98cBN+XNcpUG+Wb+KiMeAh/Ob9ZDaFN/FyC9gzHpKU48gJa1PKlg+Xgj+uqTtSbeEF1amRcSdki4mZawVwOF+A9L6RUQcOMikXWvEDeDwQZZzDnBOC5Nm1gs+CZyfm7TcT3qbfg3g4nwx8xBwQI57BakLigWkbig+Wn5yzZrXVAUsIl4ANq0KO3iI+CcAJzSzTjMz6y8RcRup/7tqI7qAMesl7gnfzMzMrGSugJmZmZmVzBUwMzMzs5K5AmZmZmZWMlfAzMzMzErmCpiZmZlZyVwBMzMzMyuZK2BmZmZmJXMFzMzMzKxkroCZmZmZlcwVMDMzM7OSuQJmZmZmVjJXwMzMzMxK5gqYmZmZWclcATMzMzMr2ZhmZpa0EHgOeAlYERFTJG0CXARMAhYCH4qIpZIEnAbsA7wAzIqIW5tZf9kmHXV5Q/MtPPF9LU6JmVl/kbQmcDPwSES8X9JWwIXAJsCtwMER8WdJ6wBzgHcATwH/FBELO5Rss4a14g7YeyJi+4iYkn8fBVwTEVsD1+TfAHsDW+fPYcAZLVi3mZn1h08Ddxd+nwScmsuSpcAhOfwQYGlEvBE4Nccz6znteAQ5DTgvfz8P2LcQPieSG4BxkjZrw/rNzKyHSNoceB/w/fxbwHuBS3KU6rKkUsZcAuya45v1lKYeQQIB/EJSAN+LiDOBCRGxGCAiFkt6TY47EXi4MO+iHLa4uEBJh5HukDFhwgQGBgZqrnjCejB78oomk1+OwbZhpJYvX96yZfWC0ba9ZqPYN4EvABvm35sCz0RE5SRfKS+gUJZExApJy3L8J4sLrC5Lev180kz6u6GsrKfM7tb/T7uOnWYrYLtExKO5kjVP0u+HiFvrCiVWC0iVuDMBpkyZElOnTq25sG+dfxmnzG82+eVYeNDUlixnYGCAwfZHPxpt22s2Gkl6P/B4RNwiaWoluEbUqGPayoCqsmTs2LE9fT5p5nw4q8H2y600e/KKYcvsVpWVrdausqipGkxEPJr/Pi7pJ8COwBJJm+W7X5sBj+foi4AtCrNvDjzazPrNzKzn7QJ8QNI+wLrARqQ7YuMkjcl3wYrlRaUsWSRpDPAq4Onyk12+Rl8Es+7UcBswSRtI2rDyHdgDuAOYC8zM0WYCl+Xvc4EZSnYGllUeVZqZ2egUEUdHxOYRMQmYDvwyIg4CrgX2z9Gqy5JKGbN/jr/aHTCzbtfMHbAJwE9y28cxwH9FxJWSbgIulnQI8BBwQI5/BakLigWkbig+2sS6zcysv30RuFDS14DfAmfn8LOBH0haQLrzNb1D6TNrSsMVsIi4H9iuRvhTwK41wgM4vNH1mZlZf4uIAWAgf7+f1KylOs6fWHlhb9az3BO+mZmZWclcATMzMzMrmStgZmZmZiVzBcyszSQtlDRf0m2Sbs5hm0iaJ+m+/HfjHC5Jp0taIOl2STt0NvVmZtYOroCZlcNjppqZ2StcATPrDI+ZamY2ivXGWD5mva1jY6b2iqHGiGvHuK/dvr96fdxCMxueK2Bm7dexMVN7xVBj1dUzhtxIdeuYcxUeB9Ws//kRpFmbFcdMBVYZMxXAY6aamY0+vgNWgkYHUF144vtanBIrWx4ndY2IeK4wZupxrBzP7kRWH+fuCEkXAjvhMVPNzPqSK2Bm7eUxU83MbDWugJm1kcdMNTOzWtwGzMzMzKxkroCZmZmZlcwVMDMzM7OSNdwGTNIWwBzgtcDLwJkRcZqkY4F/Bp7IUb8UEVfkeY4GDgFeAj4VEVc1kXYzM+txQ5QlmwAXAZOAhcCHImKp0hstp5FeVnkBmBURt3Yi7dZao63HgGbugK0AZkfEW4GdgcMlbZOnnZrHvdu+UPnaBpgObAvsBXxX0ppNrN/MzHrfYGWJx0u1vtZwBSwiFleuOiLiOeBu0pApg5kGXBgRL0bEA6TX7HdsdP1mZtb7hihLPF6q9bWWdEMhaRLwduBGYBdSR5IzgJtJVzZLSRnqhsJslTHuqpdV1xh37RgfrttUb/toGx9utG2v2WhXVZa0dLzUXj+fLF++nNmTX+p0MhrWzjK73f/Xdh07TVfAJI0Ffgx8JiKelXQGcDxp/LrjgVOAj9HiMe6+df5lLR8frttUj1c32saHG23bazaa1ShLBo1aI2zYsmTs2LE9fT4ZGBjglOuf73QyGtaOMV0r2j22a7vKoqbegpS0FinDnB8RlwJExJKIeCkiXgbOYuVjRo9xZ2Zmq6lVluDxUq3PNVwBy2+inA3cHRHfKIQXn8XvB9yRv88FpktaR9JWpAaUv2l0/WZm1vsGK0tYOV4qrD5e6gwlO+PxUq1HNXM/cBfgYGC+pNty2JeAAyVtT7olvBD4OEBE3CnpYuAu0lsvh0dE7z7QNjOzVhisLDkRj5dqfazhClhEXE/tZ/FXDDHPCcAJja7TzKwVGu1vCHq3z6FuNURZAh4v1fpYf7di73HVhcTsySuYVUfB4QLCOqWZio2Z2WjioYjMzMzMSuY7YGZmZiVq5E5x6kPLRXY/8R0wMzMzs5K5AmZmZmZWMlfAzMzMzErmCpiZmZlZyVwBMzMzMyuZK2BmZmZmJXMFzMzMzKxk7lTEzMzMelajI3B0etQYV8D6UK8ejGZmZqOFH0GamZmZlcwVMDMzM7OS+RGkmZlZAxpt7mEGvgNmZmZmVrrS74BJ2gs4DVgT+H5EnFh2Gqw2N97vDt2QR3xlPzjnk+7QqnziY906pdQKmKQ1ge8AuwOLgJsk1nV5VQAAIABJREFUzY2Iu8pMh7WWC6TWcR4xG57zibVCvWXX7MkrmFWI26qyq+w7YDsCCyLifgBJFwLTAGeaUWi4g7/6oG9Wj1T4WppHfHXfPUbyv2jFsd8jx3ujXJZYz1NElLcyaX9gr4g4NP8+GNgpIo4oxDkMOCz/fDNwzyCLGw882cbkdqPRts1lbu+WEfHqktY1qHrySA6vN5/0g9F23EP3bnPP5JMaeeQpunOf1qtbj4l69XL6R5L2uvNI2XfAVCNslRpgRJwJnDnsgqSbI2JKqxLWC0bbNo+27c2GzSNQfz7pB6PxOBiN2zxCIy5Len2fOv2d0660l/0W5CJgi8LvzYFHS06DWTdzHjEbnvOJ9byyK2A3AVtL2krS2sB0YG7JaTDrZs4jZsNzPrGeV+ojyIhYIekI4CrSq8PnRMSdDS5uVDx+qTLatnm0bW+r80i/GHXHAaNzm+vWYD7p9X3q9HdOW9JeaiN8MzMzM3NP+GZmZmalcwXMzMzMrGQ9WQGTtJekeyQtkHRUp9PTapK2kHStpLsl3Snp0zl8E0nzJN2X/27c6bS2kqQ1Jf1W0s/y760k3Zi396Lc2NZGkX7P6zB683u79fL5RNI4SZdI+n0+Lt7ZS8eDpM/mY/kOSRdIWreb97+kcyQ9LumOQljN/a3k9HxOul3SDo2ut+cqYIUhKPYGtgEOlLRNZ1PVciuA2RHxVmBn4PC8jUcB10TE1sA1+Xc/+TRwd+H3ScCpeXuXAod0JFXWEaMkr8Poze/t1svnk9OAKyPiLcB2pO3oieNB0kTgU8CUiHgb6SWJ6XT3/j8X2KsqbLD9vTewdf4cBpzR6Ep7rgJGYQiKiPgzUBmCom9ExOKIuDV/f46U+SaStvO8HO08YN/OpLD1JG0OvA/4fv4t4L3AJTlKX22v1aXv8zqMzvzebr18PpG0EfBu4GyAiPhzRDxDbx0PY4D1JI0B1gcW08X7PyKuA56uCh5sf08D5kRyAzBO0maNrLcXK2ATgYcLvxflsL4kaRLwduBGYEJELIZ00gZe07mUtdw3gS8AL+ffmwLPRMSK/Luv/89W06jK6zCq8nu79fL55A3AE8B/5keo35e0AT1yPETEI8DJwEOkitcy4BZ6Z/9XDLa/W3Ze6sUKWF1DtfQDSWOBHwOfiYhnO52edpH0fuDxiLilGFwjal/+n21Qo+oYGC35vd364HwyBtgBOCMi3g48T5c+bqwlt5WaBmwFvA7YgPTYrlq37v/htOxY6sUK2KgYgkLSWqST8fkRcWkOXlK51Zn/Pt6p9LXYLsAHJC0kPWZ6L+kKdly+hQ19+n+2IY2KvA6jLr+3W6+fTxYBiyLixvz7ElKFrFeOh92AByLiiYj4C3Ap8C56Z/9XDLa/W3Ze6sUKWN8PQZHbK5wN3B0R3yhMmgvMzN9nApeVnbZ2iIijI2LziJhE+n/+MiIOAq4F9s/R+mZ7rW59n9dh9OX3duv180lEPAY8LOnNOWhX4C5653h4CNhZ0vr52K6kvyf2f8Fg+3suMCO/DbkzsKzyqHKkerInfEn7kK5oKkNQnNDhJLWUpL8FfgXMZ2Ubhi+R2oVcDLyedJAfEBHVDQd7mqSpwOci4v2S3kC6gt0E+C3wkYh4sZPps3L1e16H0Z3f261XzyeStie9QLA2cD/wUdINk544HiR9Ffgn0hu+vwUOJbWT6sr9L+kCYCowHlgCHAP8lBr7O1cqv016a/IF4KMRcXND6+3FCpiZmZlZL+vFR5BmZmZmPc0VMDMzM7OSuQJmZmZmVrJRWQGTtFDSHyUtL3w+LGlRjbgDkg7N34+V9MMhlrnbCNOxoaRv5Hmfl/RQHv9rx0KcyNOKaf1CYfo2kuZKWibpOaUx5d5VmD4pL6My70JVjamXx7z6SV7Pg5I+XJj2HknzJT0j6akcb2Jh+jpK42g9K+kxSUcWpq2dt2dhTsPUqvVK0kl5uU9J+npu4FiZfqbSOIAvS5o1kn1rjeui/DFO0hn5uHohH4cfrRFvVp72Qo57hqRxhenHSvpLYVvulvTBwvSp+fi8tGq52+XwgULY9pJ+lfPbIklfKUyrzmvLJf1bYXrb8koh3sw8/6Ej2dfWffKxsESpE9ZK2KGS7q86xqrLiL8bYpnnSvpz1fy/y9NqHb+/K8y7maSzJS1WKmt+L+mrlfRJOj7nwxWSjq1aryR9WamMe1bShUo9/g+VrjVbuDu70qisgGX/EBFjKx9K7pNE0jrAL4HJwPuBjYC3kt4S2acq+nbFtEbE1/My/gr4H9LbU5VO734C/ELSO6uWMS5v5/7Av0navTDtO8CfgQnAQcAZkrbN0+4C9oyIcXn597Hq2FfHksbE2hJ4D/AFScUxta4HPgI8VmM3HEYa3mE74K/zfvh4YfrvgE8At9aY19qr0/ljbeBq0nH1TuBVwOeBE6sqLrNJY8x9PsfZOc8zT6sO9ntRYVs+A/xQ0oTC9CeAd0natBA2E7i3Kmn/BVxHepPr74F/kfSBqjjjCvvu+EL4sbQvr1Q6wDwauLPG/NabxpDGtCx6qCpvwqplxK+GWebXq8qT7aqmj6ueJmkT4NfAesA7I2JDYHdgHPBXeb4FpNEHLq+xzhnAwaQ+2l6Xl/OtYdL10jDb0fNGcwWs0w4mdeC2b0TcEREvRcTzEXFJRBxb5zKOBX4dEV+OiKcj4rmIOB34AalQWk1+XfZOYHuAfPXyQeDfImJ5RFxP6ufk4Bx/SUQUC9+XgDcWfs8Ajo+IpRFxN3AWMCvP++eI+GZeZq3MNBM4JSIW5eErTqnMm+f/TkRcA/ypzv1h/eNg0uvfB0TEAxHxl4i4kjTI73GSNspX0F8FPhkRV+Y4C4EPkSo5H6m14Ii4CniOlQUHpAuQn5L6jaoMBP4h4Pyq2SeROkt9KSL+QKo0bUt92pZXsv8POB14ss70WPf7v8Dnind0O+RIUp75SM5jRMTDEfHpiLg9/z4vIn6e41X7B+DsPM9yUvn0T5LWLyf53ckVsM7ZDbgqIp5vYhm7Az+qEX4xsEutg1up47i3ka5WAN4EvBQRxSv931EoVCS9XtIzwB+BzwGVO3Abk65mfjfYvMPYtol5rb/tDvy8Rv74MbAu6a7Yu/L3VR4d5hP8z/MyVpEfhbyP1L/SXVWT55AqSQB7ki5Uqu/8fZPUCeNaSh1lvpN0p67owfx48j8ljc/rbWteUWq2MAX4jzqXZ73hZmCAdN7tpN2ASyPi5WFj1iZWHcJHwDqkO8IVn5D0tKRbVGgi0M9GcwXsp0rtmp6R9NMOrH88hUcNSm1LnsnPx++pintrIa3PSNqzsIxaPfAuJv1vNy6EPSnpj6TbyN8lXe0DjCUNllq0DNiw8iMiHsqPIMcD/wr8vjBvJX7NeYdRve5lwNhabVusdN2QP1Y7tiMN5vtknj4eeDJWDvBbtDhPr/hQvoh4nnSH998j4pmqZf8vsEmuWM0gVciq/Yz0GP+PpHxwdkTclKc9CfwN6e7bO0j5oHIHrW15Jd+t+y7pTmCjBaR1r68An5T06hYt73NV5cl5VdOfLEyrVPw2pXZZU6+fA4fmdmavAr6Ywys3CU4nVcZeA/wbcK6kXZpYX08YzRWwfSNiXP7sS+qxd60a8dYC/tKG9T8FbFb5ERG35UrOP5KuDIp2KKR1XH6EAumEvxmr24zUo/bSQth40kn8c6QefyvbupzU/qxoI2rcRs69Lp8HXKY0ptfyQvwh5x1E9bo3ApaHewfuBp3OHzWP7Xzcjc/TnwTGa+X4ckWbseqjuIvztqxPevQ4Q9LHa8z3A+AIUhutn1StexPgSuA40p23LYA9JX0C0p23iLg5IlZExJK8nD3yo9J25pVPALdHxK/rXJb1kIi4g1Txb9WA3CdXlSczq6aPL0w7OYetUl414BzgAtLdvDtJwxJBGleRiLg1Ip7KeecK0oXLPzaxvp4wmitg1R4incwrV6qVMdq2BB5sw/quIZ2cNxg25uCuBg6oEf4hUtuwF4qBud3KKaQ2VZ/IwfcCYyQVbwVvx+ANeceQrlI2ioilpKuiYiPOoeatdmcT81q5ys4fVwN718gfHwReBG4g3c19kaoTdZ5nb1IeW01uw/JzUruUaj8g5Y0rqvMP8AbS4/o5uaBYRO2XZl5ZVSVJbc4ruwL7Kb1Z+Rjp0ewpkr5d57Kt+x0D/DNpOJ9OuJp0jDVUZ4iIlyPimIiYFBGbk47dR/Kn5iys+siyL7kClkXEQ6Sx106SNDa/pfh50pX/DYWoa0hat/Ap3q1aq2parSvzijmkE/JPJL1N0pqS1iW146jXV0lvbp2g1JXEhpI+SXp88sUh5juR9AbWurmNzaWkhs0b5Nu+00gFEZL+UdKbJa2Rb4F/A/htrByDbA7wr5I2lvQW0kni3MqKlF69Xzf/XDvvFxXmPVLSREmvA2ZXzbt2nles3Lc+ZjugA/njB6Sr4x/lxxZr5UfvpwPHRsSyiFhGygPfkrRXjjOJ1C5yUV7GaiRtThrHbbXKT0Q8QHq78cs1Zr03za4P5/zwWtJ4d5XX+Hcq5JVNc1oHcjqhfXllFukN6u3z5+a8X2ptg/WgiFgAXER6CaUTvkG663qepC0B8rH4DUl/nX+vlY/fNUgX9evmx+OVro7+Kj8y3yYv77jKI3NJ++fzyhqS9iC9QDO3/M0sWUSMug+wENitRvgWpJP3Y6THF1cB2xSmH0uqmRc/iwrLrJ72tWHS8SpSo94HSW1THiQ1Mt6xECfytOWFzzcL099Guj39bJ42APxtYfqkvIwxhTCRCp9P5t+bkNqEPU+60/HhQtxPAg/kaY+Rrvi3LExfh3R7+VnSIKZH1tjX1ftlUiEdXweezp+vk8cnzdMHasw7tdPHT79/uih/bAJ8Lx9Xf8zH7KE14h0C3JHjLMnzbFyVrr8U8s9iUmP19fP0qZV01lj2oaRKVOX3e4GbSG2wHiO9yVhZzoGFvLKYVGl6bRl5pWo5A7X2kz+99anOhzn//al4PObwAN5Y5zLPJb3xWyxPnszTJlFVVlTN+7p8/D5GenT+e9KdufULy64+fmflaW8C7iENXv1gjWP/VzlPPUu6oJne6f1fxseDcZuZmZmVzI9zzMzMzErmClgbSfqSVh1aofL5eafTZtZpzh9mrSfpzkHy1UGdTputyo8gzczMzEo21FtIHTd+/PiYNGlSy5f7/PPPs8EGzfT+UJ5eSWuvpBNqp/WWW255MiJa1dFhqUaST3rp/zScftmWXtqOXs0nQ+WRbtv/3ZQep6W2odIyojzS6bcAhvq84x3viHa49tpr27LcduiVtPZKOiNqpxW4ObrgmG/kM5J80kv/p+H0y7b00nb0aj4ZKo902/7vpvQ4LbUNlZaR5BG3ATMzMzMrmStgZmZmZiVzBczMzMysZF3dCL9fTDrq8obmW3ji+1qcEjNrlvNzf5n/yDJm+X9qHeA7YGZmZmYlcwXMzMzMrGSugJmZmZmVzBUwMzMzs5K5AmZmZmZWMlfAzMzMzErmbijMbNRptCsJM7NW8R0wMzMzs5K5AmZmZmZWMj+C7GKTjrqc2ZNXjLiXZvfObGZm1t18B8zMzMysZK6AmZmZmZXMFTCzNpP0WUl3SrpD0gWS1pW0laQbJd0n6SJJa+e46+TfC/L0SZ1NvZmZtcOwFTBJ50h6XNIdhbBNJM3Lhcc8SRvncEk6PRcet0vaoTDPzBz/Pkkz27M5Zt1F0kTgU8CUiHgbsCYwHTgJODUitgaWAofkWQ4BlkbEG4FTczwzM+sz9dwBOxfYqyrsKOCaXHhck38D7A1snT+HAWdAqrABxwA7ATsCx1QqbWajwBhgPUljgPWBxcB7gUvy9POAffP3afk3efquklRiWs3MrATDvgUZEdfVeAwyDZiav58HDABfzOFzIiKAGySNk7RZjjsvIp4GkDSPVKm7oOktMOtiEfGIpJOBh4A/Ar8AbgGeiYgVOdoiYGL+PhF4OM+7QtIyYFPgyeJyJR1GushhwoQJDAwM1JWe5cuX1x232zWzLbMnrxg+UosNltZ++p+YWf0a7YZiQkQsBoiIxZJek8NfKTyySsEyWPhqGi1YRqLsE14zJ/sJ6418/k6czHupECkzrflO7zRgK+AZ4EekO8XVojLLENNWBkScCZwJMGXKlJg6dWpd6RkYGKDeuN2umW0ZadcurbDwoKk1w/vpf2Jm9Wt1P2CDFR51FSrQeMEyEmWf8Jo52c+evIJT5o/s3zTYib6deqkQKTmtuwEPRMQTAJIuBd4FjJM0Jt8F2xx4NMdfBGwBLMqPLF8FPF1WYs3MrByNvgW5JD9aJP99PIdXCo+KSsEyWLhZv3sI2FnS+rkt167AXcC1wP45zkzgsvx9bv5Nnv7L/EjfzMz6SKMVsGIhUV14zMhvQ+4MLMuPKq8C9pC0cX4ks0cOM+trEXEjqTH9rcB8Up47k9Rm8khJC0htvM7Os5wNbJrDj2TlCy5mZtZHhn22JekCUiP68ZIWkd5mPBG4WNIhpCv8A3L0K4B9gAXAC8BHASLiaUnHAzfleMdVGuSb9buIOIaUb4ruJ70RXB33T6zMT2Zm1qfqeQvywEEm7VojbgCHD7Kcc4BzRpQ6MzMzsz7knvDNzMzMSuYKmJmZmVnJXAEzMzMzK5krYGZm1naStpB0raS78+D0n87hHlvYRiVXwMzMrAwrgNkR8VZgZ+BwSdvgsYVtlHIFzMzM2i4iFkfErfn7c8DdpCHpigPQVw9MPyeSG0ijR2wG7EkeWzgilgKVsYXNekqrhyIyMzMbkqRJwNuBG2nT2ML1jivcyHi7Ff0wVvFQnJbaWpUWV8DMzKw0ksYCPwY+ExHPphG6aketEVb32ML1jiv8rfMvG/F4uxXtGHe3m8bVdVpqa1Va/AjSzMxKIWktUuXr/Ii4NAd7bGEblVwBMzOztsuD0Z8N3B0R3yhM8tjCNir5EaSZmZVhF+BgYL6k23LYl/DYwjZKuQJmZmZtFxHXU7v9FnhsYRuF/AjSzMzMrGQNV8AkvVnSbYXPs5I+I+lYSY8UwvcpzHN07tX4Hkl7tmYTzLqbpHGSLpH0+9wL+Dsb6f3bzMz6R8MVsIi4JyK2j4jtgXeQntH/JE8+tTItIq4AyD0eTwe2JXWa911JazaXfLOecBpwZUS8BdiO1AHliHr/NjOz/tKqR5C7An+IiAeHiDMNuDAiXoyIB0gNK3ds0frNupKkjYB3k97+IiL+HBHPMPLev83MrI+0qhH+dOCCwu8jJM0AbiaN/bWU1FPxDYU4TfVe3Iyye9RttJdlaKyX5k70FtxNvRQPp+S0vgF4AvhPSdsBtwCfZuS9fy8uLrTRfNJL/6fhNLMtzeTJRg2W1n76n5hZ/ZqugElaG/gAcHQOOgM4ntQz8fHAKcDHaHHvxc0ou0fdWUdd3vC8syevGHEvze3onXk43dRL8XBKTusYYAfgkxFxo6TTWPm4sZa25pNe+j8Np5ltaSZPNmqwfNlP/xMzq18rHkHuDdwaEUsAImJJRLwUES8DZ7HyMaN7L7bRaBGwKCJuzL8vIVXIRtr7t5mZ9ZFWVMAOpPD4saq9yn7AHfn7XGC6pHUkbUVqZPybFqzfrGtFxGPAw5LenIN2Be5i5L1/m5lZH2nqEaSk9YHdgY8Xgr8uaXvSY5OFlWkRcaeki0mFzwrg8Ih4qZn1m/WITwLn58f195N69F6DEfT+bbVN6sCjRDOzVmiqAhYRLwCbVoUdPET8E4ATmlmnWa+JiNuAKTUmjaj3bzMz6x/uCd/MzMysZK6AmZmZmZXMFTAzMzOzkrkCZmZmZlYyV8DMzMzMSuYKmJmZmVnJXAEzMzMzK5krYGZmZmYlcwXMzMzMrGSugJmZmZmVzBUwMzMzs5K5AmZmZmZWMlfAzMzMzErWVAVM0kJJ8yXdJunmHLaJpHmS7st/N87hknS6pAWSbpe0Qys2wKwXSFpT0m8l/Sz/3krSjTmfXCRp7Ry+Tv69IE+f1Ml0m5lZe7TiDth7ImL7iJiSfx8FXBMRWwPX5N8AewNb589hwBktWLdZr/g0cHfh90nAqTmfLAUOyeGHAEsj4o3AqTmemZn1mXY8gpwGnJe/nwfsWwifE8kNwDhJm7Vh/WZdRdLmwPuA7+ffAt4LXJKjVOeTSv65BNg1xzczsz4ypsn5A/iFpAC+FxFnAhMiYjFARCyW9JocdyLwcGHeRTlscXGBkg4j3SFjwoQJDAwMNJnE1S1fvrwtyx3M7MkrGp53wnojn7/Mbasoe582owNp/SbwBWDD/HtT4JmIqPxjK3kBCvkkIlZIWpbjP1lcYKP5pJf+T8NZvnw5sye/1Olk1G2w/d5P/xMzq1+zFbBdIuLRXMmaJ+n3Q8StdRUfqwWkStyZAFOmTImpU6c2mcTVDQwM0I7lDmbWUZc3PO/sySs4Zf7I/k0LD5ra8PoaVfY+bUaZaZX0fuDxiLhFUmWlQ+WFtuaTXvo/DWdgYIBTrn++08mo22D5sp/+J2ZWv6YqYBHxaP77uKSfADsCSyRtlu9+bQY8nqMvArYozL458Ggz6zfrAbsAH5C0D7AusBHpjtg4SWPyXbBiXqjkk0WSxgCvAp4uP9lmZtZODbcBk7SBpA0r34E9gDuAucDMHG0mcFn+PheYkd+G3BlYVnlUadavIuLoiNg8IiYB04FfRsRBwLXA/jladT6p5J/9c/zV7oCZmVlva6YR/gTgekm/A34DXB4RVwInArtLug/YPf8GuAK4H1gAnAV8ool1m/W6LwJHSlpAauN1dg4/G9g0hx/JyreIzXqapHMkPS7pjkLYiLstkjQzx79P0sxa6zLrBQ0/goyI+4HtaoQ/BexaIzyAwxtdXzeY1ERbLrOIGAAG8vf7SY/sq+P8CTig1ISZleNc4NvAnEJYpduiEyUdlX9/kVW7LdqJ1G3RTpI2AY4BppDaRt4iaW5ELC1tK8xaxD3hm5lZ20XEdazennGk3RbtCcyLiKdzpWsesFf7U2/Wes2+BWlmZtaokXZbNFj4aurtqqWRrn4q+qGbpKE4LbW1Ki2ugJmZWbcZrDuWurppgfq7avnW+ZeNuKufinZ0+dNN3ZI4LbW1Ki1+BGlmZp2ypDIiSp3dFrk7I+sbroCZmVmnjLTboquAPSRtnN+Y3COHmfUcP4I0M7O2k3QBMBUYL2kR6W3GE4GLJR0CPMTKN4CvAPYhdVv0AvBRgIh4WtLxwE053nER4Y6KrSe5AmZmZm0XEQcOMmlE3RZFxDnAOS1MmllHuAJmZlaCwfoRnD15xZDjxS488X3tSpKZdZDbgJmZmZmVzBUwMzMzs5K5AmZmZmZWMlfAzMzMzErmCpiZmZlZyfwWpFkbSdoCmAO8FngZODMiTpO0CXARMAlYCHwoIpZKEnAaqQ+kF4BZEXFrJ9JepsHeEBxKGr/PpzAz600N3wGTtIWkayXdLelOSZ/O4cdKekTSbfmzT2GeoyUtkHSPpD1bsQFmXW4FMDsi3grsDBwuaRvgKOCaiNgauCb/Btgb2Dp/DgPOKD/JZmbWbs1cPlYKllslbQjcImlennZqRJxcjJwLnenAtsDrgKslvSkiXmoiDWZdLQ+fsjh/f07S3cBEYBqpV3CA84AB4Is5fE7uiPIGSeMkbZaXY2ZmfaLhCtgQBctgpgEXRsSLwAOSFgA7Ar9uNA1mvUTSJODtwI3AhEqlKiIWS3pNjjYReLgw26IctkoFTNJhpDtkTJgwgYGBgbrSsHz58rrjlik9ThyZCes1Nl+3GW47uvH/ZWbNa0kDiqqCZRfgCEkzgJtJd8mWkgqRGwqzVQqW6mU1VLCMRKOFUCdO9o0UMp04YXdrwV5LJ9IqaSzwY+AzEfFsaupVO2qNsFgtIOJM4EyAKVOmxNSpU+tKx8DAAPXGLdNQPcEPZvbkFZwyv/fbgA23HQsPmlpeYsysNE2fvWoULGcAx5MKjeOBU4CP0eaCZSQaLYQaKSSa1Ugh04kTdrcW7LWUnVZJa5HyyPkRcWkOXlJ5tChpM+DxHL4I2KIw++bAo6Ul1szMStFUBaxWwRIRSwrTzwJ+ln+6YClJI2+Ugceca4f8VuPZwN0R8Y3CpLnATODE/PeyQvgRki4EdgKWuf2XmVn/aeYtyJoFS76ar9gPuCN/nwtMl7SOpK1Ib3n9ptH1m/WIXYCDgfdWvRl8IrC7pPuA3fNvgCuA+4EFwFnAJzqQZjMza7Nm7oBVCpb5km7LYV8CDpS0Penx4kLg4wARcaeki4G7SG9QHu43IK3fRcT11H78DrBrjfgBHN7WRJmZWcc18xbkYAXLFUPMcwJwQqPrNDMzM+sHHorIzMzMrGSugJmZmZmVzBUwMzMzs5K5AmZmZmZWMlfAzMzMzErmCpiZmZlZyXp/IDUzMzOzEWp01Jhz99qgJev3HTAzMzOzkvkOmJlZF/PYrmb9yXfAzMzMzErmCpiZmZlZyVwBMzMzMyuZ24DZK9zWxJrV6DFkZjbalF4Bk7QXcBqwJvD9iDix7DTMf2QZs1xQWJfqhjxi1u2cT6zXlfoIUtKawHeAvYFtgAMlbVNmGsy6mfOI2fCcT6wflH0HbEdgQUTcDyDpQmAacNdIF9TMo47Zkxue1WqYdNTlzJ68ouvvKvbIo9KW5RFYPZ/0wv/JWqPPmxS0NJ+YdULZFbCJwMOF34uAnYoRJB0GHJZ/Lpd0T6sT8SkYDzzZ6uW2Q6+ktRfSqZNe+VorrVuWmpjBDZtHoPF80gv/p3r1y7Z023YU8kktPZNPRpBHGt7/w+yrRnXT8eC01PCek4ZMS915pOwKmGqExSo/Is4EzmxrIqSbI2JKO9fRKr2S1l5JJ3R9WofNI9B4PunybR+RftmWftmOkrWsLOm2/d9N6XFaamtVWsruhmIRsEXh9+bAoyWnwaybOY+YDc/5xHpe2RWwm4CJVpFTAAAGB0lEQVStJW0laW1gOjC35DSYdTPnEbPhOZ9Yzyv1EWRErJB0BHAV6dXhcyLizjLTkLX1EWeL9UpaeyWd0MVpLSGPdO22N6BftqVftqM0Lc4n3bb/uyk9TkttLUmLIlZrXmJmZmZmbeShiMzMzMxK5gqYmZmZWcn6ugImaS9J90haIOmoGtO3lHSNpNslDUjavEPpPEfS45LuGGS6JJ2et+N2STuUncZCWoZL61sk/VrSi5I+V3b6CukYLp0H5X15u6T/lbRd2Wksk6QDJN0p6WVJU6qmHZ2PrXsk7dmpNI6UpGMlPSLptvzZp9NpGonhzk/WvDrKgHUkXZSn3yhpUmFaS/NFHWk5UtJd+Zx0jaQtC9NeKhznLXnZoI70zJL0RGG9hxamzZR0X/7MLCEtpxbSca+kZwrTWrZvmimLG9onEdGXH1LDzD8AbwDWBn4HbFMV50fAzPz9vcAPOpTWdwM7AHcMMn0f4Oekvm92Bm7s4H4dLq2vAf4GOAH4XBen813Axvn73p3cpyXtj7cCbwYGgCmF8G1y3lgH2CrnmTU7nd46t+nYTh5jTaZ92POTP+3fx8AngP/I36cDF+XvLc0XdablPcD6+fu/VNKSfy/vwL6ZBXy7xrybAPfnvxvn7xu3My1V8T9Jeumi5fum0bK40X3Sz3fAXhmqIiL+DFSGqijaBrgmf7+2xvRSRMR1wNNDRJkGzInkBmCcpM3KSd2qhktrRDweETcBfykvVTXTMVw6/zciluafN5D6EepbEXF3RNTqCXwacGFEvBgRDwALSHnH2que85M1p559PA04L3+/BNhVkmh9vhg2LRFxbUS8kH+2+5zUzPG3JzAvIp7O59B5wF4lpuVA4IIm1jeoJsrihvZJP1fAag1VMbEqzu+AD+bv+wEbStq0hLSNVD3bYo07hHRVMxr1+rF1RH4UcI6kjTudmBHo9f3eC+rZx6/EiYgVwDJg0zrnbXVaiqrPSetKulnSDZL2bSIdI03PB3P+ukRSpePbju2b/Fh2K+CXheBW75uhDJbWhvZJ2UMRlameIV0+B3xb0izgOuARYEWb09WIuoansZGT9B7Sye5vO52WZkm6GnhtjUlfjojLBputRljXHFtDbRNwBnA8Kb3HA6cAHysvdU3p6v3eJ+rZx4PFafX/p+7lSfoIMAX4+0Lw6yPiUUlvAH4paX5E/KHN6flv4IKIeFHS/yHdKXxvnfO2Oi0V04FLIuKlQlir981QWnq89HMFbNihKiLiUeAfASSNBT4YEctKS2H9POxGG0j6a+D7wN4R8VSn09OsiNitgdm6+tiqd5sknQX8rM3JaaWu3u99op59XImzSNIY4FWkR1Ct/v/UtTxJu5EuLv4+Il6shOeyioi4X9IA8HZSu6m2pafqnHgWUBl6fBEwtWregXampWA6cHhVOlu9b4YyWFob2if9/Ahy2KEqJI2XVNkHRwPnlJzGes0FZuQ3MHYGlkXE4k4nqpdJej1wKXBwRNzb6fR00Fxgen4bbCtga+A3HU5TXaraQe4H1HxzqUt5KJ32q2cfzwUqb6ztD/wyUqvqVueLesqjtwPfAz4QEY8XwjeWtE7+Ph7YBbiribTUm55i/voAcHf+fhWwR07XxsAeOaxtacnpeTOpgfuvC2Ht2DdDGawsbmyftOrtgW78kN5YuJdUG/5yDjuOdIBDynD35TjfB9bpUDovABaTGq4vIj0S+z/A/8nTBXwnb8d8Cm+xdWFaX5vDnwWeyd836sJ0fh9YCtyWPzd3+nht8/7YL++HF4ElwFWFaV/Ox9Y9pLuB/397d5CCIBQEAHSWXaFtq87QbaqLtKt7dIPWQWcoaOdhWjiBFIGFThHvgYjCx3Fw/h8Q8evx9rynfdbDJSfG6bdjejP+p/nJNn6OH9aASbRfwzfRNlizzthB66JHLMeszfucdMjzi3zOz7lfF+VmGxHXvO4pIuadsavMWRMRy7FjyeNNROwexg2amx7rxsu1+JOc+BURAECxf34FCQDwkzRgAADFNGAAAMU0YAAAxTRgAADFNGAAAMU0YAAAxW75k1tIf7CN5gAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Train.hist(figsize=(10,10))\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### From the histograms above, we can observe that attributes AS_MeanAmphiMoment, AS_DAYM780201, AS_FUKS010112, FULL_DAYM780201, FULL_GEOR030101, FULL_AURR980107,FULL_CHARGE have a normal. We can also tell from these plots that attribute CT_RACS820104 and FULL_AcidicMolPerc are skewed to the right. We can also tell that attributes NT_EFC195 and CLASS are categorical attributes. This can also be observed using density plots as shown below." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Using Density plots. Density plots are used to observe the distribution of a variable in a dataset. The peaks of a Density Plot help display where values are concentrated over the interval. Density plots give a more precise location and also gives a continuous distribution view. " + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Train.plot(kind='density', figsize=(10,10), subplots=True, layout=(4,3), sharex=False)\n", + "plt.show" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### From the above plots, FULL_Charge, FULL_AURR980107, FULL_DAYM780201, FULL_GEOR030101, CT_RACS820104, FULL_OOBM850104, AS_FUKS010112, AS_DAYM780201 show a normal distribution of variables. CLASS and NT_EFC195 are categorical data CLASS having equal number of instances while NT_EFC195 has a category that has almost all instances. \tFULL_AcidicMolPerc and AS_MeanAmphiMoment have more than one peak meaning that the data points are distribute at 2 peak for FULL_AcidicMolPerc and 3 peaks for AS_MeanAmphiMoment\t" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 9. Checking for the skewness of the data. Skewness is deviation from a normal distribution. The data may be skewed to the left or to the right of the normal distribution curve (bell shaped). Since many machine learning algorithms assume normal distribution,this allows one to know what attributes need to be corrected of skewness to improve the accuracy of the model. Skewness can be observed with bar plots of .skew()." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Train.skew().plot(kind='bar', figsize=(10,6))" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "NT_EFC195\n", + "0 2769\n", + "1 269\n", + "dtype: int64" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# From above, attribute NT_EFC195 shows that its, skewed.\n", + "Train.groupby('NT_EFC195').size()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### From the check above, attribute NT_EFC195 has skewed data and this could alter final results of the model. The data could be transformed or the attributed drop(not used in building a classifier." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 10. Spot checking classification algorithms since its a classification problem at hand.\n", + "#### This is done to know which algorithm is best suited for the problem at hand. Two linear machine learning algorithms(Logistic regression and Linear discriminant analysis) and four non-linear machine learning algorithm were used(k-nearest neighbors, naive bayes, support vector machines and classific regression tress. " + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('LR', 0.8342865299822478)\n", + "('LDA', 0.8377162908048379)\n", + "('KNN', 0.8690586462107053)\n", + "('CART', 1.0)\n", + "('NB', 0.8407203694376205)\n", + "('SVM', 0.8187103751493263)\n", + "('ABC', 0.8848771929251248)\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "from matplotlib import pyplot\n", + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "from sklearn.neighbors import KNeighborsClassifier\n", + "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", + "from sklearn.naive_bayes import GaussianNB\n", + "from sklearn.svm import SVC\n", + "from sklearn.ensemble import AdaBoostClassifier\n", + "from sklearn.metrics import matthews_corrcoef\n", + "\n", + "#split the dataset \n", + "A = Train.values\n", + "# Separating A into output and input components\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "# prepare models and add them to a list\n", + "models = []\n", + "models.append(('LR', LogisticRegression()))\n", + "models.append(('LDA', LinearDiscriminantAnalysis()))\n", + "models.append(('KNN', KNeighborsClassifier()))\n", + "models.append(('CART', DecisionTreeClassifier()))\n", + "models.append(('NB', GaussianNB()))\n", + "models.append(('SVM', SVC()))\n", + "models.append(('ABC', AdaBoostClassifier()))\n", + "\n", + "#print(models)\n", + "\n", + "# evaluate each model in turn\n", + "results = []\n", + "names = []\n", + "scoring = 'accuracy'\n", + "\n", + "for name, model in models:\n", + " kfold = KFold(n_splits=20, random_state=7)\n", + " cv_results = cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\n", + " results.append(cv_results)\n", + " names.append(name)\n", + " model.fit(X, Y)\n", + "\n", + " Prediction = model.predict(X)\n", + " msg = (name, matthews_corrcoef(Y, Prediction))\n", + " print(msg)\n", + "\n", + "# boxplot algorithm comparison\n", + "fig = pyplot.figure()\n", + "fig.suptitle('Algorithm Comparison')\n", + "ax = fig.add_subplot(111)\n", + "pyplot.boxplot(results)\n", + "ax.set_xticklabels(names)\n", + "pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### From these results, it would suggest that both DecisionTreeClassifier, KNeighborsClassifier and GaussianNB are worthy of further study on this problem." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### **11. Data Preparation.**\n", + "#### This is important because this finds a way to best expose the structure of the problem to machine learning algorithim intended to be used. Since the data has attributes of varying scales, its important to use one of the methods for data preparation like rescaling, standardization, normalization or binarization for better prediction. Here, rescaling is used to have all the attribute on the same scale." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[0.457 0. 0.348 0.545 0.33 0.483 0. 0.005 0.508 0.415 0.182]\n", + " [0.435 0.116 0.322 0.489 0.276 0.458 1. 0.011 0.421 0.586 0.475]\n", + " [0.467 0.116 0.246 0.523 0.288 0.565 0. 0.011 0.442 0.273 0.666]\n", + " [0.457 0.089 0.275 0.399 0.403 0.647 0. 0.011 0.405 0.153 0.424]\n", + " [0.511 0.183 0.323 0.373 0.342 0.595 0. 0.011 0.5 0.196 0.536]]\n" + ] + } + ], + "source": [ + "from numpy import set_printoptions\n", + "from sklearn.preprocessing import MinMaxScaler\n", + "\n", + "A = Train.values\n", + "# Separating A into output and input components\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "scaler = MinMaxScaler(feature_range= (0,1))\n", + "rescaledX = scaler.fit_transform(X)\n", + "\n", + "# Summary of the transformed data\n", + "set_printoptions(precision = 3) # This sets the number of floating point output after rescaling the data\n", + "print(rescaledX[0:5, :]) # This is used as check to confirm that the data has been rescaled" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Standardization\n", + "#### It is a useful technique to transform attributes with a Gaussian distribution and differing means and standard deviations to a standard Gaussian distribution with a mean of 0 and a standard deviation of 1" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[ 7.697e-01 -1.123e+00 -1.900e-01 1.376e-01 -6.067e-01 -7.206e-01\n", + " -3.117e-01 -1.331e+00 -2.257e-02 -3.610e-01 -9.251e-01]\n", + " [ 5.079e-01 -4.109e-01 -3.763e-01 -2.432e-01 -1.181e+00 -9.245e-01\n", + " 3.208e+00 -1.303e+00 -5.924e-01 9.021e-01 1.037e+00]\n", + " [ 9.006e-01 -4.109e-01 -9.163e-01 -8.651e-03 -1.054e+00 -4.632e-02\n", + " -3.117e-01 -1.304e+00 -4.590e-01 -1.409e+00 2.318e+00]\n", + " [ 7.697e-01 -5.741e-01 -7.115e-01 -8.701e-01 1.594e-01 6.274e-01\n", + " -3.117e-01 -1.302e+00 -7.015e-01 -2.300e+00 6.989e-01]\n", + " [ 1.424e+00 2.041e-03 -3.670e-01 -1.050e+00 -4.790e-01 2.003e-01\n", + " -3.117e-01 -1.302e+00 -7.713e-02 -1.977e+00 1.447e+00]]\n" + ] + } + ], + "source": [ + "from numpy import set_printoptions\n", + "from sklearn.preprocessing import StandardScaler\n", + "B= Train.values\n", + "#Separating the array into intput and output components\n", + "X = B[:, 0:11]\n", + "Y = B[:, 11]\n", + "scaler2 = StandardScaler()\n", + "standardizedX = scaler2.fit_transform(X)\n", + "# A portion of the transformed data\n", + "set_printoptions(precision = 3) # This sets the number of floating point output after rescaling the data\n", + "print(standardizedX[0:5,:]) # This is used as check to confirm that the data has been rescaled" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### **12. Feature selection**\n", + "#### Statistical tests can be used to select those features that have the strongest relationship with the output variable. Feature selection is done on non transformed data using select k best using he univariate statistic F was used since it can work best with data containg negative values as opposed to chi2 that doesnt take in negative values." + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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featuresscorespvalue
7AS_MeanAmphiMoment2813.8681780.000000e+00
1FULL_AcidicMolPerc1697.2495654.220004e-295
2FULL_AURR9801071572.2806771.887905e-277
3FULL_DAYM7802011350.3007436.997934e-245
0FULL_Charge1214.9028383.404241e-224
5FULL_OOBM850104785.1247987.441087e-154
8AS_DAYM780201717.3174084.911002e-142
10CT_RACS820104234.2741975.329249e-51
6NT_EFC195221.3908532.189203e-48
4FULL_GEOR030101220.9670652.669597e-48
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" + ], + "text/plain": [ + " features scores pvalue\n", + "7 AS_MeanAmphiMoment 2813.868178 0.000000e+00\n", + "1 FULL_AcidicMolPerc 1697.249565 4.220004e-295\n", + "2 FULL_AURR980107 1572.280677 1.887905e-277\n", + "3 FULL_DAYM780201 1350.300743 6.997934e-245\n", + "0 FULL_Charge 1214.902838 3.404241e-224\n", + "5 FULL_OOBM850104 785.124798 7.441087e-154\n", + "8 AS_DAYM780201 717.317408 4.911002e-142\n", + "10 CT_RACS820104 234.274197 5.329249e-51\n", + "6 NT_EFC195 221.390853 2.189203e-48\n", + "4 FULL_GEOR030101 220.967065 2.669597e-48" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sklearn.feature_selection import SelectKBest, f_classif\n", + "from numpy import set_printoptions\n", + "# Separating A into output and input components\n", + "A = Train.values\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "#Feature Extraction\n", + "bestfeat = SelectKBest(score_func=f_classif, k=10)\n", + "fit = bestfeat.fit(X,Y) #fitting f_classif test on predictors to get features that best predict\n", + "\n", + "set_printoptions(precision=3) # This sets the number of floating point output after rescaling the data\n", + "selected_features = fit.transform(X)\n", + "#Creating a dataframe to represent the order features selected starting from the best feature\n", + "scores = pd.DataFrame(fit.scores_)\n", + "pvalues = pd.DataFrame(fit.pvalues_)\n", + "columns = pd.DataFrame(Train.columns[0:11])\n", + "\n", + "selected_features_dataframe = pd.concat([columns,scores, pvalues,], axis=1)\n", + "selected_features_dataframe.columns = ['features', 'scores', 'pvalue']\n", + "selected_features_dataframe.nlargest(10, \"scores\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### SelectKBest using the f statistic, gives scores to each attribute and takes the specified number of attributes with the highest scores. Attributes AS_MeanAmphiMoment, FULL_AcidicMolPerc, FULL_AURR980107, FULL_DAYM780201, FULL_Charge, FULL_OOBM850104, AS_DAYM780201 and CT_RACS820104 were the selected features." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Feature selection using SelectKBest, Chi2 statistical test since there are no negative values in the attributes after rescaling with the minmax scaler." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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featuresscorespvalue
7AS_MeanAmphiMoment244.2277284.708742e-55
6NT_EFC195188.1970267.868482e-43
1FULL_AcidicMolPerc157.6175133.751602e-36
2FULL_AURR98010754.2314481.782118e-13
3FULL_DAYM78020137.3117801.006747e-09
8AS_DAYM78020126.1562243.148806e-07
5FULL_OOBM85010416.2314335.605627e-05
0FULL_Charge15.2452499.441397e-05
10CT_RACS82010415.1467759.946804e-05
4FULL_GEOR0301014.7886912.864719e-02
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" + ], + "text/plain": [ + " features scores pvalue\n", + "7 AS_MeanAmphiMoment 244.227728 4.708742e-55\n", + "6 NT_EFC195 188.197026 7.868482e-43\n", + "1 FULL_AcidicMolPerc 157.617513 3.751602e-36\n", + "2 FULL_AURR980107 54.231448 1.782118e-13\n", + "3 FULL_DAYM780201 37.311780 1.006747e-09\n", + "8 AS_DAYM780201 26.156224 3.148806e-07\n", + "5 FULL_OOBM850104 16.231433 5.605627e-05\n", + "0 FULL_Charge 15.245249 9.441397e-05\n", + "10 CT_RACS820104 15.146775 9.946804e-05\n", + "4 FULL_GEOR030101 4.788691 2.864719e-02" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sklearn.feature_selection import SelectKBest\n", + "from sklearn.feature_selection import chi2\n", + "\n", + "#Feature Extraction\n", + "test = SelectKBest(score_func=chi2, k=10)\n", + "fit = test.fit(rescaledX,Y) # fitting chi2 test on predictors to get features that best predict\n", + "\n", + "# Summary of scores \n", + "set_printoptions(precision=3) # This sets the number of floating point output after rescaling the data\n", + "#print(fit.scores_)\n", + "selected_features1 = fit.transform(rescaledX)\n", + "#Creating a dataframe to represent the order features selected starting from the best feature\n", + "scores = pd.DataFrame(fit.scores_)\n", + "pvalues = pd.DataFrame(fit.pvalues_)\n", + "columns = pd.DataFrame(Train.columns[0:11])\n", + "\n", + "selected_features1 = pd.concat([columns,scores, pvalues], axis=1)\n", + "selected_features1.columns = ['features', 'scores', 'pvalue']\n", + "selected_features1.nlargest(10, \"scores\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### From the dataframe above, AS_MeanAmphiMoment has the highest score of 244.227728 followed by NT_EFC195, then FULL_AcidicMolPerc and like that till the last attribute in dataframe, FULL_GEOR030101 that has lowwest score of 4.788691." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Feature selection using the recursive feature selection method with LogisticRegression - it works by recursively removing attributes and building a model on those attributes that remain. It uses the model accuracy to identify which attributes (and combination of attributes) contribute the most to predicting the target attribute" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Selected_FeaturesRFEFeature_Ranking
2FULL_AURR9801072
0FULL_Charge1
1FULL_AcidicMolPerc1
3FULL_DAYM7802011
4FULL_GEOR0301011
5FULL_OOBM8501041
6NT_EFC1951
7AS_MeanAmphiMoment1
8AS_DAYM7802011
9AS_FUKS0101121
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" + ], + "text/plain": [ + " Selected_FeaturesRFE Feature_Ranking\n", + "2 FULL_AURR980107 2\n", + "0 FULL_Charge 1\n", + "1 FULL_AcidicMolPerc 1\n", + "3 FULL_DAYM780201 1\n", + "4 FULL_GEOR030101 1\n", + "5 FULL_OOBM850104 1\n", + "6 NT_EFC195 1\n", + "7 AS_MeanAmphiMoment 1\n", + "8 AS_DAYM780201 1\n", + "9 AS_FUKS010112 1" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sklearn.feature_selection import RFE\n", + "from sklearn.linear_model import LogisticRegression\n", + "model = LogisticRegression()\n", + "rfe= RFE(model,10)\n", + "fit = rfe.fit(standardizedX, Y) # fitting logistic regression on predictors to get features that best predict\n", + "selectedfeaturesRFE = standardizedX[:, fit.support_]\n", + "\n", + "#Creating a dataframe to represent the order features selected starting from the best feature\n", + "#Num_Features = pd.DataFrame(fit.n_features_)\n", + "Selected_FeaturesRFE = pd.DataFrame(fit.support_)\n", + "Feature_Ranking = pd.DataFrame(fit.ranking_)\n", + "columns = pd.DataFrame(Train.columns[0:11])\n", + "\n", + "selected_features2 = pd.concat([columns, Feature_Ranking], axis=1)\n", + "selected_features2.columns = ['Selected_FeaturesRFE', 'Feature_Ranking']\n", + "selected_features2.nlargest(10, \"Feature_Ranking\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### From the dataframe above, FULL_AURR980107 has the highest rank of 2 followed by FULL_Charge, then FULL_AcidicMolPerc and like that till the last attribute in dataframe, AS_FUKS010112." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### **13. Evaluating Machine learning Alogorithms** - the best way to evaluate the performance of an algorithm would be to make predictions for new data to which you already know the answers. Evaluation shoud be done on data that is not used to train the algorithm. The evaluation is an estimate that we can use to talk about how well we think the algorithm may actually do in practice.\n", + "#### **Split into Train and Test set**\n", + "#### It's the simplest method that we can use to evaluate the performance of a machine learning algorithm is to use dierent training and testing datasets. The train dataset is split it into two parts. The algorithm is trained on one part and predictions are made on the second part and evaluate the predictions against the expected results. The size of the split can depend on the size of your dataset, although it is common to use 67% of the data for training and the remaining 33% for testing. This algorithm evaluation technique is very fast. It is ideal for large datasets (millions of records) where there is strong evidence that both splits of the data are representative of the underlying problem. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### **LogisticRegression** - Logistic regression is basically a supervised classification algorithm. Supervised learning is when a model learns from data that is already labeled. A supervised learning model takes in a set of input objects and output values. The model then trains on that data to learn how to map the inputs to the desired output so it can learn to make predictions on unseen data. In a classification problem, the target variable(or output), y, can take only discrete values for given set of features(or inputs), X. Logistic regression is a classification algorithm used to assign observations to a discrete set of classes. It is based on the concept of probability." + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MCC: 0.8283116428616907\n", + "Accuracy: 91.92422731804587\n", + "387\n", + "371\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import matthews_corrcoef\n", + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "A = Train.values\n", + "# Separating A into output and input components\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "test_size = 0.33\n", + "seed = 1\n", + "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", + "my_model1 = LogisticRegression()\n", + "my_model1.fit(selected_features_train, Y_train)\n", + "result = my_model1.score(selected_features_test, Y_test)\n", + "\n", + "Prediction = my_model1.predict(selected_features_train)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (result*100.0))\n", + "\n", + "#Assigning the preditions of the model to variable AssignmentOutPut1\n", + "AssignmentOutPut1 = my_model1.predict(Test.values) #Converting AssignmentOutPut1 to a dataframe since its output is an array\n", + "AssignmentOutPut1 = pd.DataFrame(AssignmentOutPut1)\n", + "\n", + "AssignmentOutPut1.columns = ['Class'] # Naming the output column\n", + "AssignmentOutPut1.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut1['Class'] = AssignmentOutPut1['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut1.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut1.groupby('Class').size()[1].sum())\n", + "\n", + "AssignmentOutPut1.to_csv('AssignmentOutPut1.csv') # Writing AssignmentOutPut1 to a csv file" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### **KNeighborsClassifier** - k-Nearest-Neighbors (k-NN) is a supervised machine learning model. KNN models work by taking a data point and looking at the ‘k’ closest labeled data points. The data point is then assigned the label of the majority of the ‘k’ closest points. For example, if k = 5, and 3 of points are ‘green’ and 2 are ‘red’, then the data point in question would be labeled ‘green’, since ‘green’ is the majority " + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MCC: 0.8566012373350099\n", + "Accuracy: 90.62811565304088\n", + "397\n", + "361\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import matthews_corrcoef\n", + "from sklearn.neighbors import KNeighborsClassifier\n", + "\n", + "A = Train.values\n", + "# Separating A into output and input components\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "test_size = 0.33\n", + "seed = 2\n", + "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", + "my_model2 = KNeighborsClassifier()\n", + "my_model2.fit(selected_features_train, Y_train)\n", + "result = my_model2.score(selected_features_test, Y_test)\n", + "\n", + "Prediction = my_model2.predict(selected_features_train)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (result*100.0))\n", + "\n", + "#Assigning the preditions of the model to variable AssignmentOutPut2\n", + "AssignmentOutPut2 = my_model2.predict(Test.values) \n", + "#Converting AssignmentOutPut to a dataframe since its output is an array\n", + "AssignmentOutPut2 = pd.DataFrame(AssignmentOutPut2)# Converting AssignmentOutPut2 to a dataframe since its output is an array\n", + "AssignmentOutPut2.columns = ['Class'] # Naming the out put column\n", + "AssignmentOutPut2.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut2['Class'] = AssignmentOutPut2['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut2.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut2.groupby('Class').size()[1].sum())\n", + "\n", + "AssignmentOutPut2.to_csv('AssignmentOutPut2.csv') # Writing AssignmentOutPut2 to a csv file" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### **DecisionTreeClassifier** - its also a supervised learning algorithm that identifies ways to split a data set based on different conditions." + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MCC: 1.0\n", + "Accuracy: 89.63110667996011\n", + "388\n", + "370\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import matthews_corrcoef\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "\n", + "A = Train.values\n", + "# Separating A into output and input components\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "test_size = 0.33\n", + "seed = 3\n", + "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", + "my_model3 = DecisionTreeClassifier()\n", + "my_model3.fit(selected_features_train, Y_train)\n", + "result = my_model3.score(selected_features_test, Y_test)\n", + "\n", + "Prediction = my_model3.predict(selected_features_train)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (result*100.0))\n", + "AssignmentOutPut3 = my_model3.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut\n", + "\n", + "AssignmentOutPut3 = pd.DataFrame(AssignmentOutPut3)# Converting AssignmentOutPut3 to a dataframe since its output is an array\n", + "AssignmentOutPut3.columns = ['Class'] # Naming the out put column\n", + "AssignmentOutPut3.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut3['Class'] = AssignmentOutPut3['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut3.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut3.groupby('Class').size()[1].sum())\n", + "\n", + "AssignmentOutPut1.to_csv('AssignmentOutPut3.csv') # Writing AssignmentOutPut3 to a csv file\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### **GaussianNB** - its a classification algorithm for binary (two-class) and multi-class classification problems. Naive Bayes calculates the probability of each class and the conditional probability of each class given each input value. These probabilities are estimated for new data and multiplied together, assuming that they are all independent" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MCC: 0.8417648773342619\n", + "Accuracy: 91.92422731804587\n", + "369\n", + "389\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import matthews_corrcoef\n", + "from sklearn.naive_bayes import GaussianNB\n", + "\n", + "A = Train.values\n", + "# Separating A into output and input components\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "test_size = 0.33\n", + "seed = 4\n", + "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", + "my_model4 = GaussianNB()\n", + "my_model4.fit(selected_features_train, Y_train)\n", + "result = my_model4.score(selected_features_test, Y_test)\n", + "\n", + "Prediction = my_model4.predict(selected_features_train)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (result*100.0))\n", + "\n", + "AssignmentOutPut4 = my_model4.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut4\n", + "\n", + "AssignmentOutPut4 = pd.DataFrame(AssignmentOutPut4)# Converting AssignmentOutPut4 to a dataframe since its output is an array\n", + "AssignmentOutPut4.columns = ['Class'] # Naming the out put column\n", + "AssignmentOutPut4.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut4['Class'] = AssignmentOutPut4['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "AssignmentOutPut4.to_csv('AssignmentOutPut4.csv') # Writing AssignmentOutPut4 to a csv file\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut4.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut4.groupby('Class').size()[1].sum())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### **Support Vector Machines** - its also a supervised machine learning algorithm capable of performing classification, regression and outlier detection. They draw a line that best separates two classes. Data instances closest to the line that best separates the classes are called support vectors. " + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MCC: 0.8399582732206575\n", + "Accuracy: 92.82153539381855\n", + "379\n", + "379\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import matthews_corrcoef\n", + "from sklearn.svm import SVC\n", + "\n", + "A = Train.values\n", + "# Separating A into output and input components\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "test_size = 0.33\n", + "seed = 5\n", + "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", + "my_model5 = SVC(kernel = 'linear')\n", + "my_model5.fit(selected_features_train, Y_train)\n", + "result = my_model5.score(selected_features_test, Y_test)\n", + "\n", + "Prediction = my_model5.predict(selected_features_train)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (result*100.0))\n", + "AssignmentOutPut5 = my_model5.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut5\n", + "\n", + "AssignmentOutPut5 = pd.DataFrame(AssignmentOutPut5)# Converting AssignmentOutPut5 to a dataframe since its output is an array\n", + "AssignmentOutPut5.columns = ['Class'] # Naming the out put column\n", + "AssignmentOutPut5.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut5['Class'] = AssignmentOutPut5['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "AssignmentOutPut1.to_csv('AssignmentOutPut5.csv') # Writing AssignmentOutPut5 to a csv file\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut5.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut5.groupby('Class').size()[1].sum())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### **LinearDiscriminantAnalysis** - it is a dimensionality reduction technique used for the supervised classification problems. It too assumes a Gaussian distribution for the numerical input variables.It is used to project the features in higher dimension space into a lower dimension space." + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MCC: 0.8376165100283083\n", + "Accuracy: 91.72482552342971\n", + "403\n", + "355\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", + "from sklearn.metrics import matthews_corrcoef\n", + "\n", + "A = Train.values\n", + "# Separating A into output and input components\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "test_size = 0.33\n", + "seed = 6\n", + "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", + "my_model6 = LinearDiscriminantAnalysis()\n", + "my_model6.fit(selected_features_train, Y_train)\n", + "result = my_model6.score(selected_features_test, Y_test)\n", + "\n", + "Prediction = my_model6.predict(selected_features_train)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", + "print(\"Accuracy:\", (result*100.0))\n", + "\n", + "AssignmentOutPut6 = my_model6.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut\n", + "AssignmentOutPut6 = pd.DataFrame(AssignmentOutPut6)# Converting AssignmentOutPut6 to a dataframe since its output is an array\n", + "AssignmentOutPut6.columns = ['Class'] # Naming the out put column\n", + "AssignmentOutPut6.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut6['Class'] = AssignmentOutPut6['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "AssignmentOutPut6.to_csv('AssignmentOutPut6.csv') # Writing AssignmentOutPut6 to a csv file\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut6.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut6.groupby('Class').size()[1].sum())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### **Ada Boost** - it trains predictors sequentially, each trying to correct its predecessor. It works by weighting instances in the dataset by how easy or difficult they are to classify, allowing the algorithm to pay or less attention to them in the construction of subsequent models" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MCC: 0.8546905980754327\n", + "Confusion_matrix: [[475 30]\n", + " [ 43 455]]\n", + "385\n", + "373\n" + ] + } + ], + "source": [ + "from sklearn.ensemble import AdaBoostClassifier\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import matthews_corrcoef\n", + "from sklearn.metrics import confusion_matrix\n", + "\n", + "A = Train.values\n", + "# Separating A into output and input components\n", + "\n", + "test_size = 0.33\n", + "seed = 6\n", + "# Split data into training and test sets to evaluate the model’s performance.\n", + "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", + "# Construct and fit a model to the training set. max_depth=1 is used to tell the model that the forest to be composed of trees with a\n", + "# single decision node and two leaves. n_estimators is used to specify the total number of trees in the forest.\n", + "Model7 = AdaBoostClassifier(DecisionTreeClassifier(max_depth=1),n_estimators=200) \n", + "Model7.fit(selected_features_train, Y_train)\n", + "predictions = Model7.predict(selected_features_test)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_test, predictions)))\n", + "print(\"Confusion_matrix:\", confusion_matrix(Y_test, predictions))\n", + "\n", + "AssignmentOutPut7 = Model7.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut7\n", + "AssignmentOutPut7 = pd.DataFrame(AssignmentOutPut7)# Converting AssignmentOutPut7 to a dataframe since its output is an array\n", + "AssignmentOutPut7.columns = ['Class'] # Naming the out put column\n", + "AssignmentOutPut7.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut7['Class'] = AssignmentOutPut7['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "AssignmentOutPut7.to_csv('AssignmentOutPut7.csv') # Writing AssignmentOutPut7 to a csv file\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut7.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut7.groupby('Class').size()[1].sum())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### **Principle component analysis** - PCA is a common way of speeding up a machine learning algorithm. Its mostly used when a machine learning algorithm is too slow because the input dimension is too high, then PCA is used to speed it up can be a reasonable choice. PCA can also be used for data visualization." + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Using PCA for visualization of data.\n", + "from sklearn.decomposition import PCA\n", + "#A = Train.values\n", + "# Separating A into output and input components\n", + "features = ['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107', 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104']\n", + "x =Train.loc[:, features].values\n", + "y =Train.loc[:,['CLASS']].values\n", + "pca = PCA(n_components=2)\n", + "principalComponents = pca.fit_transform(x)\n", + "principalDf = pd.DataFrame(principalComponents, columns = ['principal_component1', 'principal_component2'])\n", + "FinalDf = pd.concat([principalDf, Train[['CLASS']]], axis = 1)\n", + "FinalDf\n", + "\n", + "#The plot\n", + "fig = plt.figure(figsize = (8,8))\n", + "ax = fig.add_subplot(1,1,1) \n", + "ax.set_xlabel('Principal_Component1', fontsize = 10)\n", + "ax.set_ylabel('Principal_Component2', fontsize = 10)\n", + "ax.set_title('2 component PCA', fontsize = 15)\n", + "plt.scatter(FinalDf.iloc[:, 0], FinalDf.iloc[:, 1], c = FinalDf.iloc[:, 2], cmap ='Spectral') \n", + "#classes = [\"1.0\", \"0.0\"]\n", + "#colors = ['r','g', 'b']\n", + "#for CLASS, color in (classes,colors):\n", + "# indicesToKeep = FinalDf['CLASS'] == CLASS\n", + "# ax.scatter(FinalDf.loc[indicesToKeep, 'principal_component1'], FinalDf.loc[indicesToKeep, 'principal_component2'], c =color )\n", + "ax.legend()\n", + "ax.grid()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### **Using principle component analysis for machine learning**" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MCC: 0.7507336393432698\n", + "Socre: 0.8753738783649053\n", + "506\n", + "497\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.decomposition import PCA\n", + "A= Train.values\n", + "X = A[:, 0:11]\n", + "Y = A[:, 11]\n", + "#Make an instance of the Model\n", + "pca = PCA(.95)\n", + "#Splitting data\n", + "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", + "pca = PCA(n_components=2)\n", + "principalComponents = pca.fit_transform(selected_features_train)\n", + "fit_train = pca.fit(selected_features_train) #Fit PCA on training set\n", + "\n", + "#Apply the mapping (transform) to both the training set and the test set.\n", + "selected_features_trainF = pca.transform(selected_features_train)\n", + "selected_features_testF = pca.transform(selected_features_test)\n", + "\n", + "#Importing the model\n", + "from sklearn.linear_model import LogisticRegression\n", + "Model8 = LogisticRegression()\n", + "Model8.fit(selected_features_trainF, Y_train)\n", + "\n", + "#Predicting new data\n", + "Pred = Model8.predict(selected_features_testF)\n", + "print(\"MCC:\", (matthews_corrcoef(Y_test, Pred)))\n", + "print(\"Socre:\", Model8.score(selected_features_testF, Y_test))\n", + "\n", + "AssignmentOutPut8 = Model8.predict(selected_features_testF) #Assigning the preditions of the model to variable AssignmentOutPut8\n", + "AssignmentOutPut8 = pd.DataFrame(AssignmentOutPut8)# Converting AssignmentOutPut8 to a dataframe since its output is an array\n", + "AssignmentOutPut8.columns = ['Class'] # Naming the out put column\n", + "AssignmentOutPut8.index.name = \"Index\" #Creating a column called index\n", + "AssignmentOutPut8['Class'] = AssignmentOutPut8['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", + "\n", + "AssignmentOutPut8.to_csv('AssignmentOutPut8.csv') # Writing AssignmentOutPut8 to a csv file\n", + "#Printing the number of False and Trues\n", + "print(AssignmentOutPut8.groupby('Class').size()[0].sum())\n", + "print(AssignmentOutPut8.groupby('Class').size()[1].sum())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### The Naive bayes(GaussianNB) algorithm with none rescaled or transformed data gave the best prediction from all the algorithms used." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.6" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} From 0730c91bbeaaad1fbaf8b73f454756dd0a0415de Mon Sep 17 00:00:00 2001 From: Atwine Date: Fri, 13 Mar 2020 13:05:15 +0300 Subject: [PATCH 22/29] Updated --- Assignment Colab/Agasi_Update.ipynb | 1 - Assignment Colab/agasi-herbert.ipynb | 2204 ---------------- Assignment Colab/nsangi-olga-tendo(1).ipynb | 2491 ------------------- Assignment Colab/nsangi-olga-tendo.ipynb | 2485 ------------------ 4 files changed, 7181 deletions(-) delete mode 100644 Assignment Colab/Agasi_Update.ipynb delete mode 100644 Assignment Colab/agasi-herbert.ipynb delete mode 100644 Assignment Colab/nsangi-olga-tendo(1).ipynb delete mode 100644 Assignment Colab/nsangi-olga-tendo.ipynb diff --git a/Assignment Colab/Agasi_Update.ipynb b/Assignment Colab/Agasi_Update.ipynb deleted file mode 100644 index a0c7b44..0000000 --- a/Assignment Colab/Agasi_Update.ipynb +++ /dev/null @@ -1 +0,0 @@ -{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\n# DATA VISUALIZATION\nimport matplotlib.pyplot as plt\nimport matplotlib.gridspec as gridspec\nimport seaborn as sns\n\n#scikit learn libraries\n#Lineaer Models\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.neural_network import MLPClassifier\nfrom sklearn.linear_model import SGDClassifier\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n\n\nfrom sklearn.svm import SVC\nfrom sklearn.naive_bayes import GaussianNB\n# Tree\nfrom sklearn.tree import DecisionTreeClassifier\n\n# sklearn libraries\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn.model_selection import train_test_split,KFold,cross_val_score\nfrom sklearn.preprocessing import normalize\nfrom sklearn.metrics import confusion_matrix,accuracy_score,precision_score,recall_score,f1_score,matthews_corrcoef,classification_report,roc_curve\nfrom sklearn.externals import joblib\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.decomposition import PCA\n\n#let's remove the annoying warnings from our cells.\nimport warnings\nwarnings.filterwarnings('ignore')\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n for filename in filenames:\n print(os.path.join(dirname, filename))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"## Loading the datasets\n\nTrain = pd.read_csv(\"../input/ace-class-assignment/AMP_TrainSet.csv\")\nTest = pd.read_csv(\"../input/ace-class-assignment/Test.csv\")\n\n## Taking a preview of the data\nTrain.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"## Loking at the dimensions of the dataset\n\nTrain.shape,Test.shape","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"## Looking for misssing and null values\nTrain.isnull().any().sum()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"## Looking the data types of the data\nTrain.dtypes","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"## Looking at the description of the data \nTrain.describe()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Looking at the data:\n* There are two categorical features CLASS and NT_EFC195\n* There is a big difference between the 75th percentile and the maximum values for columns FULL_Charge and FULL_AcidicMolPerc\n* The columns FULL_AcidicMolPerc and FULL_OOBM850104 have both negative and positive values."},{"metadata":{"trusted":true},"cell_type":"code","source":"# Looking at the ratio of the binary data for the class\n\nAll = Train.shape[0]\nPositive = Train[Train['CLASS'] == 1]\nNegative = Train[Train['CLASS'] == 0]\n\nx = len(Positive)/All\ny = len(Negative)/All\n\nprint('Positives :',x*100,'%')\nprint('Negatives :',y*100,'%')\n\n## The sets are evenly balanced and hence there will be no need to use SMOTE OR NEAR MISS","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Visualizing the data class\nlabels = ['Negatives','Positives']\nclasses = pd.value_counts(Train['CLASS'], sort = True)\nclasses.plot(kind = 'bar', rot=0)\nplt.title(\"Visualizing the data class\")\nplt.xticks(range(2), labels)\nplt.xlabel(\"Class\")\nplt.ylabel(\"Frequency\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Plot the distribution of features"},{"metadata":{"trusted":true},"cell_type":"code","source":"# distribution of features\n# This feature works with numerical data not categorical data.\nfeatures =Train.drop([\"CLASS\",\"NT_EFC195\"],axis=1).columns\n\nplt.figure(figsize=(12,12*4))\ngs = gridspec.GridSpec(12, 1)\nfor i, cn in enumerate(Train[features]):\n ax = plt.subplot(gs[i])\n sns.distplot(Train[cn][Train.CLASS == 1], bins=50)\n sns.distplot(Train[cn][Train.CLASS == 0], bins=50)\n ax.set_xlabel('')\n ax.set_title('histogram of feature: ' + str(cn))\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# PCA (Principal Component Analysis) mainly using to reduce the size of the feature space while\n# retaining as much of the information as possible.\n# In here all the features transformed into 2 features using PCA.\n\nX = Train.drop(['CLASS'], axis = 1)\ny = Train['CLASS']\n\npca = PCA(n_components=2)\nprincipalComponents = pca.fit_transform(X.values)\nprincipalDf = pd.DataFrame(data = principalComponents\n , columns = ['principal component 1', 'principal component 2'])\nFTrain = pd.concat([principalDf, y], axis = 1)\nFTrain.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# 2D visualization\nfig = plt.figure(figsize = (8,8))\nax = fig.add_subplot(1,1,1) \nax.set_xlabel('Principal Component 1', fontsize = 15)\nax.set_ylabel('Principal Component 2', fontsize = 15)\nax.set_title('2 component PCA', fontsize = 20)\ntargets = [0, 1]\ncolors = ['r', 'g']\nfor target, color in zip(targets,colors):\n indicesToKeep = FTrain['CLASS'] == target\n ax.scatter(FTrain.loc[indicesToKeep, 'principal component 1']\n , FTrain.loc[indicesToKeep, 'principal component 2']\n , c = color\n , s = 50)\nax.legend(targets)\nax.grid()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"\n# Data splitting\n\n# splitting the faeture array and label array keeping 80% for the trainnig sets\nX_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.20)\n\n# normalize: Scale input vectors individually to unit norm (vector length).\nX_train = normalize(X_train)\nX_test=normalize(X_test)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Spot-Check Algorithms\n\nmodels = []\nmodels.append(('LR', LogisticRegression()))\nmodels.append(('LDA', LinearDiscriminantAnalysis()))\nmodels.append(('KNN', KNeighborsClassifier()))\nmodels.append(('CART', DecisionTreeClassifier()))\nmodels.append(('NB', GaussianNB()))\nmodels.append(('SVM', SVC()))\nmodels.append(('NN',MLPClassifier()))\nmodels.append(('SG',SGDClassifier()))\n\n# evaluate each model in turn\n\nresults = []\nnames = []\nseed =25\nfor name, model in models:\n kfold = KFold(n_splits=10, random_state=seed,shuffle=True)\n cv_results = cross_val_score(model, X_train, y_train, cv=kfold, \n scoring='accuracy')\n results.append(cv_results)\n names.append(name)\n print(\"%s: %f (%f)\" % (name, cv_results.mean(), cv_results.std()))\n#print(msg)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"\n# Model Evaluation\n"},{"metadata":{"trusted":true},"cell_type":"code","source":"\n#scoring knn\nknn_accuracy_score = accuracy_score(y_test,knn_predicted_test_labels)\nknn_precison_score = precision_score(y_test,knn_predicted_test_labels)\nknn_recall_score = recall_score(y_test,knn_predicted_test_labels)\nknn_f1_score = f1_score(y_test,knn_predicted_test_labels)\nknn_MCC = matthews_corrcoef(y_test,knn_predicted_test_labels)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"for n in results:\n print(n)\n#names['LR'].predict(X_test)","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4} \ No newline at end of file diff --git a/Assignment Colab/agasi-herbert.ipynb b/Assignment Colab/agasi-herbert.ipynb deleted file mode 100644 index 7c3752e..0000000 --- a/Assignment Colab/agasi-herbert.ipynb +++ /dev/null @@ -1,2204 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", - "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Using TensorFlow backend.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "/kaggle/input/ace-class-assignment/Test.csv\n", - "/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\n" - ] - } - ], - "source": [ - "# This Python 3 environment comes with many helpful analytics libraries installed\n", - "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", - "# For example, here's several helpful packages to load in \n", - "\n", - "import numpy as np # linear algebra\n", - "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", - "import matplotlib.pyplot as plt #Data visualization\n", - "import seaborn as sns #Data Visualization\n", - "import math\n", - "\n", - "\n", - "###Feature Selection\n", - "from sklearn.feature_selection import SelectKBest\n", - "from sklearn.feature_selection import chi2\n", - "from sklearn.feature_selection import f_classif\n", - "from sklearn.feature_selection import mutual_info_classif\n", - "from sklearn.feature_selection import SelectFromModel\n", - "from sklearn.feature_selection import RFE\n", - "from sklearn.feature_selection import SelectFromModel\n", - "from sklearn.ensemble import RandomForestClassifier\n", - "from sklearn.ensemble import VotingClassifier\n", - "\n", - "###Modeling\n", - "from sklearn.linear_model import LogisticRegression\n", - "from sklearn.model_selection import train_test_split\n", - "\n", - "from sklearn.metrics import accuracy_score, confusion_matrix, recall_score\n", - "from imblearn.over_sampling import SMOTE\n", - "from imblearn.under_sampling import NearMiss\n", - "\n", - "from sklearn.naive_bayes import GaussianNB\n", - "from sklearn.neural_network import MLPClassifier\n", - "from sklearn.linear_model import SGDClassifier\n", - "from sklearn import svm\n", - "from sklearn import tree\n", - "\n", - "from sklearn.model_selection import cross_val_score\n", - "\n", - "from numpy import savetxt\n", - "# Input data files are available in the \"../input/\" directory.\n", - "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", - "\n", - "import os\n", - "for dirname, _, filenames in os.walk('/kaggle/input'):\n", - " for filename in filenames:\n", - " print(os.path.join(dirname, filename))\n", - "\n", - "# Any results you write to the current directory are saved as output." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Importing Datasets" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0", - "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a" - }, - "outputs": [], - "source": [ - "#This segment imports the two datasets the test and train\n", - "Test = pd.read_csv(\"../input/ace-class-assignment/Test.csv\")\n", - "Train = pd.read_csv(\"../input/ace-class-assignment/AMP_TrainSet.csv\")\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Taking a preview of the data." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "#This is a for data with absolute values\n" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Train shape (3038, 12) \n", - " Test shape (758, 11) \n" - ] - } - ], - "source": [ - "print(\"Train shape {} \\n Test shape {} \".format(Train.shape,Test.shape))" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", - " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", - " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", - " 'CLASS'],\n", - " dtype='object')" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Train.columns" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "#Train['FULL_Charge'] = Train['FULL_Charge'] **2\n", - "#Train['CT_RACS820104'] = Train['CT_RACS820104'] **2" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "FULL_Charge float64\n", - "FULL_AcidicMolPerc float64\n", - "FULL_AURR980107 float64\n", - "FULL_DAYM780201 float64\n", - "FULL_GEOR030101 float64\n", - "FULL_OOBM850104 float64\n", - "NT_EFC195 int64\n", - "AS_MeanAmphiMoment float64\n", - "AS_DAYM780201 float64\n", - "AS_FUKS010112 float64\n", - "CT_RACS820104 float64\n", - "CLASS int64\n", - "dtype: object" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Train.dtypes" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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count3038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.000000
mean2.0602378.5215200.97141073.6687600.994007-2.4329270.08854515.68323373.6508285.9113611.2352550.500000
std3.8199297.5866520.1074138.5274890.0313331.7072230.28413311.5756659.1660920.6936890.2100120.500082
min-16.0000000.0000000.68400042.7500000.866000-10.4320000.0000000.04100042.7780003.5330000.7850000.000000
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" - ], - "text/plain": [ - " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n", - "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", - "mean 2.060237 8.521520 0.971410 73.668760 \n", - "std 3.819929 7.586652 0.107413 8.527489 \n", - "min -16.000000 0.000000 0.684000 42.750000 \n", - "25% 0.000000 2.516000 0.895000 68.294000 \n", - "50% 2.000000 7.143000 0.963000 74.059500 \n", - "75% 4.000000 13.158000 1.041000 79.343750 \n", - "max 30.000000 46.667000 1.451000 101.682000 \n", - "\n", - " FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n", - "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", - "mean 0.994007 -2.432927 0.088545 15.683233 \n", - "std 0.031333 1.707223 0.284133 11.575665 \n", - "min 0.866000 -10.432000 0.000000 0.041000 \n", - "25% 0.974000 -3.606000 0.000000 5.587500 \n", - "50% 0.994000 -2.296500 0.000000 14.988500 \n", - "75% 1.011000 -1.283250 0.000000 26.807750 \n", - "max 1.196000 3.576000 1.000000 51.280000 \n", - "\n", - " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 CLASS \n", - "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", - "mean 73.650828 5.911361 1.235255 0.500000 \n", - "std 9.166092 0.693689 0.210012 0.500082 \n", - "min 42.778000 3.533000 0.785000 0.000000 \n", - "25% 67.556000 5.459250 1.082000 0.000000 \n", - "50% 73.697000 5.925500 1.184000 0.500000 \n", - "75% 79.778000 6.382000 1.351000 1.000000 \n", - "max 103.167000 8.662000 2.192000 1.000000 " - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Train.describe()" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "sns.boxplot(Train[['FULL_OOBM850104']])" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "##Outlier detection\n", - "#O_FULL_Charge = [x for x in Train['FULL_Charge'] if x > 10]\n", - "#print(len(O_FULL_Charge))\n", - "#print(len(Train['FULL_Charge']))\n", - "\n", - "##Outlier detection for FULL_AcidicMolPerc\n", - "\n", - "#O_FULL_AcidicMolPerc = [x for x in Train['FULL_AcidicMolPerc'] if x > 20]\n", - "#print(len(O_FULL_AcidicMolPerc))\n", - "#O_FULL_AcidicMolPerc\n", - "\n", - "\n", - "## Testing to remove the outliers\n", - "\n", - "#Train[['FULL_Charge']] =[Train['FULL_Charge'].mean(axis = 0) for x in range(Train['FULL_Charge']) if x > 10]\n", - "#def out(xx):\n", - " # mm =Train['FULL_Charge'].mean() \n", - " # for x in range(len(Train['FULL_Charge'])):\n", - " # if x > 20:\n", - " # Train['FULL_Charge'].iloc[x] = mm \n", - " \n", - " \n", - "#out(Train)\n", - "#Train['FULL_Charge'].mean() \n", - "#Train[['FULL_Charge' ]> 20] =Train['FULL_Charge'].mean()\n", - "\n", - "##AS_MeanAmphiMoment\n", - "#This feature has no outliers\n", - "\n", - "###\n", - "#'FULL_AURR980107'\n", - "##This attribute has outliers greater than 13 \n", - "#Train['FULL_AURR980107']\n", - "#FAURR = np.array(Train['FULL_AURR980107'])\n", - "#FAURR[FAURR >= 13]= FAURR.mean()\n", - "#Train['FULL_AURR980107'] = pd.DataFrame(FAURR)\n", - "\n", - "\n", - "##Removing the outliers and replacing them with the mean\n", - "##Values greater than 10 and values less than -6\n", - "#FCharge = np.array(Train['FULL_Charge'])\n", - "#FCharge[ FCharge >= 10 ]= FCharge.mean()\n", - "#FCharge[ FCharge <= -6 ]= FCharge.mean()\n", - "#Train['FULL_Charge'] = pd.DataFrame(FCharge)\n", - "\n", - "##Removing outliers for values\n", - "#Train['FULL_DAYM780201']\n", - "#FDAY = np.array(Train['FULL_DAYM780201'])\n", - "#FDAY[FDAY >= 95]= FDAY.mean()\n", - "#FDAY[FDAY <= 52]= FDAY.mean()\n", - "#Train['FULL_DAYM780201'] = pd.DataFrame(FDAY)\n", - "### \n", - "#Removing outliers greater\n", - "#Train[['FULL_AcidicMolPerc']] \n", - "#FAcidic = np.array(Train['FULL_AcidicMolPerc'])\n", - "#FAcidic[ FAcidic >= 27 ]= FCharge.mean()\n", - "#Train['FULL_AcidicMolPerc'] = pd.DataFrame(FAcidic)\n", - "\n", - "\n", - "##Train[['FULL_OOBM850104']]\n", - "#FOOB = np.array(Train['FULL_OOBM850104'])\n", - "#FOOB[FOOB >= 2 ]= FOOB.mean()\n", - "#FOOB[FOOB <= -7 ]= FOOB.mean()\n", - "#Train['FULL_OOBM850104'] = pd.DataFrame(FOOB)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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c0n9LOqXSb9E0ZZz8RR8AOMJf9AGAI0QZABwhygDgCFEGAEeIMgA4QpQBwBGiDACOEGUAcOT/AQdi0NNOKculAAAAAElFTkSuQmCC\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "##The density plot is used to determint the distribution of the data.\n", - "##Sometimes the two peaks illustrate a binary categorical feature i.e.\n", - "##Most of the data appers to be normally distributed.\n", - "Train.plot(kind='density', subplots=True, layout=(4,4), sharex=False)\n", - "plt.show" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Looking at the categorical variable closesly to understand the short and long peak.\n", - "A count of the categorical values and a bar plot will give more description." - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0 2769\n", - "1 269\n", - "Name: NT_EFC195, dtype: int64" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Train.NT_EFC195.value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": "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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "Train.NT_EFC195.value_counts().plot(kind=\"bar\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Looking at the above graph. It shows that data is very unbalanced. In this case if we are to use this feature in our machine Learning alogorithm we would require to use either SMOTE or Near Miss to balance the dataset." - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "##\n", - "#This is to determine the skewness of the data.\n", - "## For each feature the skewness can be determined.\n", - "\n", - "Train.skew().plot(kind='bar')" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "import seaborn as sns\n", - "sns.pairplot(Train)" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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QJDHhU0BV9WySdwF3AycAO6vq4UnOoXOeWtPzma/PCUtVrdwlSXrR8ZPAktQpA0CSOmUASFKnJv05AEkiyesYfAvAOgafBdoP7K6qR6Y6sc54BCBpopJcy+BrYAJ8kcHbwwPc6hdETpbvAupQkquq6uPTnof6lORbwOur6sdL6icCD1fVpunMrD8eAfTpz6c9AXXtp8Crl6mf2cY0IV4DeJFK8uCRhoAzJjkXaYn3APck2cuhL4c8C3gN8K6pzapDngJ6kUryBHAh8NTSIeDfqmq5/8CkiUjyEgZfD7+OwWtyAbi/qn4y1Yl1xiOAF6/PAK+oqq8sHUjy+clPRzqkqn4K3DvtefTOIwBJ6pQXgSWpUwaAJHXKAJCkThkAktSp/wPs1chqmw6rowAAAABJRU5ErkJggg==\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "Train.CLASS.value_counts().plot(kind='bar')" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "FULL_Charge 0.088068\n", - "FULL_AcidicMolPerc -0.143168\n", - "FULL_AURR980107 -0.169540\n", - "FULL_DAYM780201 -0.090058\n", - "FULL_GEOR030101 -0.230417\n", - "FULL_OOBM850104 -0.230561\n", - "NT_EFC195 1.000000\n", - "AS_MeanAmphiMoment 0.178683\n", - "AS_DAYM780201 -0.036844\n", - "AS_FUKS010112 0.145924\n", - "CT_RACS820104 0.080898\n", - "CLASS 0.260702\n", - "Name: NT_EFC195, dtype: float64" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Train.corr(method='pearson')['NT_EFC195']" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Missing data variables" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FULL_Charge 0\n", - "FULL_AcidicMolPerc 0\n", - "FULL_AURR980107 0\n", - "FULL_DAYM780201 0\n", - "FULL_GEOR030101 0\n", - "FULL_OOBM850104 0\n", - "NT_EFC195 0\n", - "AS_MeanAmphiMoment 0\n", - "AS_DAYM780201 0\n", - "AS_FUKS010112 0\n", - "CT_RACS820104 0\n", - "CLASS 0\n", - "dtype: int64\n", - "FULL_Charge 0\n", - "FULL_AcidicMolPerc 0\n", - "FULL_AURR980107 0\n", - "FULL_DAYM780201 0\n", - "FULL_GEOR030101 0\n", - "FULL_OOBM850104 0\n", - "NT_EFC195 0\n", - "AS_MeanAmphiMoment 0\n", - "AS_DAYM780201 0\n", - "AS_FUKS010112 0\n", - "CT_RACS820104 0\n", - "CLASS 0\n", - "dtype: int64\n" - ] - } - ], - "source": [ - "print(Train.isna().sum())\n", - "print(Train.isnull().sum())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Feature Selection\n", - "### Chi Square test" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The chi square test didn't yield any results as a result of and error caused by having negative values. The code is in the section below." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "```\n", - "sel_chi2 = SelectKBest(chi2, k=4) # select 4 features\n", - "X_train_chi2 = sel_chi2.fit_transform(X_train, y_train)\n", - "print(sel_chi2.get_support())\n", - "```" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [], - "source": [ - "#array = Train.values\n", - "X = Train.drop(\"CLASS\", axis = 1)\n", - "y = Train.CLASS\n", - "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42, stratify=y)\n", - "#array.shape" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# F test" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[False True True True False False False True False False False]\n" - ] - } - ], - "source": [ - "sel_f = SelectKBest(f_classif, k=4)\n", - "X_train_f = sel_f.fit_transform(X_train, y_train)\n", - "print(sel_f.get_support())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Mutual_info_classif test" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[ True True True False False False False True False False False]\n" - ] - } - ], - "source": [ - "sel_mutual = SelectKBest(mutual_info_classif, k=4)\n", - "X_train_mutual = sel_mutual.fit_transform(X_train, y_train)\n", - "print(sel_mutual.get_support())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Recursive Feature Elimination" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[False False True False False True True False False False True]\n", - "Index(['FULL_AURR980107', 'FULL_OOBM850104', 'NT_EFC195', 'CT_RACS820104'], dtype='object')\n" - ] - } - ], - "source": [ - "model_logistic = LogisticRegression(solver='lbfgs', multi_class='multinomial', max_iter=1000)\n", - "sel_rfe_logistic = RFE(estimator=model_logistic, n_features_to_select=4, step=1)\n", - "X_train_rfe_logistic = sel_rfe_logistic.fit_transform(X_train, y_train)\n", - "print(sel_rfe_logistic.get_support())\n", - "#####\n", - "print(Train.columns[sel_rfe_logistic.get_support(indices=True)])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Random forest as the model" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[False True True True False False False True False False False]\n" - ] - } - ], - "source": [ - "model_tree = RandomForestClassifier(random_state=100, n_estimators=50)\n", - "sel_rfe_tree = RFE(estimator=model_tree, n_features_to_select=4, step=1)\n", - "X_train_rfe_tree = sel_rfe_tree.fit_transform(X_train, y_train)\n", - "print(sel_rfe_tree.get_support())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " # Feature selection using SelectFromModel" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# L1-based feature selection" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[ True True False True False True True True True True True]\n" - ] - } - ], - "source": [ - "model_logistic = LogisticRegression(solver='saga', multi_class='multinomial', max_iter=10000, penalty='l1')\n", - "sel_model_logistic = SelectFromModel(estimator=model_logistic)\n", - "X_train_sfm_l1 = sel_model_logistic.fit_transform(X_train, y_train)\n", - "print(sel_model_logistic.get_support())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Tree-based feature selection" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[0.11807409 0.16028202 0.07342594 0.10156481 0.0515547 0.08030908\n", - " 0.00589794 0.3148824 0.03561078 0.02422801 0.03417023]\n", - "[ True True False True False False False True False False False]\n" - ] - } - ], - "source": [ - "model_tree = RandomForestClassifier(random_state=100, n_estimators=50)\n", - "model_tree.fit(X_train, y_train)\n", - "print(model_tree.feature_importances_)\n", - "sel_model_tree = SelectFromModel(estimator=model_tree, prefit=True, threshold='mean') \n", - " # since we already fit the data, we specify prefit option here\n", - " # Features whose importance is greater or equal to the threshold are kept while the others are discarded.\n", - "X_train_sfm_tree = sel_model_tree.transform(X_train)\n", - "print(sel_model_tree.get_support())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "For the different feature selection model the " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Conclusion on Best Features" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " sel_model_tree sel_rfe_tree sel_rfe_logistic sel_mutual sel_f\n", - "0 1 0 0 1 0\n", - "1 1 1 0 1 1\n", - "2 0 1 1 1 1\n", - "3 1 1 0 0 1\n", - "4 0 0 0 0 0\n", - "5 0 0 1 0 0\n", - "6 0 0 1 0 0\n", - "7 1 1 0 1 1\n", - "8 0 0 0 0 0\n", - "9 0 0 0 0 0\n", - "10 0 0 1 0 0\n", - " 0 1 2 3 4 5 6 7 8 9 10\n", - "sel_model_tree 1 1 0 1 0 0 0 1 0 0 0\n", - "sel_rfe_tree 0 1 1 1 0 0 0 1 0 0 0\n", - "sel_rfe_logistic 0 0 1 0 0 1 1 0 0 0 1\n", - "sel_mutual 1 1 1 0 0 0 0 1 0 0 0\n", - "sel_f 0 1 1 1 0 0 0 1 0 0 0\n" - ] - }, - { - "data": { - "text/plain": [ - "[2, 4, 4, 3, 0, 1, 1, 4, 0, 0, 1]" - ] - }, - "execution_count": 28, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "F1 = pd.DataFrame(sel_model_tree.get_support(), columns=['sel_model_tree'])\n", - "F2 = pd.DataFrame(sel_rfe_tree.get_support(),columns=['sel_rfe_tree'])\n", - "F3 = pd.DataFrame(sel_rfe_logistic.get_support(),columns=['sel_rfe_logistic'])\n", - "F4 = pd.DataFrame(sel_mutual.get_support(),columns=['sel_mutual'])\n", - "F5 = pd.DataFrame(sel_f.get_support(),columns=['sel_f'])\n", - "df = pd.concat([F1,F2,F3,F4,F5], axis=1)\n", - "\n", - "df = df.replace({True:1,False:0})\n", - "print(df)\n", - "dff =df.T\n", - "print(dff)\n", - "#dff[1].sum()\n", - "dfff =[]\n", - "for x in dff:\n", - " dfff.append(dff[x].sum())\n", - " \n", - "dfff\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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3038 rows × 5 columns

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" - ], - "text/plain": [ - " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n", - "0 5.0 0.000 0.951 74.842 \n", - "1 4.0 5.405 0.931 71.595 \n", - "2 5.5 5.405 0.873 73.595 \n", - "3 5.0 4.167 0.895 66.250 \n", - "4 7.5 8.537 0.932 64.720 \n", - "... ... ... ... ... \n", - "3033 1.0 5.263 0.945 67.947 \n", - "3034 -6.5 21.667 1.133 75.433 \n", - "3035 -1.5 12.500 1.091 76.542 \n", - "3036 2.0 5.000 0.849 73.750 \n", - "3037 -1.0 15.789 1.066 66.158 \n", - "\n", - " AS_MeanAmphiMoment \n", - "0 0.282 \n", - "1 0.600 \n", - "2 0.593 \n", - "3 0.614 \n", - "4 0.616 \n", - "... ... \n", - "3033 16.706 \n", - "3034 16.897 \n", - "3035 16.918 \n", - "3036 17.131 \n", - "3037 17.151 \n", - "\n", - "[3038 rows x 5 columns]" - ] - }, - "execution_count": 29, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "##Adding the fifth feature to check the performance of the model.\n", - "#Train[['FULL_Charge','FULL_AcidicMolPerc','FULL_AURR980107','FULL_DAYM780201','AS_MeanAmphiMoment']]\n", - "##Checking the different features forthe different algorithms\n", - "\n", - "#['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", - " # 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", - " # 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", - " # 'CLASS'\n", - " \n", - "##Absolute value of features.\n", - "##[0, 4, 4, 4, 1, 1, 1, 4, 0, 0, 1]\n", - " \n", - "Train[['FULL_Charge','FULL_AcidicMolPerc','FULL_AURR980107','FULL_DAYM780201','AS_MeanAmphiMoment']]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Machine Learning\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Test " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Different algorithms are ran agasi the different features and the accuracy values of the different models is recorded. Ind addition a confusion matrix is uesd to add weight to accuray of the model. i.e. \n", - "True Positve and a False Negative.\n", - "* Logistic Regression \n", - "* Smote\n", - "* Near Miss \n", - "* Gaussian " - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.9171052631578948" - ] - }, - "execution_count": 30, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#X = Train[['FULL_AcidicMolPerc','FULL_AURR980107','FULL_DAYM780201','AS_MeanAmphiMoment']]\n", - "#X = Train[['FULL_Charge','FULL_AcidicMolPerc','FULL_AURR980107','FULL_DAYM780201','AS_MeanAmphiMoment']]\n", - "\n", - "## 'FULL_AURR980107'\n", - "\n", - "#X=Train[['FULL_AcidicMolPerc','FULL_AURR980107','FULL_DAYM780201','FULL_OOBM850104','AS_MeanAmphiMoment']]\n", - "\n", - "#'FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", - "# 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", - "# 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", - "# 'CLASS'\n", - "#\n", - "##Original data\n", - "\n", - "#First Test\n", - "### Train[['FULL_Charge','FULL_AcidicMolPerc','FULL_AURR980107','FULL_DAYM780201','FULL_OOBM850104','AS_MeanAmphiMoment']]\n", - "# Logistic 0.9013157894736842\n", - "# Smote 0.9263157894736842\n", - "# Near Miss 0.9263157894736842\n", - "# Gaussian 0.9394736842105263\n", - "\n", - "#Second Test\n", - "## Eliminating 'FULL_OOBM850104'\n", - "##X=Train[['FULL_Charge','FULL_AcidicMolPerc','FULL_AURR980107','FULL_DAYM780201','AS_MeanAmphiMoment']]\n", - "# Logistic Regression 0.8947368421052632\n", - "# Smote 0.9078947368421053\n", - "# Near Miss 0.9078947368421053\n", - "# Gaussian 0.9289473684210526\n", - "\n", - "\n", - "#There was a drop hence 'FULL_OOBM850104' is a good feature\n", - "\n", - "#Third Test\n", - "#,'FULL_AURR980107' eliminated \n", - "### Train[['FULL_Charge','FULL_AcidicMolPerc','FULL_DAYM780201','FULL_OOBM850104','AS_MeanAmphiMoment']]\n", - "#Logistic0.8986842105263158\n", - "# Smote 0.9210526315789473\n", - "#Near Miss 0.9210526315789473\n", - "#Gausian 0.9394736842105263\n", - "\n", - "# There was no big difference hence we can eliminate it.\n", - "\n", - "#Fourth Test\n", - "## Train[['FULL_AcidicMolPerc','FULL_DAYM780201','FULL_OOBM850104','AS_MeanAmphiMoment']]\n", - "#Logistic 0.8973684210526316\n", - "#Gausian 0.8973684210526316\n", - "\n", - "#The Sixth Feature\n", - "#Eliminating ,'FULL_AcidicMolPerc'\n", - "#Train[['FULL_Charge','FULL_DAYM780201','FULL_OOBM850104','AS_MeanAmphiMoment']]\n", - "#Logistic Regresssion 0.8828947368421053\n", - "#Smote 0.8921052631578947\n", - "#Near Miss 0.8921052631578947\n", - "#Gaussian 0.9105263157894737\n", - "#7th Feature\n", - "# Eliminating 'AS_MeanAmphiMoment'\n", - "#Train[['FULL_Charge','FULL_DAYM780201','FULL_AcidicMolPerc','FULL_OOBM850104',]]\n", - "#Logistic Regression 0.8473684210526315\n", - "#Smote 0.881578947368421\n", - "#Near Miss 0.881578947368421\n", - "#Gaussian 0.9\n", - "\n", - "#8th Test\n", - "#inluding Feature NT_EFC195\n", - "\n", - "#Trail\n", - "#Train[['FULL_Charge']] = Train[['FULL_Charge']] ** 2\n", - "#Train[['FULL_DAYM780201']] = Train[['FULL_DAYM780201']] ** 2\n", - "#Train[['FULL_OOBM850104']] = Train[['FULL_OOBM850104']] ** 2\n", - "X =Train[['FULL_Charge','FULL_AcidicMolPerc','FULL_DAYM780201','FULL_OOBM850104','AS_MeanAmphiMoment']]\n", - "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state = 25, stratify=y)\n", - "y_train.value_counts()\n", - "lr = LogisticRegression()\n", - "lr.fit(X_train, y_train)\n", - "\n", - "y_pred = lr.predict(X_test)\n", - "\n", - "confusion_matrix(y_test, y_pred)\n", - "\n", - "accuracy_score(y_test, y_pred)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Second Test" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "I try to tranform my data to cater for the negative values in my column and well as keeping track of the confusion matrix as well as the accuracy." - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [], - "source": [ - "##Train[['FULL_Charge']] = Train[['FULL_Charge']] ** 2\n", - "#X =Train[['FULL_Charge','FULL_AcidicMolPerc','FULL_DAYM780201','FULL_OOBM850104','AS_MeanAmphiMoment']]\n", - "#X_train, X_test, y_train, y_test = train_test_split(X, y, random_state = 1, stratify=y)\n", - "#y_train.value_counts()\n", - "#lr = LogisticRegression()\n", - "#lr.fit(X_train, y_train)\n", - "\n", - "#y_pred = lr.predict(X_test)\n", - "\n", - "#confusion_matrix(y_test, y_pred)\n", - "\n", - "#accuracy_score(y_test, y_pred)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# SMOTE" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.9210526315789473" - ] - }, - "execution_count": 32, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "smt = SMOTE()\n", - "X_train, y_train = smt.fit_sample(X_train, y_train)\n", - "np.bincount(y_train)\n", - "\n", - "lr = LogisticRegression()\n", - "lr.fit(X_train, y_train)\n", - "\n", - "y_pred = lr.predict(X_test)\n", - "\n", - "confusion_matrix(y_test, y_pred)\n", - "\n", - "accuracy_score(y_test, y_pred)\n", - "\n", - "recall_score(y_test, y_pred)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Nearmiss" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[347 33]\n", - " [ 30 350]]\n", - "0.9210526315789473\n" - ] - } - ], - "source": [ - "nr = NearMiss()\n", - "X_train, y_train = nr.fit_sample(X_train, y_train)\n", - "np.bincount(y_train)\n", - "\n", - "lr = LogisticRegression()\n", - "lr.fit(X_train, y_train)\n", - "\n", - "y_pred = lr.predict(X_test)\n", - "\n", - "print(confusion_matrix(y_test, y_pred))\n", - "\n", - "accuracy_score(y_test, y_pred)\n", - "\n", - "print(recall_score(y_test, y_pred))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Gaussian" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[344 36]\n", - " [ 20 360]]\n", - "0.9263157894736842\n", - "0.9473684210526315\n", - "[[344 36]\n", - " [ 20 360]]\n", - "0.9473684210526315\n" - ] - } - ], - "source": [ - "gnb = GaussianNB()\n", - "y_pred = gnb.fit(X_train, y_train).predict(X_test)\n", - "print(confusion_matrix(y_test,y_pred))\n", - "print(accuracy_score(y_test,y_pred))\n", - "\n", - "smt = SMOTE()\n", - "X_train, y_train = smt.fit_sample(X_train, y_train)\n", - "np.bincount(y_train)\n", - "\n", - "gnb = GaussianNB()\n", - "gnb.fit(X_train, y_train)\n", - "\n", - "y_pred = gnb.predict(X_test)\n", - "confusion_matrix(y_test, y_pred)\n", - "accuracy_score(y_test, y_pred)\n", - "print(recall_score(y_test, y_pred))\n", - "\n", - "\n", - "nr = NearMiss()\n", - "X_train, y_train = nr.fit_sample(X_train, y_train)\n", - "np.bincount(y_train)\n", - "\n", - "gnb = GaussianNB()\n", - "gnb.fit(X_train, y_train)\n", - "\n", - "y_pred = gnb.predict(X_test)\n", - "print(confusion_matrix(y_test, y_pred))\n", - "accuracy_score(y_test, y_pred)\n", - "print(recall_score(y_test, y_pred))\n", - "\n", - "\n", - "### Test for 94% accuracy\n", - "\n", - "X_trained = Test[['FULL_Charge','FULL_AcidicMolPerc','FULL_DAYM780201','FULL_OOBM850104','AS_MeanAmphiMoment']]\n", - "#X_trained = Test[['FULL_Charge','FULL_AcidicMolPerc','FULL_DAYM780201','FULL_OOBM850104','AS_MeanAmphiMoment']]\n", - "y_pred = gnb.predict(X_trained).astype(int)\n", - "#y_pred\n", - "#savetxt('data.csv', y_pred, delimiter=',',fmt=\"%d\",header=\"CLASS\")\n", - "test = pd.DataFrame(y_pred,columns=['CLASS'])\n", - "test.to_csv(\"Test_data.csv\",sep=\",\",index=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Nueral Networks" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[ 74 306]\n", - " [353 27]]\n", - "0.13289473684210526\n", - "0.07105263157894737\n", - "[[344 36]\n", - " [ 20 360]]\n", - "0.9473684210526315\n" - ] - } - ], - "source": [ - "clf = MLPClassifier(solver='lbfgs', alpha=1e-5,hidden_layer_sizes=(5, 2), random_state=1)\n", - "y_pred = clf.fit(X, y).predict(X_test)\n", - "print(confusion_matrix(y_test, y_pred))\n", - "print(accuracy_score(y_test,y_pred))\n", - "\n", - "##Balancing the data set using smote\n", - "smt = SMOTE()\n", - "X_train, y_train = smt.fit_sample(X_train, y_train)\n", - "np.bincount(y_train)\n", - "##Re runnings the algorithm.\n", - "clf = MLPClassifier(solver='lbfgs', alpha=1e-5,hidden_layer_sizes=(5, 2), random_state=1)\n", - "clf.fit(X_train, y_train)\n", - "y_pred = clf.predict(X_test)\n", - "confusion_matrix(y_test, y_pred)\n", - "accuracy_score(y_test, y_pred)\n", - "print(recall_score(y_test, y_pred))\n", - "\n", - "##Near Miss\n", - "\n", - "nr = NearMiss()\n", - "X_train, y_train = nr.fit_sample(X_train, y_train)\n", - "np.bincount(y_train)\n", - "\n", - "#clf = MLPClassifier(solver='lbfgs', alpha=1e-5,hidden_layer_sizes=(5, 2), random_state=1)\n", - "clf = MLPClassifier(solver='lbfgs', alpha=1e-5,hidden_layer_sizes=(5, 2), random_state=1)\n", - "clf.fit(X_train, y_train)\n", - "y_pred = gnb.predict(X_test)\n", - "print(confusion_matrix(y_test, y_pred))\n", - "accuracy_score(y_test, y_pred)\n", - "print(recall_score(y_test, y_pred))\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Stockastic Gradient" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The model doesn't work well after balancing the data for the class model with SMOTE and Near Miss but the " - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[380 0]\n", - " [157 223]]\n", - "0.7934210526315789\n", - "0.07105263157894737\n", - "[[ 74 306]\n", - " [353 27]]\n", - "0.07105263157894737\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/conda/lib/python3.6/site-packages/sklearn/linear_model/_stochastic_gradient.py:557: ConvergenceWarning: Maximum number of iteration reached before convergence. Consider increasing max_iter to improve the fit.\n", - " ConvergenceWarning)\n" - ] - } - ], - "source": [ - "SGDC = SGDClassifier(loss=\"hinge\", penalty=\"l2\", max_iter=30)\n", - "y_pred = SGDC.fit(X, y).predict(X_test)\n", - "print(confusion_matrix(y_test, y_pred))\n", - "print(accuracy_score(y_test,y_pred))\n", - "\n", - "##Balancing the data set using smote\n", - "smt = SMOTE()\n", - "X_train, y_train = smt.fit_sample(X_train, y_train)\n", - "np.bincount(y_train)\n", - "##Re runnings the algorithm.\n", - "SGDC = MLPClassifier(solver='lbfgs', alpha=1e-5,hidden_layer_sizes=(5, 2), random_state=1)\n", - "SGDC.fit(X_train, y_train)\n", - "y_pred = SGDC.predict(X_test)\n", - "confusion_matrix(y_test, y_pred)\n", - "accuracy_score(y_test, y_pred)\n", - "print(recall_score(y_test, y_pred))\n", - "\n", - "##Near Miss\n", - "\n", - "nr = NearMiss()\n", - "X_train, y_train = nr.fit_sample(X_train, y_train)\n", - "np.bincount(y_train)\n", - "\n", - "SGDC = MLPClassifier(solver='lbfgs', alpha=1e-5,hidden_layer_sizes=(5, 2), random_state=1)\n", - "SGDC.fit(X_train, y_train)\n", - "y_pred = SGDC.predict(X_test)\n", - "print(confusion_matrix(y_test, y_pred))\n", - "accuracy_score(y_test, y_pred)\n", - "print(recall_score(y_test, y_pred))\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Support vector machines" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[358 22]\n", - " [ 29 351]]\n", - "0.9328947368421052\n" - ] - } - ], - "source": [ - "SVM = svm.SVC()\n", - "y_pred = SVM.fit(X_train,y_train).predict(X_test)\n", - "print(confusion_matrix(y_test, y_pred))\n", - "print(accuracy_score(y_test,y_pred))\n", - "\n", - "##Balancing the data set using smote\n", - "#smt = SMOTE()\n", - "#X_train, y_train = smt.fit_sample(X_train, y_train)\n", - "#np.bincount(y_train)\n", - "##Re runnings the algorithm.\n", - "#SVM = svm.SVC()\n", - "#SVM .fit(X_train, y_train)\n", - "#y_pred = SGDC.predict(X_test)\n", - "#confusion_matrix(y_test, y_pred)\n", - "#accuracy_score(y_test, y_pred)\n", - "#print(recall_score(y_test, y_pred))\n", - "\n", - "##Near Miss\n", - "\n", - "#nr = NearMiss()\n", - "#X_train, y_train = nr.fit_sample(X_train, y_train)\n", - "#np.bincount(y_train)\n", - "# Testing\n", - "#SVM = svm.SVC()\n", - "#SVM.fit(X_train, y_train)\n", - "#y_pred = SGDC.predict(X_test)\n", - "#print(confusion_matrix(y_test, y_pred))\n", - "#accuracy_score(y_test, y_pred)\n", - "#print(recall_score(y_test, y_pred))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "For the different model checked.These two below perfomed the best most times.\n", - "* Logistic Regression\n", - "* Gaussian\n", - "* Neural Networks" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Submission" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201FULL_GEOR030101FULL_OOBM850104NT_EFC195AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CT_RACS820104
count758.000000758.000000758.000000758.000000758.000000758.000000758.000000758.000000758.000000758.000000758.000000
mean2.0738798.9450910.97304673.8218910.994212-2.3979220.08443315.57006773.8442045.9044921.250189
std4.2306157.8144490.1106768.0295240.0323701.5971380.27821911.3625898.9151930.6569110.218102
min-13.0000000.0000000.69900047.0000000.889000-7.8440000.0000000.06000047.0000003.8430000.841000
25%-0.5000002.7217500.89400068.7402500.973000-3.4572500.0000005.70900068.3460005.4712501.096000
50%2.0000007.5000000.96500074.0695000.994000-2.2380000.00000015.05700073.6460005.9355001.188000
75%4.00000014.2302501.05350079.2847501.013000-1.3062500.00000025.29025080.0692506.3752501.378500
max30.00000044.1180001.431000102.9290001.1820002.0170001.00000050.098000102.9290007.5880002.283000
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" - ], - "text/plain": [ - " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n", - "count 758.000000 758.000000 758.000000 758.000000 \n", - "mean 2.073879 8.945091 0.973046 73.821891 \n", - "std 4.230615 7.814449 0.110676 8.029524 \n", - "min -13.000000 0.000000 0.699000 47.000000 \n", - "25% -0.500000 2.721750 0.894000 68.740250 \n", - "50% 2.000000 7.500000 0.965000 74.069500 \n", - "75% 4.000000 14.230250 1.053500 79.284750 \n", - "max 30.000000 44.118000 1.431000 102.929000 \n", - "\n", - " FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n", - "count 758.000000 758.000000 758.000000 758.000000 \n", - "mean 0.994212 -2.397922 0.084433 15.570067 \n", - "std 0.032370 1.597138 0.278219 11.362589 \n", - "min 0.889000 -7.844000 0.000000 0.060000 \n", - "25% 0.973000 -3.457250 0.000000 5.709000 \n", - "50% 0.994000 -2.238000 0.000000 15.057000 \n", - "75% 1.013000 -1.306250 0.000000 25.290250 \n", - "max 1.182000 2.017000 1.000000 50.098000 \n", - "\n", - " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 \n", - "count 758.000000 758.000000 758.000000 \n", - "mean 73.844204 5.904492 1.250189 \n", - "std 8.915193 0.656911 0.218102 \n", - "min 47.000000 3.843000 0.841000 \n", - "25% 68.346000 5.471250 1.096000 \n", - "50% 73.646000 5.935500 1.188000 \n", - "75% 80.069250 6.375250 1.378500 \n", - "max 102.929000 7.588000 2.283000 " - ] - }, - "execution_count": 38, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Test.describe()" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FULL_Charge 0\n", - "FULL_AcidicMolPerc 0\n", - "FULL_AURR980107 0\n", - "FULL_DAYM780201 0\n", - "FULL_GEOR030101 0\n", - "FULL_OOBM850104 0\n", - "NT_EFC195 0\n", - "AS_MeanAmphiMoment 0\n", - "AS_DAYM780201 0\n", - "AS_FUKS010112 0\n", - "CT_RACS820104 0\n", - "CLASS 0\n", - "dtype: int64\n", - "FULL_Charge 0\n", - "FULL_AcidicMolPerc 0\n", - "FULL_AURR980107 0\n", - "FULL_DAYM780201 0\n", - "FULL_GEOR030101 0\n", - "FULL_OOBM850104 0\n", - "NT_EFC195 0\n", - "AS_MeanAmphiMoment 0\n", - "AS_DAYM780201 0\n", - "AS_FUKS010112 0\n", - "CT_RACS820104 0\n", - "CLASS 0\n", - "dtype: int64\n" - ] - } - ], - "source": [ - "print(Train.isna().sum())\n", - "print(Train.isnull().sum())" - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "metadata": {}, - "outputs": [], - "source": [ - "###\n", - "#'FULL_AURR980107'\n", - "##This attribute has outliers greater than 13 \n", - "#Test['FULL_AURR980107']\n", - "#FAURR = np.array(Test['FULL_AURR980107'])\n", - "#FAURR[FAURR >= 13]= FAURR.mean()\n", - "#Test['FULL_AURR980107'] = pd.DataFrame(FAURR)\n", - "\n", - "\n", - "##Removing the outliers and replacing them with the mean\n", - "##Values greater than 10 and values less than -6\n", - "#FCharge = np.array(Test['FULL_Charge'])\n", - "#FCharge[ FCharge >= 10 ]= FCharge.mean()\n", - "#FCharge[ FCharge <= -6 ]= FCharge.mean()\n", - "#Test['FULL_Charge'] = pd.DataFrame(FCharge)\n", - "\n", - "##Removing outliers for values\n", - "#Test['FULL_DAYM780201']\n", - "#FDAY = np.array(Train['FULL_DAYM780201'])\n", - "#FDAY[FDAY >= 95]= FDAY.mean()\n", - "#FDAY[FDAY <= 52]= FDAY.mean()\n", - "#Test['FULL_DAYM780201'] = pd.DataFrame(FDAY)\n", - "### \n", - "#Removing outliers greater\n", - "#Test[['FULL_AcidicMolPerc']] \n", - "#FAcidic = np.array(Train['FULL_AcidicMolPerc'])\n", - "#FAcidic[ FAcidic >= 27 ]= FCharge.mean()\n", - "#Test['FULL_AcidicMolPerc'] = pd.DataFrame(FAcidic)" - ] - }, - { - "cell_type": "code", - "execution_count": 41, - "metadata": {}, - "outputs": [], - "source": [ - "smt = SMOTE()\n", - "X_train, y_train = smt.fit_sample(X, y)\n", - "np.bincount(y_train)\n", - "\n", - "gnb = GaussianNB()\n", - "gnb.fit(X, y)\n", - "X_trained = Test[['FULL_Charge','FULL_AcidicMolPerc','FULL_DAYM780201','FULL_OOBM850104','AS_MeanAmphiMoment']]\n", - "#X_trained = Test[['FULL_Charge','FULL_AcidicMolPerc','FULL_DAYM780201','FULL_OOBM850104','AS_MeanAmphiMoment']]\n", - "y_pred = gnb.predict(X_trained).astype(int)\n", - "#y_pred\n", - "#savetxt('data.csv', y_pred, delimiter=',',fmt=\"%d\",header=\"CLASS\")\n", - "test = pd.DataFrame(y_pred,columns=['CLASS'])\n", - "test.to_csv(\"outliers_avail.csv\",sep=\",\",index=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Voting Classfier" - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[358 22]\n", - " [ 22 358]]\n", - "0.9421052631578948\n" - ] - } - ], - "source": [ - "nr = NearMiss()\n", - "X_train, y_train = nr.fit_sample(X_train, y_train)\n", - "np.bincount(y_train)\n", - "ensemble=VotingClassifier(estimators=[('gnb', gnb),('clf',clf),('SVM',SVM)], voting='hard')\n", - "y_pred =ensemble.fit(X_train,y_train).predict(X_test)\n", - "print(confusion_matrix(y_test, y_pred))\n", - "accuracy_score(y_test, y_pred)\n", - "print(recall_score(y_test, y_pred))\n", - "X_trained = Test[['FULL_Charge','FULL_AcidicMolPerc','FULL_DAYM780201','FULL_OOBM850104','AS_MeanAmphiMoment']]\n", - "y_pred = ensemble.predict(X_trained).astype(int)\n", - "test = pd.DataFrame(y_pred,columns=['CLASS'])\n", - "test.to_csv(\"New.csv\",sep=\",\",index=True)\n" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.6" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/Assignment Colab/nsangi-olga-tendo(1).ipynb b/Assignment Colab/nsangi-olga-tendo(1).ipynb deleted file mode 100644 index d89b5b1..0000000 --- a/Assignment Colab/nsangi-olga-tendo(1).ipynb +++ /dev/null @@ -1,2491 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# **ACE Class competition**\n", - "#### By Nsangi Olga Tendo\n", - "## Machine Learning Process:\n", - "#### 1. Have a peek of raw data\n", - "#### 2. Review of dimensions of thedataset.\n", - "#### 3. Review of attribues in the data set\n", - "#### 4. Review the data types of attributes in your data.\n", - "#### 5. Review of missing data(NAs)\n", - "#### 6. Summary of data using descriptive statistics.\n", - "#### 7. Understand the relationships in your data using correlations.\n", - "#### 8. Data Visualisation\n", - "#### 9. Review the skew of the distributions of each attribute.\n", - "#### 10.Spot checking classification algorithms\n", - "#### 11.Data preparation\n", - "#### 12.Feature selection\n", - "#### 13. Machine learning" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", - "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\n", - "/kaggle/input/ace-class-assignment/Test.csv\n" - ] - } - ], - "source": [ - "# This Python 3 environment comes with many helpful analytics libraries installed\n", - "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", - "# For example, here's several helpful packages to load in \n", - "\n", - "#Importing the necessary libraries that are going to be used in the pipeline\n", - "import numpy as np # linear algebra\n", - "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", - "import matplotlib.pyplot as plt\n", - "import seaborn as sns\n", - "\n", - "\n", - "# Input data files are available in the \"../input/\" directory.\n", - "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", - "\n", - "import os\n", - "for dirname, _, filenames in os.walk('/kaggle/input'):\n", - " for filename in filenames:\n", - " print(os.path.join(dirname, filename))\n", - "# Any results you write to the current directory are saved as output.\n", - "import warnings\n", - "warnings.filterwarnings('ignore')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### 1. Naming the Training and test dataset using." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0", - "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a" - }, - "outputs": [], - "source": [ - "Train = pd.read_csv(\"../input/ace-class-assignment/AMP_TrainSet.csv\")\n", - "Test = pd.read_csv(\"../input/ace-class-assignment/Test.csv\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Confirming that the data has been read in and assigned to variables Train and Test" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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" - ], - "text/plain": [ - " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n", - "0 5.0 0.000 0.951 74.842 \n", - "1 4.0 5.405 0.931 71.595 \n", - "2 5.5 5.405 0.873 73.595 \n", - "3 5.0 4.167 0.895 66.250 \n", - "4 7.5 8.537 0.932 64.720 \n", - "5 5.0 7.692 1.030 78.949 \n", - "6 3.0 6.897 0.930 78.586 \n", - "7 2.0 5.882 0.868 76.588 \n", - "8 7.0 2.632 0.857 60.447 \n", - "9 9.0 0.000 0.911 65.808 \n", - "\n", - " FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n", - "0 0.975 -3.663 0 0.282 \n", - "1 0.957 -4.011 1 0.600 \n", - "2 0.961 -2.512 0 0.593 \n", - "3 0.999 -1.362 0 0.614 \n", - "4 0.979 -2.091 0 0.616 \n", - "5 0.976 -3.091 1 0.511 \n", - "6 0.957 -3.544 1 0.385 \n", - "7 0.949 -5.832 0 0.154 \n", - "8 1.012 -0.292 0 0.188 \n", - "9 1.049 -3.888 0 0.361 \n", - "\n", - " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 CLASS \n", - "0 73.444 5.661 1.041 1 \n", - "1 68.222 6.537 1.453 1 \n", - "2 69.444 4.934 1.722 1 \n", - "3 67.222 4.316 1.382 1 \n", - "4 72.944 4.540 1.539 1 \n", - "5 78.778 5.992 1.091 1 \n", - "6 78.222 6.284 1.467 1 \n", - "7 76.588 6.479 1.086 1 \n", - "8 64.333 3.849 1.925 1 \n", - "9 63.222 6.327 1.216 1 " - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Train.head(10)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### 2. Dimensions of the train and test data set\n", - "#### This helps in knowing the size of your data set and also give an intiution on what algorithms you could use incase the size is big or small." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "((3038, 12), (758, 11))" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Train.shape, Test.shape" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### 3. Establishing the attributes in the train and test data set" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", - " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", - " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", - " 'CLASS'],\n", - " dtype='object'),\n", - " Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", - " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", - " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112',\n", - " 'CT_RACS820104'],\n", - " dtype='object'))" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Train.columns, Test.columns" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### 4. Establishing the data types for each attribute in the train data set. This helps in finding out which columns have data types like strings that may need to be converted to foating points or integers to represent categorical or ordinal values since most machine learning algorithms take in integers or floats for inputs. This can be done using df.dtype method or the df.info() method as shown in the two cells below, tho the df.info() is more informative as its also tells the total number of instances for each column." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(FULL_Charge float64\n", - " FULL_AcidicMolPerc float64\n", - " FULL_AURR980107 float64\n", - " FULL_DAYM780201 float64\n", - " FULL_GEOR030101 float64\n", - " FULL_OOBM850104 float64\n", - " NT_EFC195 int64\n", - " AS_MeanAmphiMoment float64\n", - " AS_DAYM780201 float64\n", - " AS_FUKS010112 float64\n", - " CT_RACS820104 float64\n", - " CLASS int64\n", - " dtype: object,\n", - " FULL_Charge float64\n", - " FULL_AcidicMolPerc float64\n", - " FULL_AURR980107 float64\n", - " FULL_DAYM780201 float64\n", - " FULL_GEOR030101 float64\n", - " FULL_OOBM850104 float64\n", - " NT_EFC195 int64\n", - " AS_MeanAmphiMoment float64\n", - " AS_DAYM780201 float64\n", - " AS_FUKS010112 float64\n", - " CT_RACS820104 float64\n", - " dtype: object)" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Train.dtypes, Test.dtypes" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "RangeIndex: 3038 entries, 0 to 3037\n", - "Data columns (total 12 columns):\n", - "FULL_Charge 3038 non-null float64\n", - "FULL_AcidicMolPerc 3038 non-null float64\n", - "FULL_AURR980107 3038 non-null float64\n", - "FULL_DAYM780201 3038 non-null float64\n", - "FULL_GEOR030101 3038 non-null float64\n", - "FULL_OOBM850104 3038 non-null float64\n", - "NT_EFC195 3038 non-null int64\n", - "AS_MeanAmphiMoment 3038 non-null float64\n", - "AS_DAYM780201 3038 non-null float64\n", - "AS_FUKS010112 3038 non-null float64\n", - "CT_RACS820104 3038 non-null float64\n", - "CLASS 3038 non-null int64\n", - "dtypes: float64(10), int64(2)\n", - "memory usage: 284.9 KB\n" - ] - } - ], - "source": [ - "Train.info()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### 5. Establishing if there are any missing values in the attributes of the data set. This helps to give an insight on how to handle the missing values, whether to remove rows that have missing values or establishing a method like the mean,median ect to impute the NAs. " - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "FULL_Charge 0\n", - "FULL_AcidicMolPerc 0\n", - "FULL_AURR980107 0\n", - "FULL_DAYM780201 0\n", - "FULL_GEOR030101 0\n", - "FULL_OOBM850104 0\n", - "NT_EFC195 0\n", - "AS_MeanAmphiMoment 0\n", - "AS_DAYM780201 0\n", - "AS_FUKS010112 0\n", - "CT_RACS820104 0\n", - "CLASS 0\n", - "dtype: int64" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Train.isna().sum()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### 6. Descriptive statistics summary of the data in each column.\n", - "#### This includes measures of central tendencies like teh mean, median and measures of spread like standard, variance, range and interquatile range. The smallest and largest values of each column are also returned. This helps in understanding the distribution of data in each column. This way you can also find out if you have negative values in any attribute. This also helps in understanding the scales at which each attribute is at." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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" - ], - "text/plain": [ - " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n", - "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", - "mean 2.060237 8.521520 0.971410 73.668760 \n", - "std 3.819929 7.586652 0.107413 8.527489 \n", - "min -16.000000 0.000000 0.684000 42.750000 \n", - "25% 0.000000 2.516000 0.895000 68.294000 \n", - "50% 2.000000 7.143000 0.963000 74.059500 \n", - "75% 4.000000 13.158000 1.041000 79.343750 \n", - "max 30.000000 46.667000 1.451000 101.682000 \n", - "\n", - " FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n", - "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", - "mean 0.994007 -2.432927 0.088545 15.683233 \n", - "std 0.031333 1.707223 0.284133 11.575665 \n", - "min 0.866000 -10.432000 0.000000 0.041000 \n", - "25% 0.974000 -3.606000 0.000000 5.587500 \n", - "50% 0.994000 -2.296500 0.000000 14.988500 \n", - "75% 1.011000 -1.283250 0.000000 26.807750 \n", - "max 1.196000 3.576000 1.000000 51.280000 \n", - "\n", - " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 CLASS \n", - "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", - "mean 73.650828 5.911361 1.235255 0.500000 \n", - "std 9.166092 0.693689 0.210012 0.500082 \n", - "min 42.778000 3.533000 0.785000 0.000000 \n", - "25% 67.556000 5.459250 1.082000 0.000000 \n", - "50% 73.697000 5.925500 1.184000 0.500000 \n", - "75% 79.778000 6.382000 1.351000 1.000000 \n", - "max 103.167000 8.662000 2.192000 1.000000 " - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Train.describe()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### From the values above, there are no missing values since all counts in each column is equal. We can also observe that there are negative values in some attributes have a minimum values in negatives." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Since this is a classification problem, its important to check out the propotions of the values in the class to be predicted as its possible one class may have more values as compared to the others. Incases where one class is higher than another class we could employe methods likes smote to over sample the least represented class so as to have an un biased algorithm." - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0, 0.5, 'Distirbution')" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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CLASS0.534602-0.598816-0.584111-0.554838-0.260470-0.4532870.2607020.693552-0.4371680.0334320.2676521.000000
\n", - "
" - ], - "text/plain": [ - " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 \\\n", - "FULL_Charge 1.000000 -0.612996 -0.490977 \n", - "FULL_AcidicMolPerc -0.612996 1.000000 0.794796 \n", - "FULL_AURR980107 -0.490977 0.794796 1.000000 \n", - "FULL_DAYM780201 -0.434603 0.541481 0.548253 \n", - "FULL_GEOR030101 -0.058725 0.115201 0.346139 \n", - "FULL_OOBM850104 -0.283758 0.513344 0.462712 \n", - "NT_EFC195 0.088068 -0.143168 -0.169540 \n", - "AS_MeanAmphiMoment 0.355477 -0.431590 -0.426097 \n", - "AS_DAYM780201 -0.365374 0.449621 0.456260 \n", - "AS_FUKS010112 -0.090570 0.002334 0.032958 \n", - "CT_RACS820104 0.232929 -0.213543 -0.403599 \n", - "CLASS 0.534602 -0.598816 -0.584111 \n", - "\n", - " FULL_DAYM780201 FULL_GEOR030101 FULL_OOBM850104 \\\n", - "FULL_Charge -0.434603 -0.058725 -0.283758 \n", - "FULL_AcidicMolPerc 0.541481 0.115201 0.513344 \n", - "FULL_AURR980107 0.548253 0.346139 0.462712 \n", - "FULL_DAYM780201 1.000000 0.010118 0.334778 \n", - "FULL_GEOR030101 0.010118 1.000000 0.319157 \n", - "FULL_OOBM850104 0.334778 0.319157 1.000000 \n", - "NT_EFC195 -0.090058 -0.230417 -0.230561 \n", - "AS_MeanAmphiMoment -0.408793 -0.160269 -0.336297 \n", - "AS_DAYM780201 0.894191 -0.029085 0.275640 \n", - "AS_FUKS010112 0.055915 0.040480 -0.452769 \n", - "CT_RACS820104 -0.326792 -0.151935 0.155304 \n", - "CLASS -0.554838 -0.260470 -0.453287 \n", - "\n", - " NT_EFC195 AS_MeanAmphiMoment AS_DAYM780201 \\\n", - "FULL_Charge 0.088068 0.355477 -0.365374 \n", - "FULL_AcidicMolPerc -0.143168 -0.431590 0.449621 \n", - "FULL_AURR980107 -0.169540 -0.426097 0.456260 \n", - "FULL_DAYM780201 -0.090058 -0.408793 0.894191 \n", - "FULL_GEOR030101 -0.230417 -0.160269 -0.029085 \n", - "FULL_OOBM850104 -0.230561 -0.336297 0.275640 \n", - "NT_EFC195 1.000000 0.178683 -0.036844 \n", - "AS_MeanAmphiMoment 0.178683 1.000000 -0.322378 \n", - "AS_DAYM780201 -0.036844 -0.322378 1.000000 \n", - "AS_FUKS010112 0.145924 0.025580 0.045562 \n", - "CT_RACS820104 0.080898 0.171524 -0.256060 \n", - "CLASS 0.260702 0.693552 -0.437168 \n", - "\n", - " AS_FUKS010112 CT_RACS820104 CLASS \n", - "FULL_Charge -0.090570 0.232929 0.534602 \n", - "FULL_AcidicMolPerc 0.002334 -0.213543 -0.598816 \n", - "FULL_AURR980107 0.032958 -0.403599 -0.584111 \n", - "FULL_DAYM780201 0.055915 -0.326792 -0.554838 \n", - "FULL_GEOR030101 0.040480 -0.151935 -0.260470 \n", - "FULL_OOBM850104 -0.452769 0.155304 -0.453287 \n", - "NT_EFC195 0.145924 0.080898 0.260702 \n", - "AS_MeanAmphiMoment 0.025580 0.171524 0.693552 \n", - "AS_DAYM780201 0.045562 -0.256060 -0.437168 \n", - "AS_FUKS010112 1.000000 -0.445284 0.033432 \n", - "CT_RACS820104 -0.445284 1.000000 0.267652 \n", - "CLASS 0.033432 0.267652 1.000000 " - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Train.corr(method='pearson')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### From the summary above, AS_DAYM780201 and FULL_DAYM780201 are the strongest positively correlated with a correlation of 0.894191 while FULL_AcidicMolPerc and FULL_Charge are the strongest negatively correlated attributes. This correlation can further be observed by plotting a heat map using seaborn to show the correlation of attributes with each other as shown below" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure(figsize= (10,10))\n", - "sns.heatmap(Train.corr(method = 'pearson'), cmap='Purples', robust=True, square=True, annot= True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### 8. Using visualisation to understand the data at hand. Histograms, Density plots and Box and whisker plots are some of the plots used to understand the attribute distribution. Histograms were used. They're used to summarize discrete or continuous data by showing the number(frequency) of data points that fall within a specified range of values. Histograms graphically show center) of the data, spread (i.e., the scale) of the data, skewness of the data, presence of outliers and presence of multiple modes in the data" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "Train.hist(figsize=(10,10))\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### From the histograms above, we can observe that attributes AS_MeanAmphiMoment, AS_DAYM780201, AS_FUKS010112, FULL_DAYM780201, FULL_GEOR030101, FULL_AURR980107,FULL_CHARGE have a normal. We can also tell from these plots that attribute CT_RACS820104 and FULL_AcidicMolPerc are skewed to the right. We can also tell that attributes NT_EFC195 and CLASS are categorical attributes. This can also be observed using density plots as shown below." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Using Density plots. Density plots are used to observe the distribution of a variable in a dataset. The peaks of a Density Plot help display where values are concentrated over the interval. Density plots give a more precise location and also gives a continuous distribution view. " - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "Train.plot(kind='density', figsize=(10,10), subplots=True, layout=(4,3), sharex=False)\n", - "plt.show" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### From the above plots, FULL_Charge, FULL_AURR980107, FULL_DAYM780201, FULL_GEOR030101, CT_RACS820104, FULL_OOBM850104, AS_FUKS010112, AS_DAYM780201 show a normal distribution of variables. CLASS and NT_EFC195 are categorical data CLASS having equal number of instances while NT_EFC195 has a category that has almost all instances. \tFULL_AcidicMolPerc and AS_MeanAmphiMoment have more than one peak meaning that the data points are distribute at 2 peak for FULL_AcidicMolPerc and 3 peaks for AS_MeanAmphiMoment\t" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### 9. Checking for the skewness of the data. Skewness is deviation from a normal distribution. The data may be skewed to the left or to the right of the normal distribution curve (bell shaped). Since many machine learning algorithms assume normal distribution,this allows one to know what attributes need to be corrected of skewness to improve the accuracy of the model. Skewness can be observed with bar plots of .skew()." - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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tDnxn5v3p3bYlj6mqc4CzgCv2EaAkSdJUpKpWPiB5APAnVfXo7v3DgJtU1RNmjjmxO+b07v03u2POXPS3DgQOBNhrr71ufNppp/X53yIBsPdT379V//6pB91tq/79KfIz13pszfNla54rnufbtiRHV9Wm1Y5bS4vV6cCeM+/3AL633DFJdgAuB/x48R+qqoOralNVbdp1113X8E9LkiRNx1oSqy8C+yS5epKLAQ8Gjlh0zBHAI7rX9wc+Xqs1hUmSJM2ZHVY7oKrOSfJ44MPA9sAbqurEJM8FNlfVEcAhwJuTnExrqXrw1gxakiRpjFZNrACq6gPABxZte9bM618DD+g3NEmSpGmx8rokSVJPTKwkSZJ6sqauQEmS+mJZAc0zW6wkSZJ6YmIlSZLUExMrSZKknjjGSpKkNXBsmNbCFitJkqSemFhJkiT1xMRKkiSpJyZWkiRJPTGxkiRJ6omJlSRJUk9MrCRJknpiYiVJktQTC4RKusgsnChJjYmV5o5f8pKkodgVKEmS1BMTK0mSpJ6YWEmSJPXExEqSJKknJlaSJEk9MbGSJEnqiYmVJElST0ysJEmSemJiJUmS1BMTK0mSpJ6YWEmSJPXExEqSJKknJlaSJEk9MbGSJEnqSapqmH84OQM4bSv9+V2AH22lv721TTX2qcYN0419qnHDdGOfatww3dinGjdMN/apxg1bN/arVdWuqx00WGK1NSXZXFWbho7jwphq7FONG6Yb+1TjhunGPtW4YbqxTzVumG7sU40bxhG7XYGSJEk9MbGSJEnqybwmVgcPHcBFMNXYpxo3TDf2qcYN0419qnHDdGOfatww3dinGjeMIPa5HGMlSZI0hHltsZIkSdpwJlaSJEk9MbGSJEnqyVwlVmkemuRZ3fu9ktxk6LhWk+QFSS4/8/4KSf5pyJhWMxvvvEhyx6FjuLAWzvmpSHLPoWNYiyS7LHr/0CQvT3JgkgwV11okefNatk3FlK/PqUny9aFjWK8kOybZL8mVho5lrhIr4NXAzYH9u/c/A141XDhrdpeq+unCm6r6CXDXAeNZix8l+WiSA+YoyTpk6AAugkcPHcByktx30c/9gIMX3g8d3yo+svAiyTOAhwFHA3cEXjJUUGu07+ybJNsDNx4olj6M9vpM8gdJjkrynSQHJ7nCzL4vDBnbapL8LMnZ3c/PkvwMuObC9qHjW06S1ybZt3t9OeA44E3Al5Lsv+Ivb2U7DPmPbwU3raobJfkStAQlycWGDmoNtk9y8ar6DUCSnYCLDxzTak4CXkpLYv8lyWeAtwLvqapfDRrZCpIcsdwu4IobGct6rXCTC7DTRsayTocBHwJ+SIsV4FLAPYAC3jVQXGsx2yp1X+DWVfWLJG8BjhkophUleRrwdGCnmXMmwG8ZwVT0lUz4+nwN8BzgKNpDzmeS3LOqvgnsOGRga/BG4HLA31bV/wNI8q2quvqgUa3u1lX1593rRwFfr6p7J7kK8EHa99Eg5i2x+l33VFYASXYFzh02pDX5T+BjSf6DFvufAYcOG9KqfldV7wPe1yWC9wAeDLwqyYer6iHDhresWwMPBX6+aHuAsXcb/xT4w4Wb36wk3xkgnrW6OXAQ8EXgtVVVSW5TVY8aOK612CnJfrTW/e2r6hcAVfW7JP83bGhLq6p/Bv45yT9X1dOGjmedpnp9XrqqPtS9flGSo4EPJXkY3ffRWFXVE5LcGHhrkncDr2TkMXd+O/P6jsB/A1TVD4bupZ+3xOrlwOHAlZI8H7g/8IxhQ1pdVf1LkuOBO9BuIM+rqg8PHNZqzjtzuxaqw4DDuibZew8W1eqOAn5ZVZ9cvCPJ1waIZz3eBFwNuEBiBbxlg2NZs6r6Yjc+5gnAx5P8PdO4cQN8ny1dfj9OsltVfT/JFYFzBoxrVVX1tCS7086ZHWa2f2q4qFY11eszSS5XVWcBVNWRXZf3O4Gdhw1tdVV1dJI7AI8HPglcYuCQ1uKnSe4OfBe4JXAAQJIdGLgFf+4KhCa5DnB72hf/x6rqpIFDWlHXwvbhqrrD0LGsR5K/qaoXDR2HpqX7ov83YFNVXWPoeC6s7rq9eFX9cuhYlpPkIFor8leAhda1qqpJTByYkiQPAU6pqqMWbd8LeGZVPWaYyNYvyW7AflX1gaFjWUmSa9MaU64CvLSq3tht/xPgTlX1lMFim6fEKslSTwY/q6rfbXgw69CNK3jYwtOOtr4kVwZ2p7WcfG+p7rUx6loE78xM7LTE/Kcr/qIukiSbgD1prVTfqKqvDhzSqroWnusvjN2ckqlen1PVNUjci/PfV44Ye8PEWM3brMBjgDOArwPf6F5/K8kxXR/yWP0a+HKSQ7qp3C9P8vKhg1pJksslOSjJV5Oc2f2c1G0b7SzBbjruUcAngH8B/hX4ZDej50aDBreKJA+nneO3AS5JGwB+W+Dobt8oTfVcAUjyx0k208aIvQF4LHBIkk8k2XPY6FZ1CuMfOH0+U74+l5Nk7BMG/h54G62X5wu0sZChjbl66pCxrSTJY5Ls071Okv/oZjYe342LHC62OWuxei1w+ML4pCR3oj3dHwa8rKpuOmR8y0nyiKW2V9VoB7An+TDwceDQqvpBt+0qwCOAO1TVKGvOJDkWeGxVfX7R9psB/15VNxgmstV1LRA3Xdw6lTa1+/NVde1hIlvZVM8VgG6G8Z2q6owkVwdeUlX36caM/W1V3WngEJeV5J3ADYCPAee1WlXVXw0W1Cqmen0u01sCLUE5rqr22Mh41iOtZtW+i3t20mbUn1hV+wwT2cqSnEDrsvxd1xX7FOBOwH7As6vq1oPFNmeJ1eaq2rTUtiTHVtUNh4ptNd3Mur2qaswDNM+T5GtV9Xvr3Te0JN9Y7kaR5OSqutZGx7RW3Q3wDxd3GXfdg5tHfAOc5LkCkOT4qrp+93p74ItVdaPu/YlVte+Kf2BAE31gm+T1mTZD9DTOX56juve7V9Voy/4k+SrwJ1V12qLtVwM+Mtbrc/Y7Pa38yeer6mXd+2MWrtMhzNuswB/PNGsCPAj4SXdDHG3ZhST3AF4EXAy4epIbAs8d+SDT05L8Ha0VYqH2yZWBRwJjnvr/wSTvp82wW4hzT+DhtFpLY/Z84JgkH2FL7HvRpho/b7CoVjfVcwVgc5JDaK0+96J1UZHkksD2A8a1qqo6dGoPbEz3+jwFuH1VfXvxjoy7FArAk2jlfr7B+e8r16LNEhyrc9MG2v+ENmHt+TP7nBXYl7TlJ54N3Krb9BngucBZtJvLyUPFtpK0mie3Az5RVft1275cVX8wbGTL67qfnkr7sllYQuD/AUcAL6yqHw8V22qS3IUtAzUDnE4bqDnqWTBw3uf+J5w/9g931fpHaeLnyo7AY4Dr0io7v6Gq/q9LWK60+Cl/TGYf2KpqKg9sk7w+kzwO+ExVHbfEvidU1SsGCGvNkmxHqxM2+5l/sapGWasNIK3Uwr/THnDeuzDzMskfA39XVXcbLLZ5Say6VqmDqupvh45lvZJ8vqpumuRLM4nVeV0QkrReU3xg07gkuXRVLS7WOhppNasuM/tgudCaXFU/GyquuZkV2GXWY575t5ITusF32yfZJ8krgM8NHdSFlWS0FbWTbJ/ksUmel+QWi/aNvpjscpJ8eegYLowxnyurSfLBoWNYxTlLlHAZ9ZP0PF6fmfbi0V8ZOoCVVNU5C0lVNzPwdrTaVoP2Ts1NixVAkhcD+9BK2/9iYXtVjXktsoUM+x9oMxoAPgz8U1X9erioLrwk366qvYaOYylJXk8rVfAF2oK6n6yqv+72DTrgcTVZfsHi0JaK2XUj4+nDmM8VgCw/xT/A+6pqt42MZz1mxoY9Fbgf8FfAjrVlfbXRmfL1uZwJnON/vdwu4B+qatSV45PcFHgIcB9alfvH0bqOBxseMW+J1X8ssbmq6s82PJg1SlvP8GrAyVMq8pi2BM+Su4BrV9UoF5FeNMtrB+DVwC60xaSPWugyGaMkvwP+i6VbHe5fVZfZ4JDWZKrnCpw32+uTnH+214KbVdVoF79e9MAW2gPb88b8wDbV6zMrLx59u6q61EbGsx5Jfk2rF7bUEk1PrqpR1ppLW7bugcC3aQsuH06bHT344tFzlVhNTZJHAy8AvglcHTiwqpa7QEclyf+jDaJe/FQQ4HNVddWNj2p1Sb5aVddZtO1ZtP+WK421ZAGcN2bmEVV1whL7vlNVoyxYOdVzBc6rlXOfqvrGEvtG+5lP1VSvzyQ/YfnFo99eVVfe+KjWJsnngCdU1dFL7BvtOZ7kDOBrwEtprce/TnJKjWCprLkqt5DkErSFGPdlZhHJEbdYPYlWmO2MJNegtUZMIrEC3kdb0f3YxTuSfGLjw1mzzUnuXFtWoqeqnpvke8BrBoxrLZ4EnL3MvvtsZCDrNNVzBeA5LD8W9QkbGMe6pS3D83Rgb86/CPOYJ8VM9fqc6uLRAI8ClpuZu2mZ7WNwFVpr7P7AS5McCeyUZIeqGnSB9LlqsUry38BXaf2tzwX+FDipqp44aGDLWDxmYKpjCCSNT/eF/rfAl5mp4zfmEhHShdE1qtydlmTdCvhYVT1ksHjmLLH6UlXtt9BP39Wg+XBV3W7o2JaS5IdsKWYKbSX6897XiJeegDYLgy21TxYW7vxCjfykykQXHO3GnBxAa526Kltifw9wSI14sfEJnyt/DZxVVYcs2v4E2pTulw4T2eqSfKaqbrX6keMy1esTzit8O6nFo9NWbngacG9gYQLMD2n3lYOmNPYXIMllgcdU1YsHi2Hk97V1SfKFqrpJkk8Bfwn8gHbzHrzPdSlZZsmJBTXupSfuRBtY+g3gu93mPWjVev+yqj4yVGwrSavMvz8tgT2927wHXVJbVQcNFdtqkrwV+ClwKOeP/RHAzlX1oKFiW8lUzxU4b4zVjarqt4u2X5xWQHG03WpJbk871xevFTjaWdJTvT7TFv19DXA5zn+O/5R2jh8zVGyryYTX8lzO0DMx5y2xejTwTuD6wH8AlwaeVVWvHTSwOZTkJOAuVXXqou1XBz5QVb8/SGCryEQXHIXWtVPLr7n39RrvIsyTPFdg5YKaK+0bgyT/CVwHOJEtXYFjnyU9yeszE108Gla9r4x6Lc/lDD3ofq4Gr1fV67uXnwRG2Uo1K8l7WaFgX4176Ykd2PJEOeu7wI4bHMt6nEvrRls8zmQ3RryeZOcnSR4AvLOqzgUWlqJ4ABeccTcmUz1XgNa9s7hLp+vyGbsbjDnxW8ZUr89LLU6qAKrqqCSjLbXQOS3TXctzOYO2GM1VYtU1z9+PC86Cee5QMa3iRUMHcBG8Afhikrdx/oU7HwQcsuxvDW+qC45C6w55IfDqbnp3gMvTmvEfPGRgq1jqXNmTFvOYzxVo9X3en+QpwEJ3zo2Bf2H81+9RSa5bVaOunr3IVK/PqS4eDe2e/VTgk0kWr+X5wMGiWkXaahNLJVABBn3wmbeuwA/RFlw+Gjhv8cghB7GtVdfUvdCV87UxD0RekOS6wD254GKpo76RZ4ILji6W5Iq06/dHQ8eyFkl+n6UX1h31uQKQtijwU4Hr0W7kJ9IG9Y56SZuuC/aawLdoY6xC6woc7bgwmO71mQkuHj1lSfahJVCLW9WuRps4MNiyNvOWWJ1QVdcbOo71SnIb2oDkU2kX5J60QpCfGjCsdUuyyxS+6JPsBZxdVT9NsjetVstJVXXioIGtQZKb0L4cv9gltnemxT7qL3ltvCRXW2r72MstTPn6nKpuJubutOr2v5jZfr6aYmOS5H3A06vq+EXbNwHPrqp7DBPZHC3C3PlckqmNKQB4MXCnqvrjqvojWpXhfxs4phUluUuSbyX5TJL9kpwIfD7J6d1spFFK8lTaGLyjuskOHwLuAhyW5dfMGoUkz6YtMPqaJP8MvJI2QeNpSf5h0OBWkOTOM68vl+T1SY5P8paxj1VK8pGZ108bMpb16hKoywP36H4uP4GkarLX53KSHDx0DCtJ8le00gpPAE5Mcq+Z3S8YJqo12XtxUgVQVZtpw4EGMxctVjN9rTvQFmE+hWk1fR+/OMalto1JNwtmf9qN+33A3bqBmr8P/NdYC512CeAm2kKvpwLX6CrfXwr4/JhbPLvz/IbAxWmlRPYZIaKrAAAeDElEQVSoqrOT7ESLfZTnS2YK36YtsvsD4HXAfYE/rqp7DxnfStLVxuteT6qAb5InAo8BFsor3Ac4uKpeMVxUK5vq9ZlkuYWKAxxXVXtsZDzr0d1Xbl5VP+9aCN8BvLmqXjZ7/o9NkpOr6lrr3bcR5mXw+t2HDuAi2py2Ev2bu/d/ShsnNmbnLhTsS/LLqjoKoKpO6sZIjNX/VdWvkvwW+BVwJkBV/SJZap3dUTmnG2fyyyTfrKqzAbr/njHPmJq1qapu2L3+t6xSy20EpvzkeQBw04WunSQvBP4XGG1ixXSvzzNoMxlng6zu/ZWW/I3x2L6qfg5QVad2Q1Pe0XUlj/lD/2KSx1TV62Y3JjmAgb8/5yWxuhKwy+JxJknuQavaO+rmb+AvgMcBf0U7kT9FK6g4Zj9N8ljgsrQyAE8GDgPuwAUXIh2TY5K8BbgUrXDiod2kh9sBYx9I/dskl6yqX9JmpgHnVU4ec2J1pa4bJ8Blk6S2NJWPOQkHuEaSI2ixL7w+z8hLooSZSTzd6zF/UcJ0r89TgNtX1bcX70gy9pIFP0hyw+rW8uxaru5Om8075qE1TwIOTzLbELEJuBgDr506L12BnwAeuUQBwmvRmr5HuaTNlCXZE3gG7ansObRuwQNoSezf1EiXn0hbFuYBtLjfQZt99BDg28CrZgdujk2Si1fVb5bYvguwW1V9eYCwVtWNDZv16q575yrAv1TVw4eIay2S/PFK+2uJRXfHoktmHwEc3m26N/DGGvcyPJO8PpM8DvhMVR23xL4njLz7dQ9aa/gPlth3y6r67ABhrVmS29Jm7EIrIvvxIeOB+UmsVqqOfNxYq94mucDAu1ljHTOj4STTXHNvqpJcdqHLdYl9ey3VQjEmSW5EW5Q2wKeq6ksDh6QRWmYm5ler6oRBA5uoeekK3GmFfWOuensu7cvxLcB7aWMKJqN7UrgfrTzEObS14F5XVd8cNLAVJDmGNpj3rWOOcylZYc29JKNdc68b2Pt4WhJ4CPB04ObAScALqmrMVeM/ASwMvP9YVc3OeH33wr4xWTSQ+tTu57x9VfXjjY5prSZ+fU5y8ehuJuZjgd8keRHwN8BngX9MckhVvWTQACdoXhKrjyZ5PvCM2Sf3JP9Iq0o9SlV1w+5i3J+WXH2l+9+PVNU5gwa3iiQH0YqzfQy4Cq0I4Tdpgx5fUFX/PWR8K7gCbSbjkUl+ALwVeHtVfW/YsNbkZbRFUU+d3ZhuzT1grGvu/SfwZdq4sId2r18I3BF4I+3LaKxmxyQtnvk11vFKP6IVp1y4hyweUD3m5b4meX3m/ItHf6HbvAfw1iSjXTy68zDguiwzExMwsVqneekKvBTweloXybHd5hsAm4FHL8x4GLskDwJeBbywqv516HhWMtv92o2L+GRV3TLJFYBPj3ha9OzU/1vTbob3pbWevLWqRltzJm2Zj99fnHSnVe3/ypDTi1eS5NjuISLA6VW1++J9A4a3okXny/nKLYy1/EKSlwG3obU6vJU29mcSN/qpXp+Z6OLRsKW0T5Ltge8DV6kta5FOsuj20Oaixaob0Lh/kmsA+3abT6yqU2aPS7Jvjax6b5LdaWum3Ye2kO6T2TLYdMzOnelWuCqwPUBV/SQjnxe9oKo+DXw6yRNorScPAkZ54+5Mdc297bqE+zLApZPs3U3rviJtBs+Yzc5oXHhN937X4cJaXlU9sbsGb0NrjXhFWqHT11TVtwYNbh0mdn1OdfFoWH4m5u0Z90zM0ZqLFqu1GtsTZpJP0r5sDqPNgDnf2IeRj4V4EG0h2q8B1wH+oqren2RX4GVV9ZBBA1xG1yw/5gWLV5QJrrmXZH9gYSbaX9LKixSt++Efx9oKAUvOaDyfqvrHjYrlwkhyeVri/Tza8h+vW+VXBjXV6zNtdYFX0sY/XmDx6BrpsjCw5EzMm9JaCkc9E3PMtrXEalRVZJOcypYChLP/RyxUjB/zWIiFQbLXAE6uqp8OHc+2bOzTortuhlTVOd2N/IbAd6vq+wOH1oskT6uqfx46DjhvaMS9aC08u9IGg7+9qsZeT2nSMtHFoxdLsiOtfMF3q+qHQ8czRdtaYjWqFqt5lOT3aHWsHjN0LEvJKuuNjXkGTJecPJB24/5QVZ3QFfJ7OrDTmB4aZnVT/pdVVcdsVCxby5juLUl+QWs5eStwMouqx1fVu5b6vTGY6vWZ5JLA7xbGWHX3wbsCp1bVqId2JHkt8IqqOjGt2PD/0orJ7ky7l7910AAnaC7GWE1dkvsAH6+qs7r3lwduU1XvHjay5SW5PvAi2riCd9OWyXg1rRn5xQOGtpoX0SY4fJAt60lOxSG0MVVfAF6e5DRa2YKnjvlcoU0iOZG27AdccJbaPBTwHdN59N+0z/U63c+sYsvagWM01evzQ7QCyd9IK0z9v8B/AXdPcpOqGvMC3reuqj/vXj8K+HpV3TutgO8HaQm61mHuE6skV52ZqvvbQYNZ3rNnn2q6Im3PpiUsY/U64DW0G8idgWNopSL+tKp+PWRgq7gRbczJ3WjLILwV+NhEZk1tAq5fVecmuQRtWv21lqqYPDJPodU7+xVtOvrhU5mpuw6jOX+q6pFDx3ARTPX6vEJVfaN7/QjaDMYndLMCjwbGnFjNfi/ekZaYU1U/mMg8pNGZ+67AJN+uqr2GjmMlC9NdF21btpr8GCyeJp+2HtbeUxpPkOQWtEGadwD+vqqOWOVXBjWV6f7L6ept7U8b/3MarTjosSv/1jSMafxmkodW1X8u16021u60xaZ0fc7ew5N8FvjXhVbkjHj1D4AkR9J6Gb4LHAlcp0uqdgBOqKrFrZ5axdy3WDGNpuTNSV5Cq2FVwBMYeHXuNbhEkv3Y8vn+HLj+QqmFsY+b6WYv7kdbZPR0YAqDNK+TLcsgBbhm935hssOol0Cqqm8leQ9tpYSHAddmS925UUry+Kp65RoOHVNB3IXVJi4zaBQXwQSvz+PTqpZ/lzYT8CNw3rCOsXss8HJaoecnzbSA3x54/2BRTZgtViPQzeJ5Ju3JLLSL8p/GPM21e8pZTtVIF75O8ijabKlL0KYWHzaVmS9JrrbS/qpaXENnFLr6cg+mtVR9h9Yd+L6RdxkD02sVnLqpXp9JdgKeSKtb9YbqFmPuWt2uWVVvHjI+bay5SKySvIKlxzgEeERVXXaDQ9JIJTmXtqTKwuK5i2dM3XPDg1qnrkttX1rsJy0uhDs23Wd+PPAe4Gwu+JmPtmtqyolV1+rzGGBvZnonqurPhoppNVO9PpPcsar+Z5l9L6yqv9/omNYqyb8Ap1TVaxdtfzKtCvtoYx+reekK3Hwh9w0qyUur6klJ3ssSieFYbyIrSXJH4O+q6o5Dx7KM2w4dwIWV5LK0pZs20brQAtwgydHAAVV19pDxreC5bDm/Lz1kIBfC9ZMs9bkudL+O+aHtPcCngY/Sps9PwVSvz1cleXJVndd11tW1egOti23M7k6rW7XYy2gPRCZW6zQXiVVVHbrcvq7fe6wWmofHHOOSktwOeC1byi28AHgT7Qvn+QOGtpqbAi+e0iD7GS+nLTHx4Nqylldo3civBB4+YGzLqqrnDB3DRfDlsQxKvxAuOcHWhqlen3cCPpTk4lX1rm7W7jtoLbT3GDa0VdXC/WTRxnOnsjzZ2Gw3dAAb4IFDB7Ccqjq6+99PLvUzdHyreDFwIHBF2g3kKODNVXXjMRcgBK4GHJ3klkMHciHcsqqeM3sTrOa5tHpWo5TkEkkekeSeaf4uyfuSvCzJLkPHN8fel+SuQwexTpO8PqvqVNoY2ecl+XPamntfr6qH1KKFmUfol0kusEh0t+1XA8QzeXMxxmolSb5TVXsOHcdSknyZFerfjHmW1xJT/79ZVdccMqa16iqBvwL4Kq0W12yiMtrZjElOrqprLbPvG1V1gZvjGCQ5DPgdbbbaFYATgPcCtwJuWFV3HzC8FSV5elW9YOg41iPJz2j3ldA+89/SPn8Yf/flJK/PmdUFdqO13P8PbS1VYLxxAyS5C+3z/ie2zEbfRKu99aSq+sBQsU3VXCRWaWvWLbkLOK6q9tjIeNZqZpbX47r/Xega/FPgl11LxCglOQX4m5lNL5p9P/JWK5LcBngnbaDsees1jnU2I0CSQ4FvAs+bLZiY5JnAtavqYYMFt4IkJ1TV9bq6OKdX1VVm9o29xs+zWf7hp6rqeRsZz7ZiatfnVGdJL0hyPeBv2TLW6kRaLa4vDxfVdM1LYvUttjyhLVY1/sWMP1tVt1xt25gk+Y8VdtdYZx4luRKtG/MawF8uTIuegm7w+iG06tTH0s75/YAvAY+ukS6EPdu6ObUip0messTmSwKPBq5YVaMejJ/kvrSWwQI+XeNe+mjS1+e86caJ3aOqxlSjbRLmIrGauiTHAo+vqs90728BvLpmKpurH11L20HA62qiJ3+SawLXpT1InFhV3xw4pBUl+SGtdlVoNYretrALeGBVXXmo2NYjyWVotYoOAA6jDbIebY2lJK+mFatcWOvtQcA3q+pxy//WsKZ6fXYJ7KyiLTl1bFX9bICQLpS0hd7vRKt4/ye0ZPz+w0Y1PXORWM30by8o4EdV9Z0h4lmvJDemTcu9XLfpp8CfjbxffvFyGQs3ks9U1bcGCGlNkuxaVWcssX1P2my7fx0grDVZWKqke33LqvrszL61VgjfcEkesdL+lWb1jkE31OCvaV30hwIvq6qfDBvV6pKcCFxvIUHppv9/uar2HTay5U31+lymBX9n4Pq0Uigf3+CQ1iXJHwEPoa3R+AXglsA1quqXgwY2UfOSWC3Vv70zcDFg/5rIemRdV0+q6qyhY1lNN/ZksZ1pTznPqaq3LbF/VLoZaQ+gPZ3tTlsc+G9W/q3hTLlLbUGSS9O6ike7qsCsJP8K3Bc4GHhVTWjx6CTvAp5cXUX+bkznQVW1/7CRrc3Urs+ldJ/5YVV106FjWU6S02kFWV8DvLuqfpbkW1V19YFDm6x5qWO1ZFG5JJtotX/+aGMjWpsss1jqQumQGnFF6qr6x6W2d0/3H2VLd8+odN0596E9nV0bOJz2ZDbKCQ6LZJnXS70flSR/QZtldKnu/c+BF1bVqwcNbHVPAX4DPAP4h5myPlMoEHpF4KQkX+je/yHwv0mOgHEWIJ749XkBVXVakh2HjmMV7wTuTesq/r+09Tyn3+IyoLlIrJZTVZu7J+SxmvxiqYtV1Y9HXlTuh7Sm7mfQui0ryX0GjmmtapnXS70fjSTPAG4B3Ka65XfS1g98WZKdq+qfBg1wBVU15Vp/zxo6gAthytfnBST5PVpiPlpV9cQkT6JVvd8f+FfgskkeCHxgSq20YzEXXYHLSXJl2olx46Fj2VakVWR/xlinF6etf/VgWlL7FuDtwP+MfeYoQJJfAifTWkuu2b2me3+NqrrUcr87pCRfA25QixZdTlu49riquvYwkW0buiEGs2sF/njAcFY01eszSy9LtjOtrtVDq+p/Nz6qC6drYbszLcm6U1VZxHed5iKxytKLMO9Me0p+YlW9d+OjWruuPtETF6bLJ7kCbcbRKEsWwLLFTXcGvkdb+PqkjY9q7boWk/1pN/F9gGfTxnB8fdDAVjBT92xJC2NpxibJ16rq95bZ99Wqus5Gx7QtSHIg8Dxa9exz2dJ9OeokBaZ3fSb540WbCjgT+EZV/XaAkHqR5I+q6lNDxzE185JYLZ51tHBSf3HM06EXJPlSLVqPbKltY7LEl3wBZ05lUPKsJH9AG9PxwJpI9fgpSfIx4AVV9bFF228HPHO5MZK6aJJ8A7h5Vf1o6Fguiilcn0luVlVHDR3HhdGVWHggbYLAh6rqhCR3B54O7DTm76GxmpfEaq+q+vbQcVxYSY6jjT/5Sfd+Z+CTVfUHw0a2PkkuRRsE+ZCqutvQ8awkyeVpT8LQ1vSawkzMA4CdF6acJ/kubXxegL+rqtcMGd9ykuwLvAf4DG3JjKINpL4lcK+qOnHA8OZWkg8B953ilPmpXZ+LZuz+b1WNdu3OxZK8EdiTNrbtpsBptLVHnzr2grJjNS+D199Nq0ZNkndW1f0Gjme9Xgx8Lsk7aF86DwQmsT5ZkosBd6U9Ud6ZNsPktYMGtYIu3oNpCeC3aEnJ1ZIcDvz5yJvt/5z2GS/4YVXt3lVI/ghtuvToVNWJaUtmPATYl/aZfwp47OJxV+rV02j3lc8zM4C6qv5quJBWNuHrc3bCziUGi+LC2QRcv6rO7e4lPwKuVVU/GDiuyZqXxGr2pB79+IHFqupNSTYDt6P9t9y3qr4ycFgrSnJHtlTnPZK2zuFNqupRgwa2umcAOwJ7LlRE7qZ4vwp4ZvczVttV1Zkz7/8boKp+3Q0EH60uxiNps74KOMmkaqv7d+DjtPX2zl3l2LGY6vW5XTc2druZ1+d9L415wgDw26o6F867Tr9uUnXRzEtX4LKFE6em6067D62w6Wi705KcC3waeGR1ldaTnDL2gbFJTqAlgL9ctP3SwFFVdb2lf3N4SU6uqmstsX074OSxfvbdrLTXAzemrXG4HXADWrfgAVV19oDhza0kn6uqWwwdx3pM9fpMcipbJggsNuoJAzOzjeH8M44XJjtcf6jYpmpeWqxukORs2omwU/caplHEb3LdaZ0b02bsfDRtfa+3AdsPG9KanLvUmJOq+nmSsT9lfCTJP1XVMxZtfy6tK3CsXg58hbYkybkAXa2zZwKvBB4+YGzz7MhuZuB7OX9X4JhbTyZ5fVbV3ms5Lsm+IxxT+PtDBzBv5qLFaqqW6E57O/CKtV6kY5HklrT/jvvRWiQOr6qDh41qaQsTBVj6yfLIqrrBxka0dl1r5utpA7+P6zbfANgMPHqshfySfKOq9lnvPl00SZZas3PsrSeTvT7XYso9KlMblD8kE6sBTbU7bTldl9QdaS0Tj+q2jeoJbcpN9gu6Gj8LC+l+paq+uWj/2D7zJbswu30mVhsoycVGPAB8Lq7PlYy9jM5Kphz7RpuXrsCpmmp32pK6bp4Pdz8L3kw3Y3MMJt5kD0C1ZWFOWeGQUX3mwGeTPAt4Xs08ySV5JjDJ2j9T0nW73pY21OAewJWHjWh583B9rmLKLRlTjn1DTXkdrMmrqi9V1d93Re+eA+wHXCzJB7uxEfNgzOsGruTNQwdwEYztM38C8AfAyUnemeQdSb5J68Z8/LChza8kN03yMlpdoiNorePzUuV+yten5pyJ1UhU1Wer6vG06rcvpRVoA84rsDhVU33KGVtysh6j+syr6uyqegBwJ+CNwJtoa5Ddf7bw48TP89FI8vyu6voLaKUW9gPOqKpDF4oQz4GpXp+j7YZdg6l+5hvOrsCRmUJ32jZiVMnJPOjGgn1zhUM8z/txIPA1WsHY93W1iebtfB7Vf0+3xNdPFx4UktyWVuT0NOCVC+Paqupmw0W5tCQfqao7reHQh231YOaELVbTMKknhSRXnXk75Se0yZiTz3xS5/mIXQV4PnBPWvfrm2llaHyQ3noOAy4FkOSGtOK936Z1d796wLjWYte1HFRVJ2ztQOaFF9o0jOrpbA2OAvaCcT6hLSfJVavqe93bqSUnk/zMF5naeT5KVfV/wAeBD3ZLlNwduCTw3SQfq6qHDBpgP8Z2fe40c+94KPCGqnpxN1P62AHjWovLJbnvcjur6l0bGcw8MLHS1jDVlocpJydT/cy1FXXLBr0DeEe3NMyyX6BjMOEutdnr73a0dRrp1t8b+7V5OVryvWSJC8DEap1MrEZq4q0nU215GPsNcCWT/Mwnfp6PWpKL04r27s107vWH0Zb0OmumS+2f2dKl9ugBY1vJx5McBnwfuAJtjUaS7AaMfU3M06rqz4YOYp5M5WLbFo269STJK1j6yzzA5Tc4nL6MOjmZ08981Of5xL0HOIu2JuNvVjl2LKbapfYk4EHAbsCtqup33fZ9gJ0Hi2ptfi/JLavqs7Mbk9wa+N7iAsRanYnVeI299WTzhdw3qIknJ5P8zFcx9vN8yvaoqjsPHcQ6TbJLrSt8+zZog9eTPBF4IPAtWvmcMfs88LMltv+KFvs9Njac6TOxGq9Rt55U1aHL7Uvyoo2MZZ0mm5xM+DNfyajP84n7XJI/qKovDx3IOkyySy3JtWmraOwPnElb9zVVddtBA1ubK1XV8Ys3VtXmJHtvfDjTZ2I1oIm3nqzkgcDfDB3EUuY0OYERf+ZzfJ6P3a2AR3aLMf+G9nlXVV1/2LBWNNUuta/SKtvfo6pOBkjy5GFDWrNLrLBvpw2LYo6YWA1rsq0nqxhtk/0qRpucrMGYP/N5Pc/H7i5DB7BeE+5Sux+txerIJB+i/TeM+Zqc9cUkj6mq181uTHIAbXye1snEakBTbj1JstzTY5jODWWxUcc91c98yuf5lFXVaQBJrsTKrRKjMdUutao6HDg8yaVo5SGeDFw5yWuAw6vqI4MGuLIn0WL/U7YkUpuAi9FmaGqdMrPYvEYkyberaq+h41hO171QLFP7pKquscEhrckqyclxVbXHRsazHlP9zFcy9vN8ypLcE3gxcFXgh8DVgJOqarRrMiY5l9aldsBMl9opEz23dwYeADyoqm43dDyr6WqGXa97e2JVfXzIeKbMxGqkknynqvYcOo55M4/JyZR5nm89SY6jzaz7aFXt131x7l9VBw4c2rKS3IfWYnULYKFL7fVVdfVBA5PWwa7AAU21awcgyeLFcgv4UVV9Z4h41mrKN+ipfuZTPs8n7ndVdWaS7ZJsV1VHJnnh0EGtZOJdahJgi9Wgptx6kuTIJTbvTOuX37+qRlnMb6rJCUz6M5/seT5lST5KS04OAq5I6w78w6q6xaCBrdPUutQkEyv1Kskm4CVV9UdDx7KUqSYnKxn7Z65hdK0+vwK2A/6Utibcf1XVmYMGJs05E6sBTbn1ZCVJjqmqxf9tozb15GTMn/m8nudT0C1qvE9VfTTJJYHtq2qpKtuSeuIYq2G9eIltOyeZcuvJlZlgNe2uyvClh47jwpjAZz535/kUJHkMcCCtRfaawO7Aa4HbDxmXNO9MrAa0XG2WrvXk5cBoW0+Wqaa9M202zxM3PqKLZgLJyWQ/8ymf5xP3OOAmtLXgqKpvdDWtJG1FJlYjNJHWk8UVs4tW0O+vq+qHA8SzJlNNTjqT/MyXM5HzfMp+U1W/XVi7OMkOjPzhQZoHJlYjNIXWE+DIqvr20EFcCFNOTqb6mS9pIuf5lH0yydOBnZLcEfhL4L0DxyTNPQevD2i11pOqGu1NcHawdJJ3VtX9ho5pLZLsNdXkZMKf+WTP8ylLsh1wAHAnWqmLD9OKbXrTl7YiW6yGNeXWk9maRFOqQ/RuYHLJSWeqn/mUz/PJqqpzgdd1P5I2iInVsKbctVPLvB67qSYnMN3PfMrn+eQkOX6l/VV1/Y2KRdoWmVgNa8qtJzdIcjYtUdmpe033vqrqssOFtqKpJicw3c98yuf5FJ1LO7ffQhtT9athw5G2LSZWw5ps60lVbT90DBfSVJOTKX/mkz3Pp6iqbpjkOsD+tOTqK93/fqSqzhk0OGkbsN3QAWzjptx6MklVtX1VXbaqLlNVO3SvF96PNqmaOM/zDVZVX62qZ3eTHd4LvIm2oLGkrcxZgQNK8n/AL+haT4BfLuxi5K0n0lp5nm+8JLsDDwbuA/wEOAw4vKp+Pmhg0jbAxEqS5kiSTwKXoSVT7wB+PLu/qn681O9J6oeJlSTNkSSnsqXLdfYGv9BC6Dg3aSsysZKkbVCSfavqxKHjkOaNg9cladv05qEDkOaRiZUkbZuy+iGS1svESpK2TY4DkbYCEytJkqSemFhJ0rbpt0MHIM0jZwVK0hxJcjXgp1V1Vvf+tsC9gdOAV1aVCZW0FdliJUnz5TDgUgBJbgj8N/Bt4AbAqweMS9omuAizJM2Xnarqe93rhwJvqKoXJ9kOOHbAuKRtgi1WkjRfZsso3A74GEBVnYslFqStzhYrSZovH09yGPB94ArAxwGS7Ab8esjApG2BiZUkzZcnAQ8CdgNuVVW/67bvA+w8WFTSNsJZgZI0p7rB6w8BHgh8C3hXVb1i2Kik+WaLlSTNkSTXBh4M7A+cCbyd9hB920EDk7YRtlhJ0hxJci7waeCAqjq523ZKVV1j2MikbYOzAiVpvtwP+AFwZJLXJbk9zgaUNowtVpI0h5JcilZxfX9a2YVDgcOr6iODBibNORMrSZpzSXYGHgA8qKpuN3Q80jwzsZIkSeqJY6wkSZJ6YmIlSZLUExMrSZKknphYSZIk9cTESpIkqSf/Hz7mtBsVh+qCAAAAAElFTkSuQmCC\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "Train.skew().plot(kind='bar', figsize=(10,6))" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "NT_EFC195\n", - "0 2769\n", - "1 269\n", - "dtype: int64" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# From above, attribute NT_EFC195 shows that its, skewed.\n", - "Train.groupby('NT_EFC195').size()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### From the check above, attribute NT_EFC195 has skewed data and this could alter final results of the model. The data could be transformed or the attributed drop(not used in building a classifier." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### 10. Spot checking classification algorithms since its a classification problem at hand.\n", - "#### This is done to know which algorithm is best suited for the problem at hand. Two linear machine learning algorithms(Logistic regression and Linear discriminant analysis) and four non-linear machine learning algorithm were used(k-nearest neighbors, naive bayes, support vector machines and classific regression tress. " - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "('LR', 0.8342865299822478)\n", - "('LDA', 0.8377162908048379)\n", - "('KNN', 0.8690586462107053)\n", - "('CART', 1.0)\n", - "('NB', 0.8407203694376205)\n", - "('SVM', 0.8187103751493263)\n", - "('ABC', 0.8848771929251248)\n" - ] - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "from matplotlib import pyplot\n", - "from sklearn.model_selection import KFold\n", - "from sklearn.model_selection import cross_val_score\n", - "from sklearn.linear_model import LogisticRegression\n", - "from sklearn.tree import DecisionTreeClassifier\n", - "from sklearn.neighbors import KNeighborsClassifier\n", - "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", - "from sklearn.naive_bayes import GaussianNB\n", - "from sklearn.svm import SVC\n", - "from sklearn.ensemble import AdaBoostClassifier\n", - "from sklearn.metrics import matthews_corrcoef\n", - "\n", - "#split the dataset \n", - "A = Train.values\n", - "# Separating A into output and input components\n", - "X = A[:, 0:11]\n", - "Y = A[:, 11]\n", - "# prepare models and add them to a list\n", - "models = []\n", - "models.append(('LR', LogisticRegression()))\n", - "models.append(('LDA', LinearDiscriminantAnalysis()))\n", - "models.append(('KNN', KNeighborsClassifier()))\n", - "models.append(('CART', DecisionTreeClassifier()))\n", - "models.append(('NB', GaussianNB()))\n", - "models.append(('SVM', SVC()))\n", - "models.append(('ABC', AdaBoostClassifier()))\n", - "\n", - "#print(models)\n", - "\n", - "# evaluate each model in turn\n", - "results = []\n", - "names = []\n", - "scoring = 'accuracy'\n", - "\n", - "for name, model in models:\n", - " kfold = KFold(n_splits=20, random_state=7)\n", - " cv_results = cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\n", - " results.append(cv_results)\n", - " names.append(name)\n", - " model.fit(X, Y)\n", - "\n", - " Prediction = model.predict(X)\n", - " msg = (name, matthews_corrcoef(Y, Prediction))\n", - " print(msg)\n", - "\n", - "# boxplot algorithm comparison\n", - "fig = pyplot.figure()\n", - "fig.suptitle('Algorithm Comparison')\n", - "ax = fig.add_subplot(111)\n", - "pyplot.boxplot(results)\n", - "ax.set_xticklabels(names)\n", - "pyplot.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### From these results, it would suggest that both DecisionTreeClassifier, KNeighborsClassifier and GaussianNB are worthy of further study on this problem." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### **11. Data Preparation.**\n", - "#### This is important because this finds a way to best expose the structure of the problem to machine learning algorithim intended to be used. Since the data has attributes of varying scales, its important to use one of the methods for data preparation like rescaling, standardization, normalization or binarization for better prediction. Here, rescaling is used to have all the attribute on the same scale." - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[0.457 0. 0.348 0.545 0.33 0.483 0. 0.005 0.508 0.415 0.182]\n", - " [0.435 0.116 0.322 0.489 0.276 0.458 1. 0.011 0.421 0.586 0.475]\n", - " [0.467 0.116 0.246 0.523 0.288 0.565 0. 0.011 0.442 0.273 0.666]\n", - " [0.457 0.089 0.275 0.399 0.403 0.647 0. 0.011 0.405 0.153 0.424]\n", - " [0.511 0.183 0.323 0.373 0.342 0.595 0. 0.011 0.5 0.196 0.536]]\n" - ] - } - ], - "source": [ - "from numpy import set_printoptions\n", - "from sklearn.preprocessing import MinMaxScaler\n", - "\n", - "A = Train.values\n", - "# Separating A into output and input components\n", - "X = A[:, 0:11]\n", - "Y = A[:, 11]\n", - "scaler = MinMaxScaler(feature_range= (0,1))\n", - "rescaledX = scaler.fit_transform(X)\n", - "\n", - "# Summary of the transformed data\n", - "set_printoptions(precision = 3) # This sets the number of floating point output after rescaling the data\n", - "print(rescaledX[0:5, :]) # This is used as check to confirm that the data has been rescaled" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Standardization\n", - "#### It is a useful technique to transform attributes with a Gaussian distribution and differing means and standard deviations to a standard Gaussian distribution with a mean of 0 and a standard deviation of 1" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[ 7.697e-01 -1.123e+00 -1.900e-01 1.376e-01 -6.067e-01 -7.206e-01\n", - " -3.117e-01 -1.331e+00 -2.257e-02 -3.610e-01 -9.251e-01]\n", - " [ 5.079e-01 -4.109e-01 -3.763e-01 -2.432e-01 -1.181e+00 -9.245e-01\n", - " 3.208e+00 -1.303e+00 -5.924e-01 9.021e-01 1.037e+00]\n", - " [ 9.006e-01 -4.109e-01 -9.163e-01 -8.651e-03 -1.054e+00 -4.632e-02\n", - " -3.117e-01 -1.304e+00 -4.590e-01 -1.409e+00 2.318e+00]\n", - " [ 7.697e-01 -5.741e-01 -7.115e-01 -8.701e-01 1.594e-01 6.274e-01\n", - " -3.117e-01 -1.302e+00 -7.015e-01 -2.300e+00 6.989e-01]\n", - " [ 1.424e+00 2.041e-03 -3.670e-01 -1.050e+00 -4.790e-01 2.003e-01\n", - " -3.117e-01 -1.302e+00 -7.713e-02 -1.977e+00 1.447e+00]]\n" - ] - } - ], - "source": [ - "from numpy import set_printoptions\n", - "from sklearn.preprocessing import StandardScaler\n", - "B= Train.values\n", - "#Separating the array into intput and output components\n", - "X = B[:, 0:11]\n", - "Y = B[:, 11]\n", - "scaler2 = StandardScaler()\n", - "standardizedX = scaler2.fit_transform(X)\n", - "# A portion of the transformed data\n", - "set_printoptions(precision = 3) # This sets the number of floating point output after rescaling the data\n", - "print(standardizedX[0:5,:]) # This is used as check to confirm that the data has been rescaled" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### **12. Feature selection**\n", - "#### Statistical tests can be used to select those features that have the strongest relationship with the output variable. Feature selection is done on non transformed data using select k best using he univariate statistic F was used since it can work best with data containg negative values as opposed to chi2 that doesnt take in negative values." - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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featuresscorespvalue
7AS_MeanAmphiMoment2813.8681780.000000e+00
1FULL_AcidicMolPerc1697.2495654.220004e-295
2FULL_AURR9801071572.2806771.887905e-277
3FULL_DAYM7802011350.3007436.997934e-245
0FULL_Charge1214.9028383.404241e-224
5FULL_OOBM850104785.1247987.441087e-154
8AS_DAYM780201717.3174084.911002e-142
10CT_RACS820104234.2741975.329249e-51
6NT_EFC195221.3908532.189203e-48
4FULL_GEOR030101220.9670652.669597e-48
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" - ], - "text/plain": [ - " features scores pvalue\n", - "7 AS_MeanAmphiMoment 2813.868178 0.000000e+00\n", - "1 FULL_AcidicMolPerc 1697.249565 4.220004e-295\n", - "2 FULL_AURR980107 1572.280677 1.887905e-277\n", - "3 FULL_DAYM780201 1350.300743 6.997934e-245\n", - "0 FULL_Charge 1214.902838 3.404241e-224\n", - "5 FULL_OOBM850104 785.124798 7.441087e-154\n", - "8 AS_DAYM780201 717.317408 4.911002e-142\n", - "10 CT_RACS820104 234.274197 5.329249e-51\n", - "6 NT_EFC195 221.390853 2.189203e-48\n", - "4 FULL_GEOR030101 220.967065 2.669597e-48" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from sklearn.feature_selection import SelectKBest, f_classif\n", - "from numpy import set_printoptions\n", - "# Separating A into output and input components\n", - "A = Train.values\n", - "X = A[:, 0:11]\n", - "Y = A[:, 11]\n", - "#Feature Extraction\n", - "bestfeat = SelectKBest(score_func=f_classif, k=10)\n", - "fit = bestfeat.fit(X,Y) #fitting f_classif test on predictors to get features that best predict\n", - "\n", - "set_printoptions(precision=3) # This sets the number of floating point output after rescaling the data\n", - "selected_features = fit.transform(X)\n", - "#Creating a dataframe to represent the order features selected starting from the best feature\n", - "scores = pd.DataFrame(fit.scores_)\n", - "pvalues = pd.DataFrame(fit.pvalues_)\n", - "columns = pd.DataFrame(Train.columns[0:11])\n", - "\n", - "selected_features_dataframe = pd.concat([columns,scores, pvalues,], axis=1)\n", - "selected_features_dataframe.columns = ['features', 'scores', 'pvalue']\n", - "selected_features_dataframe.nlargest(10, \"scores\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### SelectKBest using the f statistic, gives scores to each attribute and takes the specified number of attributes with the highest scores. Attributes AS_MeanAmphiMoment, FULL_AcidicMolPerc, FULL_AURR980107, FULL_DAYM780201, FULL_Charge, FULL_OOBM850104, AS_DAYM780201 and CT_RACS820104 were the selected features." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Feature selection using SelectKBest, Chi2 statistical test since there are no negative values in the attributes after rescaling with the minmax scaler." - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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featuresscorespvalue
7AS_MeanAmphiMoment244.2277284.708742e-55
6NT_EFC195188.1970267.868482e-43
1FULL_AcidicMolPerc157.6175133.751602e-36
2FULL_AURR98010754.2314481.782118e-13
3FULL_DAYM78020137.3117801.006747e-09
8AS_DAYM78020126.1562243.148806e-07
5FULL_OOBM85010416.2314335.605627e-05
0FULL_Charge15.2452499.441397e-05
10CT_RACS82010415.1467759.946804e-05
4FULL_GEOR0301014.7886912.864719e-02
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" - ], - "text/plain": [ - " features scores pvalue\n", - "7 AS_MeanAmphiMoment 244.227728 4.708742e-55\n", - "6 NT_EFC195 188.197026 7.868482e-43\n", - "1 FULL_AcidicMolPerc 157.617513 3.751602e-36\n", - "2 FULL_AURR980107 54.231448 1.782118e-13\n", - "3 FULL_DAYM780201 37.311780 1.006747e-09\n", - "8 AS_DAYM780201 26.156224 3.148806e-07\n", - "5 FULL_OOBM850104 16.231433 5.605627e-05\n", - "0 FULL_Charge 15.245249 9.441397e-05\n", - "10 CT_RACS820104 15.146775 9.946804e-05\n", - "4 FULL_GEOR030101 4.788691 2.864719e-02" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from sklearn.feature_selection import SelectKBest\n", - "from sklearn.feature_selection import chi2\n", - "\n", - "#Feature Extraction\n", - "test = SelectKBest(score_func=chi2, k=10)\n", - "fit = test.fit(rescaledX,Y) # fitting chi2 test on predictors to get features that best predict\n", - "\n", - "# Summary of scores \n", - "set_printoptions(precision=3) # This sets the number of floating point output after rescaling the data\n", - "#print(fit.scores_)\n", - "selected_features1 = fit.transform(rescaledX)\n", - "#Creating a dataframe to represent the order features selected starting from the best feature\n", - "scores = pd.DataFrame(fit.scores_)\n", - "pvalues = pd.DataFrame(fit.pvalues_)\n", - "columns = pd.DataFrame(Train.columns[0:11])\n", - "\n", - "selected_features1 = pd.concat([columns,scores, pvalues], axis=1)\n", - "selected_features1.columns = ['features', 'scores', 'pvalue']\n", - "selected_features1.nlargest(10, \"scores\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### From the dataframe above, AS_MeanAmphiMoment has the highest score of 244.227728 followed by NT_EFC195, then FULL_AcidicMolPerc and like that till the last attribute in dataframe, FULL_GEOR030101 that has lowwest score of 4.788691." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Feature selection using the recursive feature selection method with LogisticRegression - it works by recursively removing attributes and building a model on those attributes that remain. It uses the model accuracy to identify which attributes (and combination of attributes) contribute the most to predicting the target attribute" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Selected_FeaturesRFEFeature_Ranking
2FULL_AURR9801072
0FULL_Charge1
1FULL_AcidicMolPerc1
3FULL_DAYM7802011
4FULL_GEOR0301011
5FULL_OOBM8501041
6NT_EFC1951
7AS_MeanAmphiMoment1
8AS_DAYM7802011
9AS_FUKS0101121
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" - ], - "text/plain": [ - " Selected_FeaturesRFE Feature_Ranking\n", - "2 FULL_AURR980107 2\n", - "0 FULL_Charge 1\n", - "1 FULL_AcidicMolPerc 1\n", - "3 FULL_DAYM780201 1\n", - "4 FULL_GEOR030101 1\n", - "5 FULL_OOBM850104 1\n", - "6 NT_EFC195 1\n", - "7 AS_MeanAmphiMoment 1\n", - "8 AS_DAYM780201 1\n", - "9 AS_FUKS010112 1" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from sklearn.feature_selection import RFE\n", - "from sklearn.linear_model import LogisticRegression\n", - "model = LogisticRegression()\n", - "rfe= RFE(model,10)\n", - "fit = rfe.fit(standardizedX, Y) # fitting logistic regression on predictors to get features that best predict\n", - "selectedfeaturesRFE = standardizedX[:, fit.support_]\n", - "\n", - "#Creating a dataframe to represent the order features selected starting from the best feature\n", - "#Num_Features = pd.DataFrame(fit.n_features_)\n", - "Selected_FeaturesRFE = pd.DataFrame(fit.support_)\n", - "Feature_Ranking = pd.DataFrame(fit.ranking_)\n", - "columns = pd.DataFrame(Train.columns[0:11])\n", - "\n", - "selected_features2 = pd.concat([columns, Feature_Ranking], axis=1)\n", - "selected_features2.columns = ['Selected_FeaturesRFE', 'Feature_Ranking']\n", - "selected_features2.nlargest(10, \"Feature_Ranking\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### From the dataframe above, FULL_AURR980107 has the highest rank of 2 followed by FULL_Charge, then FULL_AcidicMolPerc and like that till the last attribute in dataframe, AS_FUKS010112." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### **13. Evaluating Machine learning Alogorithms** - the best way to evaluate the performance of an algorithm would be to make predictions for new data to which you already know the answers. Evaluation shoud be done on data that is not used to train the algorithm. The evaluation is an estimate that we can use to talk about how well we think the algorithm may actually do in practice.\n", - "#### **Split into Train and Test set**\n", - "#### It's the simplest method that we can use to evaluate the performance of a machine learning algorithm is to use dierent training and testing datasets. The train dataset is split it into two parts. The algorithm is trained on one part and predictions are made on the second part and evaluate the predictions against the expected results. The size of the split can depend on the size of your dataset, although it is common to use 67% of the data for training and the remaining 33% for testing. This algorithm evaluation technique is very fast. It is ideal for large datasets (millions of records) where there is strong evidence that both splits of the data are representative of the underlying problem. " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### **LogisticRegression** - Logistic regression is basically a supervised classification algorithm. Supervised learning is when a model learns from data that is already labeled. A supervised learning model takes in a set of input objects and output values. The model then trains on that data to learn how to map the inputs to the desired output so it can learn to make predictions on unseen data. In a classification problem, the target variable(or output), y, can take only discrete values for given set of features(or inputs), X. Logistic regression is a classification algorithm used to assign observations to a discrete set of classes. It is based on the concept of probability." - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MCC: 0.8283116428616907\n", - "Accuracy: 91.92422731804587\n", - "387\n", - "371\n" - ] - } - ], - "source": [ - "from sklearn.model_selection import train_test_split\n", - "from sklearn.metrics import matthews_corrcoef\n", - "from sklearn.linear_model import LogisticRegression\n", - "\n", - "A = Train.values\n", - "# Separating A into output and input components\n", - "X = A[:, 0:11]\n", - "Y = A[:, 11]\n", - "test_size = 0.33\n", - "seed = 1\n", - "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", - "my_model1 = LogisticRegression()\n", - "my_model1.fit(selected_features_train, Y_train)\n", - "result = my_model1.score(selected_features_test, Y_test)\n", - "\n", - "Prediction = my_model1.predict(selected_features_train)\n", - "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", - "print(\"Accuracy:\", (result*100.0))\n", - "\n", - "#Assigning the preditions of the model to variable AssignmentOutPut1\n", - "AssignmentOutPut1 = my_model1.predict(Test.values) #Converting AssignmentOutPut1 to a dataframe since its output is an array\n", - "AssignmentOutPut1 = pd.DataFrame(AssignmentOutPut1)\n", - "\n", - "AssignmentOutPut1.columns = ['Class'] # Naming the output column\n", - "AssignmentOutPut1.index.name = \"Index\" #Creating a column called index\n", - "AssignmentOutPut1['Class'] = AssignmentOutPut1['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", - "\n", - "#Printing the number of False and Trues\n", - "print(AssignmentOutPut1.groupby('Class').size()[0].sum())\n", - "print(AssignmentOutPut1.groupby('Class').size()[1].sum())\n", - "\n", - "AssignmentOutPut1.to_csv('AssignmentOutPut1.csv') # Writing AssignmentOutPut1 to a csv file" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### **KNeighborsClassifier** - k-Nearest-Neighbors (k-NN) is a supervised machine learning model. KNN models work by taking a data point and looking at the ‘k’ closest labeled data points. The data point is then assigned the label of the majority of the ‘k’ closest points. For example, if k = 5, and 3 of points are ‘green’ and 2 are ‘red’, then the data point in question would be labeled ‘green’, since ‘green’ is the majority " - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MCC: 0.8566012373350099\n", - "Accuracy: 90.62811565304088\n", - "397\n", - "361\n" - ] - } - ], - "source": [ - "from sklearn.model_selection import train_test_split\n", - "from sklearn.metrics import matthews_corrcoef\n", - "from sklearn.neighbors import KNeighborsClassifier\n", - "\n", - "A = Train.values\n", - "# Separating A into output and input components\n", - "X = A[:, 0:11]\n", - "Y = A[:, 11]\n", - "test_size = 0.33\n", - "seed = 2\n", - "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", - "my_model2 = KNeighborsClassifier()\n", - "my_model2.fit(selected_features_train, Y_train)\n", - "result = my_model2.score(selected_features_test, Y_test)\n", - "\n", - "Prediction = my_model2.predict(selected_features_train)\n", - "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", - "print(\"Accuracy:\", (result*100.0))\n", - "\n", - "#Assigning the preditions of the model to variable AssignmentOutPut2\n", - "AssignmentOutPut2 = my_model2.predict(Test.values) \n", - "#Converting AssignmentOutPut to a dataframe since its output is an array\n", - "AssignmentOutPut2 = pd.DataFrame(AssignmentOutPut2)# Converting AssignmentOutPut2 to a dataframe since its output is an array\n", - "AssignmentOutPut2.columns = ['Class'] # Naming the out put column\n", - "AssignmentOutPut2.index.name = \"Index\" #Creating a column called index\n", - "AssignmentOutPut2['Class'] = AssignmentOutPut2['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", - "\n", - "#Printing the number of False and Trues\n", - "print(AssignmentOutPut2.groupby('Class').size()[0].sum())\n", - "print(AssignmentOutPut2.groupby('Class').size()[1].sum())\n", - "\n", - "AssignmentOutPut2.to_csv('AssignmentOutPut2.csv') # Writing AssignmentOutPut2 to a csv file" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### **DecisionTreeClassifier** - its also a supervised learning algorithm that identifies ways to split a data set based on different conditions." - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MCC: 1.0\n", - "Accuracy: 89.63110667996011\n", - "388\n", - "370\n" - ] - } - ], - "source": [ - "from sklearn.model_selection import train_test_split\n", - "from sklearn.metrics import matthews_corrcoef\n", - "from sklearn.tree import DecisionTreeClassifier\n", - "\n", - "A = Train.values\n", - "# Separating A into output and input components\n", - "X = A[:, 0:11]\n", - "Y = A[:, 11]\n", - "test_size = 0.33\n", - "seed = 3\n", - "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", - "my_model3 = DecisionTreeClassifier()\n", - "my_model3.fit(selected_features_train, Y_train)\n", - "result = my_model3.score(selected_features_test, Y_test)\n", - "\n", - "Prediction = my_model3.predict(selected_features_train)\n", - "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", - "print(\"Accuracy:\", (result*100.0))\n", - "AssignmentOutPut3 = my_model3.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut\n", - "\n", - "AssignmentOutPut3 = pd.DataFrame(AssignmentOutPut3)# Converting AssignmentOutPut3 to a dataframe since its output is an array\n", - "AssignmentOutPut3.columns = ['Class'] # Naming the out put column\n", - "AssignmentOutPut3.index.name = \"Index\" #Creating a column called index\n", - "AssignmentOutPut3['Class'] = AssignmentOutPut3['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", - "\n", - "#Printing the number of False and Trues\n", - "print(AssignmentOutPut3.groupby('Class').size()[0].sum())\n", - "print(AssignmentOutPut3.groupby('Class').size()[1].sum())\n", - "\n", - "AssignmentOutPut1.to_csv('AssignmentOutPut3.csv') # Writing AssignmentOutPut3 to a csv file\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### **GaussianNB** - its a classification algorithm for binary (two-class) and multi-class classification problems. Naive Bayes calculates the probability of each class and the conditional probability of each class given each input value. These probabilities are estimated for new data and multiplied together, assuming that they are all independent" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MCC: 0.8417648773342619\n", - "Accuracy: 91.92422731804587\n", - "369\n", - "389\n" - ] - } - ], - "source": [ - "from sklearn.model_selection import train_test_split\n", - "from sklearn.metrics import matthews_corrcoef\n", - "from sklearn.naive_bayes import GaussianNB\n", - "\n", - "A = Train.values\n", - "# Separating A into output and input components\n", - "X = A[:, 0:11]\n", - "Y = A[:, 11]\n", - "test_size = 0.33\n", - "seed = 4\n", - "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", - "my_model4 = GaussianNB()\n", - "my_model4.fit(selected_features_train, Y_train)\n", - "result = my_model4.score(selected_features_test, Y_test)\n", - "\n", - "Prediction = my_model4.predict(selected_features_train)\n", - "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", - "print(\"Accuracy:\", (result*100.0))\n", - "\n", - "AssignmentOutPut4 = my_model4.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut4\n", - "\n", - "AssignmentOutPut4 = pd.DataFrame(AssignmentOutPut4)# Converting AssignmentOutPut4 to a dataframe since its output is an array\n", - "AssignmentOutPut4.columns = ['Class'] # Naming the out put column\n", - "AssignmentOutPut4.index.name = \"Index\" #Creating a column called index\n", - "AssignmentOutPut4['Class'] = AssignmentOutPut4['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", - "\n", - "AssignmentOutPut4.to_csv('AssignmentOutPut4.csv') # Writing AssignmentOutPut4 to a csv file\n", - "#Printing the number of False and Trues\n", - "print(AssignmentOutPut4.groupby('Class').size()[0].sum())\n", - "print(AssignmentOutPut4.groupby('Class').size()[1].sum())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### **Support Vector Machines** - its also a supervised machine learning algorithm capable of performing classification, regression and outlier detection. They draw a line that best separates two classes. Data instances closest to the line that best separates the classes are called support vectors. " - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MCC: 0.8399582732206575\n", - "Accuracy: 92.82153539381855\n", - "379\n", - "379\n" - ] - } - ], - "source": [ - "from sklearn.model_selection import train_test_split\n", - "from sklearn.metrics import matthews_corrcoef\n", - "from sklearn.svm import SVC\n", - "\n", - "A = Train.values\n", - "# Separating A into output and input components\n", - "X = A[:, 0:11]\n", - "Y = A[:, 11]\n", - "test_size = 0.33\n", - "seed = 5\n", - "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", - "my_model5 = SVC(kernel = 'linear')\n", - "my_model5.fit(selected_features_train, Y_train)\n", - "result = my_model5.score(selected_features_test, Y_test)\n", - "\n", - "Prediction = my_model5.predict(selected_features_train)\n", - "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", - "print(\"Accuracy:\", (result*100.0))\n", - "AssignmentOutPut5 = my_model5.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut5\n", - "\n", - "AssignmentOutPut5 = pd.DataFrame(AssignmentOutPut5)# Converting AssignmentOutPut5 to a dataframe since its output is an array\n", - "AssignmentOutPut5.columns = ['Class'] # Naming the out put column\n", - "AssignmentOutPut5.index.name = \"Index\" #Creating a column called index\n", - "AssignmentOutPut5['Class'] = AssignmentOutPut5['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", - "\n", - "AssignmentOutPut1.to_csv('AssignmentOutPut5.csv') # Writing AssignmentOutPut5 to a csv file\n", - "#Printing the number of False and Trues\n", - "print(AssignmentOutPut5.groupby('Class').size()[0].sum())\n", - "print(AssignmentOutPut5.groupby('Class').size()[1].sum())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### **LinearDiscriminantAnalysis** - it is a dimensionality reduction technique used for the supervised classification problems. It too assumes a Gaussian distribution for the numerical input variables.It is used to project the features in higher dimension space into a lower dimension space." - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MCC: 0.8376165100283083\n", - "Accuracy: 91.72482552342971\n", - "403\n", - "355\n" - ] - } - ], - "source": [ - "from sklearn.model_selection import train_test_split\n", - "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", - "from sklearn.metrics import matthews_corrcoef\n", - "\n", - "A = Train.values\n", - "# Separating A into output and input components\n", - "X = A[:, 0:11]\n", - "Y = A[:, 11]\n", - "test_size = 0.33\n", - "seed = 6\n", - "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", - "my_model6 = LinearDiscriminantAnalysis()\n", - "my_model6.fit(selected_features_train, Y_train)\n", - "result = my_model6.score(selected_features_test, Y_test)\n", - "\n", - "Prediction = my_model6.predict(selected_features_train)\n", - "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", - "print(\"Accuracy:\", (result*100.0))\n", - "\n", - "AssignmentOutPut6 = my_model6.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut\n", - "AssignmentOutPut6 = pd.DataFrame(AssignmentOutPut6)# Converting AssignmentOutPut6 to a dataframe since its output is an array\n", - "AssignmentOutPut6.columns = ['Class'] # Naming the out put column\n", - "AssignmentOutPut6.index.name = \"Index\" #Creating a column called index\n", - "AssignmentOutPut6['Class'] = AssignmentOutPut6['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", - "\n", - "AssignmentOutPut6.to_csv('AssignmentOutPut6.csv') # Writing AssignmentOutPut6 to a csv file\n", - "#Printing the number of False and Trues\n", - "print(AssignmentOutPut6.groupby('Class').size()[0].sum())\n", - "print(AssignmentOutPut6.groupby('Class').size()[1].sum())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### **Ada Boost** - it trains predictors sequentially, each trying to correct its predecessor. It works by weighting instances in the dataset by how easy or difficult they are to classify, allowing the algorithm to pay or less attention to them in the construction of subsequent models" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MCC: 0.8546905980754327\n", - "Confusion_matrix: [[475 30]\n", - " [ 43 455]]\n", - "385\n", - "373\n" - ] - } - ], - "source": [ - "from sklearn.ensemble import AdaBoostClassifier\n", - "from sklearn.tree import DecisionTreeClassifier\n", - "from sklearn.model_selection import train_test_split\n", - "from sklearn.metrics import matthews_corrcoef\n", - "from sklearn.metrics import confusion_matrix\n", - "\n", - "A = Train.values\n", - "# Separating A into output and input components\n", - "\n", - "test_size = 0.33\n", - "seed = 6\n", - "# Split data into training and test sets to evaluate the model’s performance.\n", - "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", - "# Construct and fit a model to the training set. max_depth=1 is used to tell the model that the forest to be composed of trees with a\n", - "# single decision node and two leaves. n_estimators is used to specify the total number of trees in the forest.\n", - "Model7 = AdaBoostClassifier(DecisionTreeClassifier(max_depth=1),n_estimators=200) \n", - "Model7.fit(selected_features_train, Y_train)\n", - "predictions = Model7.predict(selected_features_test)\n", - "print(\"MCC:\", (matthews_corrcoef(Y_test, predictions)))\n", - "print(\"Confusion_matrix:\", confusion_matrix(Y_test, predictions))\n", - "\n", - "AssignmentOutPut7 = Model7.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut7\n", - "AssignmentOutPut7 = pd.DataFrame(AssignmentOutPut7)# Converting AssignmentOutPut7 to a dataframe since its output is an array\n", - "AssignmentOutPut7.columns = ['Class'] # Naming the out put column\n", - "AssignmentOutPut7.index.name = \"Index\" #Creating a column called index\n", - "AssignmentOutPut7['Class'] = AssignmentOutPut7['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", - "\n", - "AssignmentOutPut7.to_csv('AssignmentOutPut7.csv') # Writing AssignmentOutPut7 to a csv file\n", - "#Printing the number of False and Trues\n", - "print(AssignmentOutPut7.groupby('Class').size()[0].sum())\n", - "print(AssignmentOutPut7.groupby('Class').size()[1].sum())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### **Principle component analysis** - PCA is a common way of speeding up a machine learning algorithm. Its mostly used when a machine learning algorithm is too slow because the input dimension is too high, then PCA is used to speed it up can be a reasonable choice. PCA can also be used for data visualization." - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# Using PCA for visualization of data.\n", - "from sklearn.decomposition import PCA\n", - "#A = Train.values\n", - "# Separating A into output and input components\n", - "features = ['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107', 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104']\n", - "x =Train.loc[:, features].values\n", - "y =Train.loc[:,['CLASS']].values\n", - "pca = PCA(n_components=2)\n", - "principalComponents = pca.fit_transform(x)\n", - "principalDf = pd.DataFrame(principalComponents, columns = ['principal_component1', 'principal_component2'])\n", - "FinalDf = pd.concat([principalDf, Train[['CLASS']]], axis = 1)\n", - "FinalDf\n", - "\n", - "#The plot\n", - "fig = plt.figure(figsize = (8,8))\n", - "ax = fig.add_subplot(1,1,1) \n", - "ax.set_xlabel('Principal_Component1', fontsize = 10)\n", - "ax.set_ylabel('Principal_Component2', fontsize = 10)\n", - "ax.set_title('2 component PCA', fontsize = 15)\n", - "plt.scatter(FinalDf.iloc[:, 0], FinalDf.iloc[:, 1], c = FinalDf.iloc[:, 2], cmap ='Spectral') \n", - "#classes = [\"1.0\", \"0.0\"]\n", - "#colors = ['r','g', 'b']\n", - "#for CLASS, color in (classes,colors):\n", - "# indicesToKeep = FinalDf['CLASS'] == CLASS\n", - "# ax.scatter(FinalDf.loc[indicesToKeep, 'principal_component1'], FinalDf.loc[indicesToKeep, 'principal_component2'], c =color )\n", - "ax.legend()\n", - "ax.grid()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### **Using principle component analysis for machine learning**" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MCC: 0.7507336393432698\n", - "Socre: 0.8753738783649053\n", - "506\n", - "497\n" - ] - } - ], - "source": [ - "from sklearn.model_selection import train_test_split\n", - "from sklearn.decomposition import PCA\n", - "A= Train.values\n", - "X = A[:, 0:11]\n", - "Y = A[:, 11]\n", - "#Make an instance of the Model\n", - "pca = PCA(.95)\n", - "#Splitting data\n", - "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", - "pca = PCA(n_components=2)\n", - "principalComponents = pca.fit_transform(selected_features_train)\n", - "fit_train = pca.fit(selected_features_train) #Fit PCA on training set\n", - "\n", - "#Apply the mapping (transform) to both the training set and the test set.\n", - "selected_features_trainF = pca.transform(selected_features_train)\n", - "selected_features_testF = pca.transform(selected_features_test)\n", - "\n", - "#Importing the model\n", - "from sklearn.linear_model import LogisticRegression\n", - "Model8 = LogisticRegression()\n", - "Model8.fit(selected_features_trainF, Y_train)\n", - "\n", - "#Predicting new data\n", - "Pred = Model8.predict(selected_features_testF)\n", - "print(\"MCC:\", (matthews_corrcoef(Y_test, Pred)))\n", - "print(\"Socre:\", Model8.score(selected_features_testF, Y_test))\n", - "\n", - "AssignmentOutPut8 = Model8.predict(selected_features_testF) #Assigning the preditions of the model to variable AssignmentOutPut8\n", - "AssignmentOutPut8 = pd.DataFrame(AssignmentOutPut8)# Converting AssignmentOutPut8 to a dataframe since its output is an array\n", - "AssignmentOutPut8.columns = ['Class'] # Naming the out put column\n", - "AssignmentOutPut8.index.name = \"Index\" #Creating a column called index\n", - "AssignmentOutPut8['Class'] = AssignmentOutPut8['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", - "\n", - "AssignmentOutPut8.to_csv('AssignmentOutPut8.csv') # Writing AssignmentOutPut8 to a csv file\n", - "#Printing the number of False and Trues\n", - "print(AssignmentOutPut8.groupby('Class').size()[0].sum())\n", - "print(AssignmentOutPut8.groupby('Class').size()[1].sum())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### The Naive bayes(GaussianNB) algorithm with none rescaled or transformed data gave the best prediction from all the algorithms used." - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.6" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/Assignment Colab/nsangi-olga-tendo.ipynb b/Assignment Colab/nsangi-olga-tendo.ipynb deleted file mode 100644 index 6a01977..0000000 --- a/Assignment Colab/nsangi-olga-tendo.ipynb +++ /dev/null @@ -1,2485 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# **ACE Class competition**\n", - "#### By Nsangi Olga Tendo\n", - "## Machine Learning Process:\n", - "#### 1. Have a peek of raw data\n", - "#### 2. Review of dimensions of thedataset.\n", - "#### 3. Review of attribues in the data set\n", - "#### 4. Review the data types of attributes in your data.\n", - "#### 5. Review of missing data(NAs)\n", - "#### 6. Summary of data using descriptive statistics.\n", - "#### 7. Understand the relationships in your data using correlations.\n", - "#### 8. Review the skew of the distributions of each attribute." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", - "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "/kaggle/input/ace-class-assignment/Test.csv\n", - "/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\n" - ] - } - ], - "source": [ - "# This Python 3 environment comes with many helpful analytics libraries installed\n", - "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", - "# For example, here's several helpful packages to load in \n", - "\n", - "import numpy as np # linear algebra\n", - "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", - "import matplotlib.pyplot as plt\n", - "import seaborn as sns\n", - "\n", - "\n", - "# Input data files are available in the \"../input/\" directory.\n", - "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", - "\n", - "import os\n", - "for dirname, _, filenames in os.walk('/kaggle/input'):\n", - " for filename in filenames:\n", - " print(os.path.join(dirname, filename))\n", - "# Any results you write to the current directory are saved as output.\n", - "import warnings\n", - "warnings.filterwarnings('ignore')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Naming the Training and test dataset using." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0", - "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a" - }, - "outputs": [], - "source": [ - "Train = pd.read_csv(\"../input/ace-class-assignment/AMP_TrainSet.csv\")\n", - "Test = pd.read_csv(\"../input/ace-class-assignment/Test.csv\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Confirming that the data has been read in and assigned to variables Train and Test" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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This helps in finding out which columns have data types like strings that may need to be converted to foating points or integers to represent categorical or ordinal values since most machine learning algorithms take in integers or floats for inputs. This can be done using df.dtype method or the df.info() method as shown in the two cells below, tho the df.info() is more informative as its also tells the total number of instances for each column." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(FULL_Charge float64\n", - " FULL_AcidicMolPerc float64\n", - " FULL_AURR980107 float64\n", - " FULL_DAYM780201 float64\n", - " FULL_GEOR030101 float64\n", - " FULL_OOBM850104 float64\n", - " NT_EFC195 int64\n", - " AS_MeanAmphiMoment float64\n", - " AS_DAYM780201 float64\n", - " AS_FUKS010112 float64\n", - " CT_RACS820104 float64\n", - " CLASS int64\n", - " dtype: object,\n", - " FULL_Charge float64\n", - " FULL_AcidicMolPerc float64\n", - " FULL_AURR980107 float64\n", - " FULL_DAYM780201 float64\n", - " FULL_GEOR030101 float64\n", - " FULL_OOBM850104 float64\n", - " NT_EFC195 int64\n", - " AS_MeanAmphiMoment float64\n", - " AS_DAYM780201 float64\n", - " AS_FUKS010112 float64\n", - " CT_RACS820104 float64\n", - " dtype: object)" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Train.dtypes, Test.dtypes" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "RangeIndex: 3038 entries, 0 to 3037\n", - "Data columns (total 12 columns):\n", - "FULL_Charge 3038 non-null float64\n", - "FULL_AcidicMolPerc 3038 non-null float64\n", - "FULL_AURR980107 3038 non-null float64\n", - "FULL_DAYM780201 3038 non-null float64\n", - "FULL_GEOR030101 3038 non-null float64\n", - "FULL_OOBM850104 3038 non-null float64\n", - "NT_EFC195 3038 non-null int64\n", - "AS_MeanAmphiMoment 3038 non-null float64\n", - "AS_DAYM780201 3038 non-null float64\n", - "AS_FUKS010112 3038 non-null float64\n", - "CT_RACS820104 3038 non-null float64\n", - "CLASS 3038 non-null int64\n", - "dtypes: float64(10), int64(2)\n", - "memory usage: 284.9 KB\n" - ] - } - ], - "source": [ - "Train.info()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Descriptive statistics summary of the data in each column.\n", - "#### This includes measures of central tendencies like teh mean, median and measures of spread like standard, variance, range and interquatile range. The smallest and largest values of each column are also returned. This helps in understanding the distribution of data in each column. This way you can also find out if you have negative values in any attribute. This also helps in understanding the scales at which each attribute is at." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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We can also observe that there are negative values in some attributes have a minimum values in negatives." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Since this is a classification problem, its important to check out the propotions of the values in the class to be predicted as its possible one class may have more values as compared to the others. Incases where one class is higher than another class we could employe methods likes smote to over sample the least represented class so as to have an un biased algorithm." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0, 0.5, 'Distirbution')" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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km4HDgT6SaoDLyK6i6gHMlATwSEScGxELJd0CPEM2hHVeRGxK6zkfuAfoCkyOiIXlitnMzJpWtsQREacUKb6+kfY/An5UpPxu4O5WDM3MzFrA3xw3M7NcnDjMzCwXJw4zM8vFicPMzHJx4jAzs1ycOMzMLBcnDjMzy8WJw8zMcnHiMDOzXJw4zMwsFycOMzPLxYnDzMxyceIwM7NcnDjMzCwXJw4zM8vFicPMzHJx4jAzs1ycOMzMLJeyJQ5JkyWtkfR0QdnukmZKWpz+7pbKJekaSUskLZA0smCZcan9YknjyhWvmZmVppw9jhuAo+uVXQL8LSKGAn9L8wDHAEPTYwLwa8gSDXAZcBBwIHBZXbIxM7PKKFviiIjZwLp6xWOAKWl6CjC2oHxqZB4BekkaABwFzIyIdRHxCjCTbZORmZm1obY+x9E/IlYBpL/9UvlAYHlBu5pU1lC5mZlVSHs5Oa4iZdFI+bYrkCZImiNpTm1tbasGZ2Zm7+tWSiNJfYGvANWFy0TEWTm3t1rSgIhYlYai1qTyGmBwQbtBwMpUfni98lnFVhwR1wLXAowaNapocjEzs5YrtcdxB7Ar8D/AXQWPvKYDdVdGjUvrrSs/I11ddTCwPg1l3QMcKWm3dFL8yFRmZmYVUlKPA9gxIi7Os2JJN5P1FvpIqiG7Oupy4BZJZwMvAiel5ncDxwJLgLeAMwEiYp2kHwCPp3bfj4j6J9zNzKwNlZo47pR0bETcXeqKI+KUBqpGF2kbwHkNrGcyMLnU7ZqZWXmVOlR1IVny2CDp9fR4rZyBmZlZ+1RSjyMiepY7EDMz6xhKHapC0ueBw9LsrIi4szwhmZlZe1bSUJWky8mGq55JjwtTmZmZdTKl9jiOBUZExGYASVOAJ3j/XlNmZtZJ5PnmeK+C6V1bOxAzM+sYSu1x/Bh4QtJ9ZLcBOQy4tGxRmZlZu1XqVVU3S5oFHECWOC6OiJfKGZiZmbVPjQ5VSfpo+jsSGEB276jlwJ6FP7ZkZmadR1M9jm+S/bDST4rUBfDZVo/IzMzatUYTR0RMSJPHRMSGwjpJVWWLyszM2q1Sr6p6qMQyMzPbzjXa45C0B9kv7n1A0v68/8NKuwA7ljk2MzNrh5o6x3EUMJ7sB5R+WlD+OvCdMsVkZmbtWFPnOKYAUySdGBF/bqOYzMysHSv1C4DDJe1bvzAivt/K8ZiZWTtXauJ4o2C6CjgeWNT64ZiZWXtX6jfHt/oeh6QryX4n3MzMOpk8NzkstCOwT2sGYmZmHUOpv8fxlKQF6bEQeA74WXM3KukbkhZKelrSzZKqJA2R9KikxZL+KGmH1LZHml+S6qubu10zM2u5Us9xHF8w/R6wOiLea84GJQ0ELgCGRcTbkm4BTib7zY+rImKapN8AZwO/Tn9fiYgPSToZ+E/gS83ZtpmZtVxJPY6IWAb0BsYA/wp8rIXb7Ub2pcJuZMNeq8jue3Vrqp8CjE3TY9I8qX60JGFmZhVR6lDV98jevHsDfYAbJP17czYYESuAK4EXyRLGemAu8GpBL6aG7BvrpL/L07Lvpfa9i8Q4QdIcSXNqa2ubE5qZmZWg1JPjpwAHRMRlEXEZcDBwWnM2KGk3sl7EEGBPYCfgmCJNo26RRureL4i4NiJGRcSovn37Nic0MzMrQamJ4wWy72/U6QH8vZnb/Bzwj4iojYiNwG3AIUCvNHQF2S1OVqbpGmAwQKrfFVjXzG2bmVkLNXWTw5+Tfbp/B1goaWaaPwJ4sJnbfBE4WNKOwNvAaGAOcB/wBWAaMA64I7WfnuYfTvX3RsQ2PQ4zM2sbTV1VNSf9nQvcXlA+q7kbjIhHJd0KzCO7QusJ4FrgLmCapB+msuvTItcDN0paQtbTOLm52zYzs5Zr8iaHkroCUyLiy6210XSe5LJ6xUuBA4u03QCc1FrbNjOzlmnyHEdEbAL61n0hz8zMOrdSvwD4AvC/kqYDb9YVRsRPG1zCzMy2S6UmjpXp0QXoWb5wzMysvSv17rj/t9yBmJlZx9DU5bhXR8RESX+l+JfuPl+2yMzMrF1qqsdxY/p7ZbkDMTOzjqGpy3HnpskREbHVbdQlXQjcX67AzMysfSr1liPjipSNb8U4zMysg2jqHMcpwKnAkHQpbp1dgLXlDMzMzNqnps5xPER26/M+QOHvjr8OLChXUGZm1n41dY5jGbBM0ueAtyNis6QPAx8FnmqLAM3MrH0p9RzHbKAq/ezr34AzgRvKFZSZmbVfpSYORcRbZD8b+/OIOAEYVr6wzMysvSo5cUj6JNmv/t2Vykq9XYmZmW1HSk0cE4FLgdsjYqGkfch+eMnMzDqZUu9VdT8FX/aLiKXABeUKyszM2i/fq8rMzHLxvarMzCyXku5VFRH3S+qbpmtbulFJvYDfAsPJejJnAc8BfwSqyX446osR8YokAT8DjgXeAsZHxLyWxmBmZs3T6MlxZSZJehl4FnheUq2k77Vwuz8D/jsiPgp8HFgEXAL8LSKGkn1X5JLU9hhgaHpMAH7dwm2bmVkLNHVV1UTgU8ABEdE7InYDDgI+JekbzdmgpF2Aw4DrASLi3Yh4FRgDTEnNpgBj0/QYYGpkHgF6SRrQnG2bmVnLNZU4zgBOiYh/1BWkK6q+nOqaYx+gFvidpCck/VbSTkD/iFiVtrEK6JfaDwSWFyxfk8rMzKwCmkoc3SPi5fqF6TxH92ZusxswEvh1ROwPvMn7w1LFqEjZNld4SZogaY6kObW1LT4NY2ZmDWgqcbzbzLrG1AA1EfFomr+VLJGsrhuCSn/XFLQfXLD8IGBl/ZVGxLURMSoiRvXt27eZoZmZWVOaShwfl/RakcfrwMeas8GIeAlYLukjqWg08Awwnfd/MGoccEeang6ckU7UHwysrxvSMjOzttfU5bhdy7TdrwM3SdoBWEp2t90uwC2SzgZeBE5Kbe8muxR3CdnluGeWKSYzMytBRW5UGBHzgVFFqkYXaRvAeWUPyszMSlLqTQ7NzMwAJw4zM8vJicPMzHJx4jAzs1ycOMzMLBcnDjMzy8WJw8zMcnHiMDOzXJw4zMwsFycOMzPLxYnDzMxyceIwM7NcnDjMzCwXJw4zM8vFicPMzHJx4jAzs1ycOMzMLBcnDjMzy6ViiUNSV0lPSLozzQ+R9KikxZL+mH6PHEk90vySVF9dqZjNzKyyPY4LgUUF8/8JXBURQ4FXgLNT+dnAKxHxIeCq1M7MzCqkIolD0iDgOOC3aV7AZ4FbU5MpwNg0PSbNk+pHp/ZmZlYBlepxXA18G9ic5nsDr0bEe2m+BhiYpgcCywFS/frU3szMKqDNE4ek44E1ETG3sLhI0yihrnC9EyTNkTSntra2FSI1M7NiKtHj+BTweUkvANPIhqiuBnpJ6pbaDAJWpukaYDBAqt8VWFd/pRFxbUSMiohRffv2Le8emJl1Ym2eOCLi0ogYFBHVwMnAvRFxGnAf8IXUbBxwR5qenuZJ9fdGxDY9DjMzaxvt6XscFwPflLSE7BzG9an8eqB3Kv8mcEmF4jMzM6Bb003KJyJmAbPS9FLgwCJtNgAntWlgZmbWoPbU4zAzsw7AicPMzHJx4jAzs1ycOMzMLBcnDjMzy8WJw8zMcnHiMDOzXJw4zMwsFycOMzPLxYnDzMxyceIwM7NcKnqvKrNK2bhxIzU1NWzYsKHSobSZqqoqBg0aRPfu3SsdinVwThzWKdXU1NCzZ0+qq6vpDL9EHBGsXbuWmpoahgwZUulwrIPzUJV1Shs2bKB3796dImkASKJ3796dqodl5ePEYZ1WZ0kadTrb/lr5OHGYmVkuThxmLfTSSy9x8skn88EPfpBhw4Zx7LHH8vzzzzN8+PBKh2ZWFj45btYCEcEJJ5zAuHHjmDZtGgDz589n9erVFY7MrHzavMchabCk+yQtkrRQ0oWpfHdJMyUtTn93S+WSdI2kJZIWSBrZ1jGbNeS+++6je/funHvuuVvKRowYweDBg7fMv/DCCxx66KGMHDmSkSNH8tBDDwGwatUqDjvsMEaMGMHw4cN54IEH2LRpE+PHj2f48OF87GMf46qrrmrzfTJrSiV6HO8BF0XEPEk9gbmSZgLjgb9FxOWSLgEuAS4GjgGGpsdBwK/TX7OKe/rpp/nEJz7RaJt+/foxc+ZMqqqqWLx4Maeccgpz5szhD3/4A0cddRTf/e532bRpE2+99Rbz589nxYoVPP300wC8+uqrbbEbZrm0eeKIiFXAqjT9uqRFwEBgDHB4ajYFmEWWOMYAUyMigEck9ZI0IK3HrN3buHEj559/PvPnz6dr1648//zzABxwwAGcddZZbNy4kbFjxzJixAj22Wcfli5dyte//nWOO+44jjzyyApHb7atip4cl1QN7A88CvSvSwbpb7/UbCCwvGCxmlRmVnH77rsvc+fObbTNVVddRf/+/XnyySeZM2cO7777LgCHHXYYs2fPZuDAgZx++ulMnTqV3XbbjSeffJLDDz+cX/7yl5xzzjltsRtmuVQscUjaGfgzMDEiXmusaZGyKLK+CZLmSJpTW1vbWmGaNeqzn/0s77zzDtddd92Wsscff5xly5ZtmV+/fj0DBgygS5cu3HjjjWzatAmAZcuW0a9fP77yla9w9tlnM2/ePF5++WU2b97MiSeeyA9+8APmzZvX5vtk1pSKXFUlqTtZ0rgpIm5LxavrhqAkDQDWpPIaYHDB4oOAlfXXGRHXAtcCjBo1apvEYlYOkrj99tuZOHEil19+OVVVVVRXV3P11VdvafO1r32NE088kT/96U985jOfYaeddgJg1qxZXHHFFXTv3p2dd96ZqVOnsmLFCs4880w2b94MwI9//OOK7JdZY9o8cSj7+ur1wKKI+GlB1XRgHHB5+ntHQfn5kqaRnRRf7/Mb1p7sueee3HLLLduU153gHjp0KAsWLNhSXpcMxo0bx7hx47ZZzr0Ma+8q0eP4FHA68JSk+ansO2QJ4xZJZwMvAieluruBY4ElwFvAmW0brpm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CLASS0.534602-0.598816-0.584111-0.554838-0.260470-0.4532870.2607020.693552-0.4371680.0334320.2676521.000000
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" - ], - "text/plain": [ - " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 \\\n", - "FULL_Charge 1.000000 -0.612996 -0.490977 \n", - "FULL_AcidicMolPerc -0.612996 1.000000 0.794796 \n", - "FULL_AURR980107 -0.490977 0.794796 1.000000 \n", - "FULL_DAYM780201 -0.434603 0.541481 0.548253 \n", - "FULL_GEOR030101 -0.058725 0.115201 0.346139 \n", - "FULL_OOBM850104 -0.283758 0.513344 0.462712 \n", - "NT_EFC195 0.088068 -0.143168 -0.169540 \n", - "AS_MeanAmphiMoment 0.355477 -0.431590 -0.426097 \n", - "AS_DAYM780201 -0.365374 0.449621 0.456260 \n", - "AS_FUKS010112 -0.090570 0.002334 0.032958 \n", - "CT_RACS820104 0.232929 -0.213543 -0.403599 \n", - "CLASS 0.534602 -0.598816 -0.584111 \n", - "\n", - " FULL_DAYM780201 FULL_GEOR030101 FULL_OOBM850104 \\\n", - "FULL_Charge -0.434603 -0.058725 -0.283758 \n", - "FULL_AcidicMolPerc 0.541481 0.115201 0.513344 \n", - "FULL_AURR980107 0.548253 0.346139 0.462712 \n", - "FULL_DAYM780201 1.000000 0.010118 0.334778 \n", - "FULL_GEOR030101 0.010118 1.000000 0.319157 \n", - "FULL_OOBM850104 0.334778 0.319157 1.000000 \n", - "NT_EFC195 -0.090058 -0.230417 -0.230561 \n", - "AS_MeanAmphiMoment -0.408793 -0.160269 -0.336297 \n", - "AS_DAYM780201 0.894191 -0.029085 0.275640 \n", - "AS_FUKS010112 0.055915 0.040480 -0.452769 \n", - "CT_RACS820104 -0.326792 -0.151935 0.155304 \n", - "CLASS -0.554838 -0.260470 -0.453287 \n", - "\n", - " NT_EFC195 AS_MeanAmphiMoment AS_DAYM780201 \\\n", - "FULL_Charge 0.088068 0.355477 -0.365374 \n", - "FULL_AcidicMolPerc -0.143168 -0.431590 0.449621 \n", - "FULL_AURR980107 -0.169540 -0.426097 0.456260 \n", - "FULL_DAYM780201 -0.090058 -0.408793 0.894191 \n", - "FULL_GEOR030101 -0.230417 -0.160269 -0.029085 \n", - "FULL_OOBM850104 -0.230561 -0.336297 0.275640 \n", - "NT_EFC195 1.000000 0.178683 -0.036844 \n", - "AS_MeanAmphiMoment 0.178683 1.000000 -0.322378 \n", - "AS_DAYM780201 -0.036844 -0.322378 1.000000 \n", - "AS_FUKS010112 0.145924 0.025580 0.045562 \n", - "CT_RACS820104 0.080898 0.171524 -0.256060 \n", - "CLASS 0.260702 0.693552 -0.437168 \n", - "\n", - " AS_FUKS010112 CT_RACS820104 CLASS \n", - "FULL_Charge -0.090570 0.232929 0.534602 \n", - "FULL_AcidicMolPerc 0.002334 -0.213543 -0.598816 \n", - "FULL_AURR980107 0.032958 -0.403599 -0.584111 \n", - "FULL_DAYM780201 0.055915 -0.326792 -0.554838 \n", - "FULL_GEOR030101 0.040480 -0.151935 -0.260470 \n", - "FULL_OOBM850104 -0.452769 0.155304 -0.453287 \n", - "NT_EFC195 0.145924 0.080898 0.260702 \n", - "AS_MeanAmphiMoment 0.025580 0.171524 0.693552 \n", - "AS_DAYM780201 0.045562 -0.256060 -0.437168 \n", - "AS_FUKS010112 1.000000 -0.445284 0.033432 \n", - "CT_RACS820104 -0.445284 1.000000 0.267652 \n", - "CLASS 0.033432 0.267652 1.000000 " - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Train.corr(method='pearson')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### From the summary above, AS_DAYM780201 and FULL_DAYM780201 are the strongest positively correlated with a correlation of 0.894191 while FULL_AcidicMolPerc and FULL_Charge are the strongest negatively correlated attributes. This correlation can further be observed by plotting a heat map using seaborn to show the correlation of attributes with each other as shown below" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure(figsize= (10,10))\n", - "sns.heatmap(Train.corr(method = 'pearson'), cmap='Purples', robust=True, square=True, annot= True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Using visualisation to understand the data at hand. Histograms, Density plots and Box and whisker plots are some of the plots used to understand the attribute distribution. Histograms were used. They're used to summarize discrete or continuous data by showing the number(frequency) of data points that fall within a specified range of values. Histograms graphically show center) of the data, spread (i.e., the scale) of the data, skewness of the data, presence of outliers and presence of multiple modes in the data" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "Train.hist(figsize=(10,10))\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### From the histograms above, we can observe that attributes AS_MeanAmphiMoment, AS_DAYM780201, AS_FUKS010112, FULL_DAYM780201, FULL_GEOR030101, FULL_AURR980107,FULL_CHARGE have a normal. We can also tell from these plots that attribute CT_RACS820104 and FULL_AcidicMolPerc are skewed to the right. We can also tell that attributes NT_EFC195 and CLASS are categorical attributes. This can also be observed using density plots as shown below." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Using Density plots. Density plots are used to observe the distribution of a variable in a dataset. The peaks of a Density Plot help display where values are concentrated over the interval. Density plots give a more precise location and also gives a continuous distribution view. " - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "Train.plot(kind='density', figsize=(10,10), subplots=True, layout=(4,3), sharex=False)\n", - "plt.show" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### From the above plots, FULL_Charge, FULL_AURR980107, FULL_DAYM780201, FULL_GEOR030101, CT_RACS820104, FULL_OOBM850104, AS_FUKS010112, AS_DAYM780201 show a normal distribution of variables. CLASS and NT_EFC195 are categorical data CLASS having equal number of instances while NT_EFC195 has a category that has almost all instances. \tFULL_AcidicMolPerc and AS_MeanAmphiMoment have more than one peak meaning that the data points are distribute at 2 peak for FULL_AcidicMolPerc and 3 peaks for AS_MeanAmphiMoment\t" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Checking for the skewness of the data. Skewness is deviation from a normal distribution. The data may be skewed to the left or to the right of the normal distribution curve (bell shaped). Since many machine learning algorithms assume normal distribution,this allows one to know what attributes need to be corrected of skewness to improve the accuracy of the model. Skewness can be observed with bar plots of .skew()." - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "Train.skew().plot(kind='bar', figsize=(10,6))" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "NT_EFC195\n", - "0 2769\n", - "1 269\n", - "dtype: int64" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# From above, attribute NT_EFC195 shows that its, skewed.\n", - "Train.groupby('NT_EFC195').size()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### From the check above, attribute NT_EFC195 has skewed data and this could alter final results of the model. The data could be transformed or the attributed drop(not used in building a classifier." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Spot checking classification algorithms since its a classification problem at hand.\n", - "#### This is done to know which algorithm is best suited for the problem at hand. Two linear machine learning algorithms(Logistic regression and Linear discriminant analysis) and four non-linear machine learning algorithm were used(k-nearest neighbors, naive bayes, support vector machines and classific regression tress. " - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "('LR', 0.8342865299822478)\n", - "('LDA', 0.8377162908048379)\n", - "('KNN', 0.8690586462107053)\n", - "('CART', 1.0)\n", - "('NB', 0.8407203694376205)\n", - "('SVM', 0.8187103751493263)\n", - "('ABC', 0.8848771929251248)\n" - ] - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "from matplotlib import pyplot\n", - "from sklearn.model_selection import KFold\n", - "from sklearn.model_selection import cross_val_score\n", - "from sklearn.linear_model import LogisticRegression\n", - "from sklearn.tree import DecisionTreeClassifier\n", - "from sklearn.neighbors import KNeighborsClassifier\n", - "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", - "from sklearn.naive_bayes import GaussianNB\n", - "from sklearn.svm import SVC\n", - "from sklearn.ensemble import AdaBoostClassifier\n", - "from sklearn.metrics import matthews_corrcoef\n", - "\n", - "#split the dataset \n", - "A = Train.values\n", - "# Separating A into output and input components\n", - "X = A[:, 0:11]\n", - "Y = A[:, 11]\n", - "# prepare models and add them to a list\n", - "models = []\n", - "models.append(('LR', LogisticRegression()))\n", - "models.append(('LDA', LinearDiscriminantAnalysis()))\n", - "models.append(('KNN', KNeighborsClassifier()))\n", - "models.append(('CART', DecisionTreeClassifier()))\n", - "models.append(('NB', GaussianNB()))\n", - "models.append(('SVM', SVC()))\n", - "models.append(('ABC', AdaBoostClassifier()))\n", - "\n", - "#print(models)\n", - "\n", - "# evaluate each model in turn\n", - "results = []\n", - "names = []\n", - "scoring = 'accuracy'\n", - "\n", - "for name, model in models:\n", - " kfold = KFold(n_splits=20, random_state=7)\n", - " cv_results = cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\n", - " results.append(cv_results)\n", - " names.append(name)\n", - " model.fit(X, Y)\n", - "\n", - " Prediction = model.predict(X)\n", - " msg = (name, matthews_corrcoef(Y, Prediction))\n", - " print(msg)\n", - "\n", - "# boxplot algorithm comparison\n", - "fig = pyplot.figure()\n", - "fig.suptitle('Algorithm Comparison')\n", - "ax = fig.add_subplot(111)\n", - "pyplot.boxplot(results)\n", - "ax.set_xticklabels(names)\n", - "pyplot.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### From these results, it would suggest that both DecisionTreeClassifier, KNeighborsClassifier and GaussianNB are worthy of further study on this problem." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### **Data Preparation.**\n", - "#### This is important because this finds a way to best expose the structure of the problem to machine learning algorithim intended to be used. Since the data has attributes of varying scales, its important to use one of the methods for data preparation like rescaling, standardization, normalization or binarization for better prediction. Here, rescaling is used to have all the attribute on the same scale." - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[0.457 0. 0.348 0.545 0.33 0.483 0. 0.005 0.508 0.415 0.182]\n", - " [0.435 0.116 0.322 0.489 0.276 0.458 1. 0.011 0.421 0.586 0.475]\n", - " [0.467 0.116 0.246 0.523 0.288 0.565 0. 0.011 0.442 0.273 0.666]\n", - " [0.457 0.089 0.275 0.399 0.403 0.647 0. 0.011 0.405 0.153 0.424]\n", - " [0.511 0.183 0.323 0.373 0.342 0.595 0. 0.011 0.5 0.196 0.536]]\n" - ] - } - ], - "source": [ - "from numpy import set_printoptions\n", - "from sklearn.preprocessing import MinMaxScaler\n", - "\n", - "A = Train.values\n", - "# Separating A into output and input components\n", - "X = A[:, 0:11]\n", - "Y = A[:, 11]\n", - "scaler = MinMaxScaler(feature_range= (0,1))\n", - "rescaledX = scaler.fit_transform(X)\n", - "\n", - "# Summary of the transformed data\n", - "set_printoptions(precision = 3) # This sets the number of floating point output after rescaling the data\n", - "print(rescaledX[0:5, :]) # This is used as check to confirm that the data has been rescaled" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Standardization\n", - "#### It is a useful technique to transform attributes with a Gaussian distribution and differing means and standard deviations to a standard Gaussian distribution with a mean of 0 and a standard deviation of 1" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[ 7.697e-01 -1.123e+00 -1.900e-01 1.376e-01 -6.067e-01 -7.206e-01\n", - " -3.117e-01 -1.331e+00 -2.257e-02 -3.610e-01 -9.251e-01]\n", - " [ 5.079e-01 -4.109e-01 -3.763e-01 -2.432e-01 -1.181e+00 -9.245e-01\n", - " 3.208e+00 -1.303e+00 -5.924e-01 9.021e-01 1.037e+00]\n", - " [ 9.006e-01 -4.109e-01 -9.163e-01 -8.651e-03 -1.054e+00 -4.632e-02\n", - " -3.117e-01 -1.304e+00 -4.590e-01 -1.409e+00 2.318e+00]\n", - " [ 7.697e-01 -5.741e-01 -7.115e-01 -8.701e-01 1.594e-01 6.274e-01\n", - " -3.117e-01 -1.302e+00 -7.015e-01 -2.300e+00 6.989e-01]\n", - " [ 1.424e+00 2.041e-03 -3.670e-01 -1.050e+00 -4.790e-01 2.003e-01\n", - " -3.117e-01 -1.302e+00 -7.713e-02 -1.977e+00 1.447e+00]]\n" - ] - } - ], - "source": [ - "from numpy import set_printoptions\n", - "from sklearn.preprocessing import StandardScaler\n", - "B= Train.values\n", - "#Separating the array into intput and output components\n", - "X = B[:, 0:11]\n", - "Y = B[:, 11]\n", - "scaler2 = StandardScaler()\n", - "standardizedX = scaler2.fit_transform(X)\n", - "# A portion of the transformed data\n", - "set_printoptions(precision = 3) # This sets the number of floating point output after rescaling the data\n", - "print(standardizedX[0:5,:]) # This is used as check to confirm that the data has been rescaled" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### **Feature selection**\n", - "#### Statistical tests can be used to select those features that have the strongest relationship with the output variable. Feature selection is done on non transformed data using select k best using he univariate statistic F was used since it can work best with data containg negative values as opposed to chi2 that doesnt take in negative values." - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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featuresscorespvalue
7AS_MeanAmphiMoment2813.8681780.000000e+00
1FULL_AcidicMolPerc1697.2495654.220004e-295
2FULL_AURR9801071572.2806771.887905e-277
3FULL_DAYM7802011350.3007436.997934e-245
0FULL_Charge1214.9028383.404241e-224
5FULL_OOBM850104785.1247987.441087e-154
8AS_DAYM780201717.3174084.911002e-142
10CT_RACS820104234.2741975.329249e-51
6NT_EFC195221.3908532.189203e-48
4FULL_GEOR030101220.9670652.669597e-48
\n", - "
" - ], - "text/plain": [ - " features scores pvalue\n", - "7 AS_MeanAmphiMoment 2813.868178 0.000000e+00\n", - "1 FULL_AcidicMolPerc 1697.249565 4.220004e-295\n", - "2 FULL_AURR980107 1572.280677 1.887905e-277\n", - "3 FULL_DAYM780201 1350.300743 6.997934e-245\n", - "0 FULL_Charge 1214.902838 3.404241e-224\n", - "5 FULL_OOBM850104 785.124798 7.441087e-154\n", - "8 AS_DAYM780201 717.317408 4.911002e-142\n", - "10 CT_RACS820104 234.274197 5.329249e-51\n", - "6 NT_EFC195 221.390853 2.189203e-48\n", - "4 FULL_GEOR030101 220.967065 2.669597e-48" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from sklearn.feature_selection import SelectKBest, f_classif\n", - "from numpy import set_printoptions\n", - "# Separating A into output and input components\n", - "A = Train.values\n", - "X = A[:, 0:11]\n", - "Y = A[:, 11]\n", - "#Feature Extraction\n", - "bestfeat = SelectKBest(score_func=f_classif, k=10)\n", - "fit = bestfeat.fit(X,Y) #fitting f_classif test on predictors to get features that best predict\n", - "\n", - "set_printoptions(precision=3) # This sets the number of floating point output after rescaling the data\n", - "selected_features = fit.transform(X)\n", - "#Creating a dataframe to represent the order features selected starting from the best feature\n", - "scores = pd.DataFrame(fit.scores_)\n", - "pvalues = pd.DataFrame(fit.pvalues_)\n", - "columns = pd.DataFrame(Train.columns[0:11])\n", - "\n", - "selected_features_dataframe = pd.concat([columns,scores, pvalues,], axis=1)\n", - "selected_features_dataframe.columns = ['features', 'scores', 'pvalue']\n", - "selected_features_dataframe.nlargest(10, \"scores\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### SelectKBest using the f statistic, gives scores to each attribute and takes the specified number of attributes with the highest scores. Attributes AS_MeanAmphiMoment, FULL_AcidicMolPerc, FULL_AURR980107, FULL_DAYM780201, FULL_Charge, FULL_OOBM850104, AS_DAYM780201 and CT_RACS820104 were the selected features." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Feature selection using SelectKBest, Chi2 statistical test since there are no negative values in the attributes after rescaling with the minmax scaler." - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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featuresscorespvalue
7AS_MeanAmphiMoment244.2277284.708742e-55
6NT_EFC195188.1970267.868482e-43
1FULL_AcidicMolPerc157.6175133.751602e-36
2FULL_AURR98010754.2314481.782118e-13
3FULL_DAYM78020137.3117801.006747e-09
8AS_DAYM78020126.1562243.148806e-07
5FULL_OOBM85010416.2314335.605627e-05
0FULL_Charge15.2452499.441397e-05
10CT_RACS82010415.1467759.946804e-05
4FULL_GEOR0301014.7886912.864719e-02
\n", - "
" - ], - "text/plain": [ - " features scores pvalue\n", - "7 AS_MeanAmphiMoment 244.227728 4.708742e-55\n", - "6 NT_EFC195 188.197026 7.868482e-43\n", - "1 FULL_AcidicMolPerc 157.617513 3.751602e-36\n", - "2 FULL_AURR980107 54.231448 1.782118e-13\n", - "3 FULL_DAYM780201 37.311780 1.006747e-09\n", - "8 AS_DAYM780201 26.156224 3.148806e-07\n", - "5 FULL_OOBM850104 16.231433 5.605627e-05\n", - "0 FULL_Charge 15.245249 9.441397e-05\n", - "10 CT_RACS820104 15.146775 9.946804e-05\n", - "4 FULL_GEOR030101 4.788691 2.864719e-02" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from sklearn.feature_selection import SelectKBest\n", - "from sklearn.feature_selection import chi2\n", - "\n", - "#Feature Extraction\n", - "test = SelectKBest(score_func=chi2, k=10)\n", - "fit = test.fit(rescaledX,Y) # fitting chi2 test on predictors to get features that best predict\n", - "\n", - "# Summary of scores \n", - "set_printoptions(precision=3) # This sets the number of floating point output after rescaling the data\n", - "#print(fit.scores_)\n", - "selected_features1 = fit.transform(rescaledX)\n", - "#Creating a dataframe to represent the order features selected starting from the best feature\n", - "scores = pd.DataFrame(fit.scores_)\n", - "pvalues = pd.DataFrame(fit.pvalues_)\n", - "columns = pd.DataFrame(Train.columns[0:11])\n", - "\n", - "selected_features1 = pd.concat([columns,scores, pvalues], axis=1)\n", - "selected_features1.columns = ['features', 'scores', 'pvalue']\n", - "selected_features1.nlargest(10, \"scores\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### From the dataframe above, AS_MeanAmphiMoment has the highest score of 244.227728 followed by NT_EFC195, then FULL_AcidicMolPerc and like that till the last attribute in dataframe, FULL_GEOR030101 that has lowwest score of 4.788691." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Feature selection using the recursive feature selection method with LogisticRegression - it works by recursively removing attributes and building a model on those attributes that remain. It uses the model accuracy to identify which attributes (and combination of attributes) contribute the most to predicting the target attribute" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Selected_FeaturesRFEFeature_Ranking
2FULL_AURR9801072
0FULL_Charge1
1FULL_AcidicMolPerc1
3FULL_DAYM7802011
4FULL_GEOR0301011
5FULL_OOBM8501041
6NT_EFC1951
7AS_MeanAmphiMoment1
8AS_DAYM7802011
9AS_FUKS0101121
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" - ], - "text/plain": [ - " Selected_FeaturesRFE Feature_Ranking\n", - "2 FULL_AURR980107 2\n", - "0 FULL_Charge 1\n", - "1 FULL_AcidicMolPerc 1\n", - "3 FULL_DAYM780201 1\n", - "4 FULL_GEOR030101 1\n", - "5 FULL_OOBM850104 1\n", - "6 NT_EFC195 1\n", - "7 AS_MeanAmphiMoment 1\n", - "8 AS_DAYM780201 1\n", - "9 AS_FUKS010112 1" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from sklearn.feature_selection import RFE\n", - "from sklearn.linear_model import LogisticRegression\n", - "model = LogisticRegression()\n", - "rfe= RFE(model,10)\n", - "fit = rfe.fit(standardizedX, Y) # fitting logistic regression on predictors to get features that best predict\n", - "selectedfeaturesRFE = standardizedX[:, fit.support_]\n", - "\n", - "#Creating a dataframe to represent the order features selected starting from the best feature\n", - "#Num_Features = pd.DataFrame(fit.n_features_)\n", - "Selected_FeaturesRFE = pd.DataFrame(fit.support_)\n", - "Feature_Ranking = pd.DataFrame(fit.ranking_)\n", - "columns = pd.DataFrame(Train.columns[0:11])\n", - "\n", - "selected_features2 = pd.concat([columns, Feature_Ranking], axis=1)\n", - "selected_features2.columns = ['Selected_FeaturesRFE', 'Feature_Ranking']\n", - "selected_features2.nlargest(10, \"Feature_Ranking\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### From the dataframe above, FULL_AURR980107 has the highest rank of 2 followed by FULL_Charge, then FULL_AcidicMolPerc and like that till the last attribute in dataframe, AS_FUKS010112." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### **Evaluating Machine learning Alogorithms** - the best way to evaluate the performance of an algorithm would be to make predictions for new data to which you already know the answers. Evaluation shoud be done on data that is not used to train the algorithm. The evaluation is an estimate that we can use to talk about how well we think the algorithm may actually do in practice.\n", - "#### **Split into Train and Test set**\n", - "#### It's the simplest method that we can use to evaluate the performance of a machine learning algorithm is to use dierent training and testing datasets. The train dataset is split it into two parts. The algorithm is trained on one part and predictions are made on the second part and evaluate the predictions against the expected results. The size of the split can depend on the size of your dataset, although it is common to use 67% of the data for training and the remaining 33% for testing. This algorithm evaluation technique is very fast. It is ideal for large datasets (millions of records) where there is strong evidence that both splits of the data are representative of the underlying problem. " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### **LogisticRegression** - Logistic regression is basically a supervised classification algorithm. Supervised learning is when a model learns from data that is already labeled. A supervised learning model takes in a set of input objects and output values. The model then trains on that data to learn how to map the inputs to the desired output so it can learn to make predictions on unseen data. In a classification problem, the target variable(or output), y, can take only discrete values for given set of features(or inputs), X. Logistic regression is a classification algorithm used to assign observations to a discrete set of classes. It is based on the concept of probability." - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MCC: 0.8283116428616907\n", - "Accuracy: 91.92422731804587\n", - "387\n", - "371\n" - ] - } - ], - "source": [ - "from sklearn.model_selection import train_test_split\n", - "from sklearn.metrics import matthews_corrcoef\n", - "from sklearn.linear_model import LogisticRegression\n", - "\n", - "A = Train.values\n", - "# Separating A into output and input components\n", - "X = A[:, 0:11]\n", - "Y = A[:, 11]\n", - "test_size = 0.33\n", - "seed = 1\n", - "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", - "my_model1 = LogisticRegression()\n", - "my_model1.fit(selected_features_train, Y_train)\n", - "result = my_model1.score(selected_features_test, Y_test)\n", - "\n", - "Prediction = my_model1.predict(selected_features_train)\n", - "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", - "print(\"Accuracy:\", (result*100.0))\n", - "\n", - "#Assigning the preditions of the model to variable AssignmentOutPut1\n", - "AssignmentOutPut1 = my_model1.predict(Test.values) #Converting AssignmentOutPut1 to a dataframe since its output is an array\n", - "AssignmentOutPut1 = pd.DataFrame(AssignmentOutPut1)\n", - "\n", - "AssignmentOutPut1.columns = ['Class'] # Naming the output column\n", - "AssignmentOutPut1.index.name = \"Index\" #Creating a column called index\n", - "AssignmentOutPut1['Class'] = AssignmentOutPut1['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", - "\n", - "#Printing the number of False and Trues\n", - "print(AssignmentOutPut1.groupby('Class').size()[0].sum())\n", - "print(AssignmentOutPut1.groupby('Class').size()[1].sum())\n", - "\n", - "AssignmentOutPut1.to_csv('AssignmentOutPut1.csv') # Writing AssignmentOutPut1 to a csv file" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### **KNeighborsClassifier** - k-Nearest-Neighbors (k-NN) is a supervised machine learning model. KNN models work by taking a data point and looking at the ‘k’ closest labeled data points. The data point is then assigned the label of the majority of the ‘k’ closest points. For example, if k = 5, and 3 of points are ‘green’ and 2 are ‘red’, then the data point in question would be labeled ‘green’, since ‘green’ is the majority " - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MCC: 0.8566012373350099\n", - "Accuracy: 90.62811565304088\n", - "397\n", - "361\n" - ] - } - ], - "source": [ - "from sklearn.model_selection import train_test_split\n", - "from sklearn.metrics import matthews_corrcoef\n", - "from sklearn.neighbors import KNeighborsClassifier\n", - "\n", - "A = Train.values\n", - "# Separating A into output and input components\n", - "X = A[:, 0:11]\n", - "Y = A[:, 11]\n", - "test_size = 0.33\n", - "seed = 2\n", - "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", - "my_model2 = KNeighborsClassifier()\n", - "my_model2.fit(selected_features_train, Y_train)\n", - "result = my_model2.score(selected_features_test, Y_test)\n", - "\n", - "Prediction = my_model2.predict(selected_features_train)\n", - "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", - "print(\"Accuracy:\", (result*100.0))\n", - "\n", - "#Assigning the preditions of the model to variable AssignmentOutPut2\n", - "AssignmentOutPut2 = my_model2.predict(Test.values) \n", - "#Converting AssignmentOutPut to a dataframe since its output is an array\n", - "AssignmentOutPut2 = pd.DataFrame(AssignmentOutPut2)# Converting AssignmentOutPut2 to a dataframe since its output is an array\n", - "AssignmentOutPut2.columns = ['Class'] # Naming the out put column\n", - "AssignmentOutPut2.index.name = \"Index\" #Creating a column called index\n", - "AssignmentOutPut2['Class'] = AssignmentOutPut2['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", - "\n", - "#Printing the number of False and Trues\n", - "print(AssignmentOutPut2.groupby('Class').size()[0].sum())\n", - "print(AssignmentOutPut2.groupby('Class').size()[1].sum())\n", - "\n", - "AssignmentOutPut2.to_csv('AssignmentOutPut2.csv') # Writing AssignmentOutPut2 to a csv file" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### **DecisionTreeClassifier** - its also a supervised learning algorithm that identifies ways to split a data set based on different conditions." - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MCC: 1.0\n", - "Accuracy: 89.43170488534396\n", - "390\n", - "368\n" - ] - } - ], - "source": [ - "from sklearn.model_selection import train_test_split\n", - "from sklearn.metrics import matthews_corrcoef\n", - "from sklearn.tree import DecisionTreeClassifier\n", - "\n", - "A = Train.values\n", - "# Separating A into output and input components\n", - "X = A[:, 0:11]\n", - "Y = A[:, 11]\n", - "test_size = 0.33\n", - "seed = 3\n", - "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", - "my_model3 = DecisionTreeClassifier()\n", - "my_model3.fit(selected_features_train, Y_train)\n", - "result = my_model3.score(selected_features_test, Y_test)\n", - "\n", - "Prediction = my_model3.predict(selected_features_train)\n", - "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", - "print(\"Accuracy:\", (result*100.0))\n", - "AssignmentOutPut3 = my_model3.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut\n", - "\n", - "AssignmentOutPut3 = pd.DataFrame(AssignmentOutPut3)# Converting AssignmentOutPut3 to a dataframe since its output is an array\n", - "AssignmentOutPut3.columns = ['Class'] # Naming the out put column\n", - "AssignmentOutPut3.index.name = \"Index\" #Creating a column called index\n", - "AssignmentOutPut3['Class'] = AssignmentOutPut3['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", - "\n", - "#Printing the number of False and Trues\n", - "print(AssignmentOutPut3.groupby('Class').size()[0].sum())\n", - "print(AssignmentOutPut3.groupby('Class').size()[1].sum())\n", - "\n", - "AssignmentOutPut1.to_csv('AssignmentOutPut3.csv') # Writing AssignmentOutPut3 to a csv file\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### **GaussianNB** - its a classification algorithm for binary (two-class) and multi-class classification problems. Naive Bayes calculates the probability of each class and the conditional probability of each class given each input value. These probabilities are estimated for new data and multiplied together, assuming that they are all independent" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MCC: 0.8417648773342619\n", - "Accuracy: 91.92422731804587\n", - "369\n", - "389\n" - ] - } - ], - "source": [ - "from sklearn.model_selection import train_test_split\n", - "from sklearn.metrics import matthews_corrcoef\n", - "from sklearn.naive_bayes import GaussianNB\n", - "\n", - "A = Train.values\n", - "# Separating A into output and input components\n", - "X = A[:, 0:11]\n", - "Y = A[:, 11]\n", - "test_size = 0.33\n", - "seed = 4\n", - "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", - "my_model4 = GaussianNB()\n", - "my_model4.fit(selected_features_train, Y_train)\n", - "result = my_model4.score(selected_features_test, Y_test)\n", - "\n", - "Prediction = my_model4.predict(selected_features_train)\n", - "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", - "print(\"Accuracy:\", (result*100.0))\n", - "\n", - "AssignmentOutPut4 = my_model4.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut4\n", - "\n", - "AssignmentOutPut4 = pd.DataFrame(AssignmentOutPut4)# Converting AssignmentOutPut4 to a dataframe since its output is an array\n", - "AssignmentOutPut4.columns = ['Class'] # Naming the out put column\n", - "AssignmentOutPut4.index.name = \"Index\" #Creating a column called index\n", - "AssignmentOutPut4['Class'] = AssignmentOutPut4['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", - "\n", - "AssignmentOutPut4.to_csv('AssignmentOutPut4.csv') # Writing AssignmentOutPut4 to a csv file\n", - "#Printing the number of False and Trues\n", - "print(AssignmentOutPut4.groupby('Class').size()[0].sum())\n", - "print(AssignmentOutPut4.groupby('Class').size()[1].sum())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### **Support Vector Machines** - its also a supervised machine learning algorithm capable of performing classification, regression and outlier detection. They draw a line that best separates two classes. Data instances closest to the line that best separates the classes are called support vectors. " - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MCC: 0.8399582732206575\n", - "Accuracy: 92.82153539381855\n", - "379\n", - "379\n" - ] - } - ], - "source": [ - "from sklearn.model_selection import train_test_split\n", - "from sklearn.metrics import matthews_corrcoef\n", - "from sklearn.svm import SVC\n", - "\n", - "A = Train.values\n", - "# Separating A into output and input components\n", - "X = A[:, 0:11]\n", - "Y = A[:, 11]\n", - "test_size = 0.33\n", - "seed = 5\n", - "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", - "my_model5 = SVC(kernel = 'linear')\n", - "my_model5.fit(selected_features_train, Y_train)\n", - "result = my_model5.score(selected_features_test, Y_test)\n", - "\n", - "Prediction = my_model5.predict(selected_features_train)\n", - "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", - "print(\"Accuracy:\", (result*100.0))\n", - "AssignmentOutPut5 = my_model5.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut5\n", - "\n", - "AssignmentOutPut5 = pd.DataFrame(AssignmentOutPut5)# Converting AssignmentOutPut5 to a dataframe since its output is an array\n", - "AssignmentOutPut5.columns = ['Class'] # Naming the out put column\n", - "AssignmentOutPut5.index.name = \"Index\" #Creating a column called index\n", - "AssignmentOutPut5['Class'] = AssignmentOutPut5['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", - "\n", - "AssignmentOutPut1.to_csv('AssignmentOutPut5.csv') # Writing AssignmentOutPut5 to a csv file\n", - "#Printing the number of False and Trues\n", - "print(AssignmentOutPut5.groupby('Class').size()[0].sum())\n", - "print(AssignmentOutPut5.groupby('Class').size()[1].sum())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### **LinearDiscriminantAnalysis** - it is a dimensionality reduction technique used for the supervised classification problems. It too assumes a Gaussian distribution for the numerical input variables.It is used to project the features in higher dimension space into a lower dimension space." - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MCC: 0.8376165100283083\n", - "Accuracy: 91.72482552342971\n", - "403\n", - "355\n" - ] - } - ], - "source": [ - "from sklearn.model_selection import train_test_split\n", - "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", - "from sklearn.metrics import matthews_corrcoef\n", - "\n", - "A = Train.values\n", - "# Separating A into output and input components\n", - "X = A[:, 0:11]\n", - "Y = A[:, 11]\n", - "test_size = 0.33\n", - "seed = 6\n", - "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", - "my_model6 = LinearDiscriminantAnalysis()\n", - "my_model6.fit(selected_features_train, Y_train)\n", - "result = my_model6.score(selected_features_test, Y_test)\n", - "\n", - "Prediction = my_model6.predict(selected_features_train)\n", - "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", - "print(\"Accuracy:\", (result*100.0))\n", - "\n", - "AssignmentOutPut6 = my_model6.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut\n", - "AssignmentOutPut6 = pd.DataFrame(AssignmentOutPut6)# Converting AssignmentOutPut6 to a dataframe since its output is an array\n", - "AssignmentOutPut6.columns = ['Class'] # Naming the out put column\n", - "AssignmentOutPut6.index.name = \"Index\" #Creating a column called index\n", - "AssignmentOutPut6['Class'] = AssignmentOutPut6['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", - "\n", - "AssignmentOutPut6.to_csv('AssignmentOutPut6.csv') # Writing AssignmentOutPut6 to a csv file\n", - "#Printing the number of False and Trues\n", - "print(AssignmentOutPut6.groupby('Class').size()[0].sum())\n", - "print(AssignmentOutPut6.groupby('Class').size()[1].sum())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### **Ada Boost** - it trains predictors sequentially, each trying to correct its predecessor. It works by weighting instances in the dataset by how easy or difficult they are to classify, allowing the algorithm to pay or less attention to them in the construction of subsequent models" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MCC: 0.8546905980754327\n", - "Confusion_matrix: [[475 30]\n", - " [ 43 455]]\n", - "385\n", - "373\n" - ] - } - ], - "source": [ - "from sklearn.ensemble import AdaBoostClassifier\n", - "from sklearn.tree import DecisionTreeClassifier\n", - "from sklearn.model_selection import train_test_split\n", - "from sklearn.metrics import matthews_corrcoef\n", - "from sklearn.metrics import confusion_matrix\n", - "\n", - "A = Train.values\n", - "# Separating A into output and input components\n", - "\n", - "test_size = 0.33\n", - "seed = 6\n", - "# Split data into training and test sets to evaluate the model’s performance.\n", - "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", - "# Construct and fit a model to the training set. max_depth=1 is used to tell the model that the forest to be composed of trees with a\n", - "# single decision node and two leaves. n_estimators is used to specify the total number of trees in the forest.\n", - "Model7 = AdaBoostClassifier(DecisionTreeClassifier(max_depth=1),n_estimators=200) \n", - "Model7.fit(selected_features_train, Y_train)\n", - "predictions = Model7.predict(selected_features_test)\n", - "print(\"MCC:\", (matthews_corrcoef(Y_test, predictions)))\n", - "print(\"Confusion_matrix:\", confusion_matrix(Y_test, predictions))\n", - "\n", - "AssignmentOutPut7 = Model7.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut7\n", - "AssignmentOutPut7 = pd.DataFrame(AssignmentOutPut7)# Converting AssignmentOutPut7 to a dataframe since its output is an array\n", - "AssignmentOutPut7.columns = ['Class'] # Naming the out put column\n", - "AssignmentOutPut7.index.name = \"Index\" #Creating a column called index\n", - "AssignmentOutPut7['Class'] = AssignmentOutPut7['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", - "\n", - "AssignmentOutPut7.to_csv('AssignmentOutPut7.csv') # Writing AssignmentOutPut7 to a csv file\n", - "#Printing the number of False and Trues\n", - "print(AssignmentOutPut7.groupby('Class').size()[0].sum())\n", - "print(AssignmentOutPut7.groupby('Class').size()[1].sum())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### **Principle component analysis** - PCA is a common way of speeding up a machine learning algorithm. Its mostly used when a machine learning algorithm is too slow because the input dimension is too high, then PCA is used to speed it up can be a reasonable choice. PCA can also be used for data visualization." - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# Using PCA for visualization of data.\n", - "from sklearn.decomposition import PCA\n", - "#A = Train.values\n", - "# Separating A into output and input components\n", - "features = ['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107', 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104']\n", - "x =Train.loc[:, features].values\n", - "y =Train.loc[:,['CLASS']].values\n", - "pca = PCA(n_components=2)\n", - "principalComponents = pca.fit_transform(x)\n", - "principalDf = pd.DataFrame(principalComponents, columns = ['principal_component1', 'principal_component2'])\n", - "FinalDf = pd.concat([principalDf, Train[['CLASS']]], axis = 1)\n", - "FinalDf\n", - "\n", - "#The plot\n", - "fig = plt.figure(figsize = (8,8))\n", - "ax = fig.add_subplot(1,1,1) \n", - "ax.set_xlabel('Principal_Component1', fontsize = 10)\n", - "ax.set_ylabel('Principal_Component2', fontsize = 10)\n", - "ax.set_title('2 component PCA', fontsize = 15)\n", - "plt.scatter(FinalDf.iloc[:, 0], FinalDf.iloc[:, 1], c = FinalDf.iloc[:, 2], cmap ='Spectral') \n", - "#classes = [\"1.0\", \"0.0\"]\n", - "#colors = ['r','g', 'b']\n", - "#for CLASS, color in (classes,colors):\n", - "# indicesToKeep = FinalDf['CLASS'] == CLASS\n", - "# ax.scatter(FinalDf.loc[indicesToKeep, 'principal_component1'], FinalDf.loc[indicesToKeep, 'principal_component2'], c =color )\n", - "ax.legend()\n", - "ax.grid()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### **Using principle component analysis for machine learning**" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MCC: 0.7507336393432698\n", - "Socre: 0.8753738783649053\n", - "506\n", - "497\n" - ] - } - ], - "source": [ - "from sklearn.model_selection import train_test_split\n", - "from sklearn.decomposition import PCA\n", - "A= Train.values\n", - "X = A[:, 0:11]\n", - "Y = A[:, 11]\n", - "#Make an instance of the Model\n", - "pca = PCA(.95)\n", - "#Splitting data\n", - "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, random_state = seed)\n", - "pca = PCA(n_components=2)\n", - "principalComponents = pca.fit_transform(selected_features_train)\n", - "fit_train = pca.fit(selected_features_train) #Fit PCA on training set\n", - "\n", - "#Apply the mapping (transform) to both the training set and the test set.\n", - "selected_features_trainF = pca.transform(selected_features_train)\n", - "selected_features_testF = pca.transform(selected_features_test)\n", - "\n", - "#Importing the model\n", - "from sklearn.linear_model import LogisticRegression\n", - "Model8 = LogisticRegression()\n", - "Model8.fit(selected_features_trainF, Y_train)\n", - "\n", - "#Predicting new data\n", - "Pred = Model8.predict(selected_features_testF)\n", - "print(\"MCC:\", (matthews_corrcoef(Y_test, Pred)))\n", - "print(\"Socre:\", Model8.score(selected_features_testF, Y_test))\n", - "\n", - "AssignmentOutPut8 = Model8.predict(selected_features_testF) #Assigning the preditions of the model to variable AssignmentOutPut8\n", - "AssignmentOutPut8 = pd.DataFrame(AssignmentOutPut8)# Converting AssignmentOutPut8 to a dataframe since its output is an array\n", - "AssignmentOutPut8.columns = ['Class'] # Naming the out put column\n", - "AssignmentOutPut8.index.name = \"Index\" #Creating a column called index\n", - "AssignmentOutPut8['Class'] = AssignmentOutPut8['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", - "\n", - "AssignmentOutPut8.to_csv('AssignmentOutPut8.csv') # Writing AssignmentOutPut8 to a csv file\n", - "#Printing the number of False and Trues\n", - "print(AssignmentOutPut8.groupby('Class').size()[0].sum())\n", - "print(AssignmentOutPut8.groupby('Class').size()[1].sum())" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.6" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} From 7be4c7baa11810f716fe17f1ce69057e3aa50368 Mon Sep 17 00:00:00 2001 From: Atwine Date: Fri, 13 Mar 2020 16:00:04 +0300 Subject: [PATCH 23/29] latest --- Assignment Colab/lwasampijja-baker.ipynb | 1440 ---------------------- 1 file changed, 1440 deletions(-) delete mode 100644 Assignment Colab/lwasampijja-baker.ipynb diff --git a/Assignment Colab/lwasampijja-baker.ipynb b/Assignment Colab/lwasampijja-baker.ipynb deleted file mode 100644 index df98d6b..0000000 --- a/Assignment Colab/lwasampijja-baker.ipynb +++ /dev/null @@ -1,1440 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**#STEP: 1 - IMPORTING LIBRARIES AND DATA**" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", - "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "/kaggle/input/ace-class-assignment/Test.csv\n", - "/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\n", - "/kaggle/input/merged-data/merged_data.csv\n" - ] - } - ], - "source": [ - "#import libraries\n", - "\n", - "import numpy as np # linear algebra\n", - "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", - "import matplotlib.pyplot as plt \n", - "import seaborn as sns\n", - "\n", - "#let's remove the annoying warnings from our cells.\n", - "import warnings\n", - "warnings.filterwarnings('ignore')\n", - "\n", - "\n", - "import os\n", - "for dirname, _, filenames in os.walk('/kaggle/input'):\n", - " for filename in filenames:\n", - " print(os.path.join(dirname, filename))" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "#Loading the training datasets \n", - "\n", - "df = pd.read_csv(\"../input/ace-class-assignment/AMP_TrainSet.csv\")\n", - "\n", - "#Loading the Testing datasets \n", - "\n", - "Test = pd.read_csv(\"../input/ace-class-assignment/Test.csv\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**#STEP: 2 -DATA VISUALISATION AND CLEANING**" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0", - "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a" - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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05.00.0000.95174.8420.975-3.66300.28273.4445.6611.0411
14.05.4050.93171.5950.957-4.01110.60068.2226.5371.4531
25.55.4050.87373.5950.961-2.51200.59369.4444.9341.7221
35.04.1670.89566.2500.999-1.36200.61467.2224.3161.3821
47.58.5370.93264.7200.979-2.09100.61672.9444.5401.5391
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" - ], - "text/plain": [ - " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n", - "0 5.0 0.000 0.951 74.842 \n", - "1 4.0 5.405 0.931 71.595 \n", - "2 5.5 5.405 0.873 73.595 \n", - "3 5.0 4.167 0.895 66.250 \n", - "4 7.5 8.537 0.932 64.720 \n", - "\n", - " FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n", - "0 0.975 -3.663 0 0.282 \n", - "1 0.957 -4.011 1 0.600 \n", - "2 0.961 -2.512 0 0.593 \n", - "3 0.999 -1.362 0 0.614 \n", - "4 0.979 -2.091 0 0.616 \n", - "\n", - " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 CLASS \n", - "0 73.444 5.661 1.041 1 \n", - "1 68.222 6.537 1.453 1 \n", - "2 69.444 4.934 1.722 1 \n", - "3 67.222 4.316 1.382 1 \n", - "4 72.944 4.540 1.539 1 " - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(3038, 12)" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#to check the dimensions we use the shape function from pandas\n", - "df.shape" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "FULL_Charge float64\n", - "FULL_AcidicMolPerc float64\n", - "FULL_AURR980107 float64\n", - "FULL_DAYM780201 float64\n", - "FULL_GEOR030101 float64\n", - "FULL_OOBM850104 float64\n", - "NT_EFC195 int64\n", - "AS_MeanAmphiMoment float64\n", - "AS_DAYM780201 float64\n", - "AS_FUKS010112 float64\n", - "CT_RACS820104 float64\n", - "CLASS int64\n", - "dtype: object" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#finding each data type for each attribute\n", - "df.dtypes" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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FULL_ChargeFULL_AcidicMolPercFULL_AURR980107FULL_DAYM780201FULL_GEOR030101FULL_OOBM850104NT_EFC195AS_MeanAmphiMomentAS_DAYM780201AS_FUKS010112CT_RACS820104CLASS
count3038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.0000003038.000000
mean2.0602378.5215200.97141073.6687600.994007-2.4329270.08854515.68323373.6508285.9113611.2352550.500000
std3.8199297.5866520.1074138.5274890.0313331.7072230.28413311.5756659.1660920.6936890.2100120.500082
min-16.0000000.0000000.68400042.7500000.866000-10.4320000.0000000.04100042.7780003.5330000.7850000.000000
25%0.0000002.5160000.89500068.2940000.974000-3.6060000.0000005.58750067.5560005.4592501.0820000.000000
50%2.0000007.1430000.96300074.0595000.994000-2.2965000.00000014.98850073.6970005.9255001.1840000.500000
75%4.00000013.1580001.04100079.3437501.011000-1.2832500.00000026.80775079.7780006.3820001.3510001.000000
max30.00000046.6670001.451000101.6820001.1960003.5760001.00000051.280000103.1670008.6620002.1920001.000000
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" - ], - "text/plain": [ - " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n", - "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", - "mean 2.060237 8.521520 0.971410 73.668760 \n", - "std 3.819929 7.586652 0.107413 8.527489 \n", - "min -16.000000 0.000000 0.684000 42.750000 \n", - "25% 0.000000 2.516000 0.895000 68.294000 \n", - "50% 2.000000 7.143000 0.963000 74.059500 \n", - "75% 4.000000 13.158000 1.041000 79.343750 \n", - "max 30.000000 46.667000 1.451000 101.682000 \n", - "\n", - " FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n", - "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", - "mean 0.994007 -2.432927 0.088545 15.683233 \n", - "std 0.031333 1.707223 0.284133 11.575665 \n", - "min 0.866000 -10.432000 0.000000 0.041000 \n", - "25% 0.974000 -3.606000 0.000000 5.587500 \n", - "50% 0.994000 -2.296500 0.000000 14.988500 \n", - "75% 1.011000 -1.283250 0.000000 26.807750 \n", - "max 1.196000 3.576000 1.000000 51.280000 \n", - "\n", - " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 CLASS \n", - "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", - "mean 73.650828 5.911361 1.235255 0.500000 \n", - "std 9.166092 0.693689 0.210012 0.500082 \n", - "min 42.778000 3.533000 0.785000 0.000000 \n", - "25% 67.556000 5.459250 1.082000 0.000000 \n", - "50% 73.697000 5.925500 1.184000 0.500000 \n", - "75% 79.778000 6.382000 1.351000 1.000000 \n", - "max 103.167000 8.662000 2.192000 1.000000 " - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#for this we use the describe function on the dataset\n", - "df.describe()" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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FULL_AcidicMolPerc-0.6129961.0000000.7947960.5414810.1152010.513344-0.143168-0.4315900.4496210.002334-0.213543-0.598816
FULL_AURR980107-0.4909770.7947961.0000000.5482530.3461390.462712-0.169540-0.4260970.4562600.032958-0.403599-0.584111
FULL_DAYM780201-0.4346030.5414810.5482531.0000000.0101180.334778-0.090058-0.4087930.8941910.055915-0.326792-0.554838
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FULL_OOBM850104-0.2837580.5133440.4627120.3347780.3191571.000000-0.230561-0.3362970.275640-0.4527690.155304-0.453287
NT_EFC1950.088068-0.143168-0.169540-0.090058-0.230417-0.2305611.0000000.178683-0.0368440.1459240.0808980.260702
AS_MeanAmphiMoment0.355477-0.431590-0.426097-0.408793-0.160269-0.3362970.1786831.000000-0.3223780.0255800.1715240.693552
AS_DAYM780201-0.3653740.4496210.4562600.894191-0.0290850.275640-0.036844-0.3223781.0000000.045562-0.256060-0.437168
AS_FUKS010112-0.0905700.0023340.0329580.0559150.040480-0.4527690.1459240.0255800.0455621.000000-0.4452840.033432
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CLASS0.534602-0.598816-0.584111-0.554838-0.260470-0.4532870.2607020.693552-0.4371680.0334320.2676521.000000
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" - ], - "text/plain": [ - " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 \\\n", - "FULL_Charge 1.000000 -0.612996 -0.490977 \n", - "FULL_AcidicMolPerc -0.612996 1.000000 0.794796 \n", - "FULL_AURR980107 -0.490977 0.794796 1.000000 \n", - "FULL_DAYM780201 -0.434603 0.541481 0.548253 \n", - "FULL_GEOR030101 -0.058725 0.115201 0.346139 \n", - "FULL_OOBM850104 -0.283758 0.513344 0.462712 \n", - "NT_EFC195 0.088068 -0.143168 -0.169540 \n", - "AS_MeanAmphiMoment 0.355477 -0.431590 -0.426097 \n", - "AS_DAYM780201 -0.365374 0.449621 0.456260 \n", - "AS_FUKS010112 -0.090570 0.002334 0.032958 \n", - "CT_RACS820104 0.232929 -0.213543 -0.403599 \n", - "CLASS 0.534602 -0.598816 -0.584111 \n", - "\n", - " FULL_DAYM780201 FULL_GEOR030101 FULL_OOBM850104 \\\n", - "FULL_Charge -0.434603 -0.058725 -0.283758 \n", - "FULL_AcidicMolPerc 0.541481 0.115201 0.513344 \n", - "FULL_AURR980107 0.548253 0.346139 0.462712 \n", - "FULL_DAYM780201 1.000000 0.010118 0.334778 \n", - "FULL_GEOR030101 0.010118 1.000000 0.319157 \n", - "FULL_OOBM850104 0.334778 0.319157 1.000000 \n", - "NT_EFC195 -0.090058 -0.230417 -0.230561 \n", - "AS_MeanAmphiMoment -0.408793 -0.160269 -0.336297 \n", - "AS_DAYM780201 0.894191 -0.029085 0.275640 \n", - "AS_FUKS010112 0.055915 0.040480 -0.452769 \n", - "CT_RACS820104 -0.326792 -0.151935 0.155304 \n", - "CLASS -0.554838 -0.260470 -0.453287 \n", - "\n", - " NT_EFC195 AS_MeanAmphiMoment AS_DAYM780201 \\\n", - "FULL_Charge 0.088068 0.355477 -0.365374 \n", - "FULL_AcidicMolPerc -0.143168 -0.431590 0.449621 \n", - "FULL_AURR980107 -0.169540 -0.426097 0.456260 \n", - "FULL_DAYM780201 -0.090058 -0.408793 0.894191 \n", - "FULL_GEOR030101 -0.230417 -0.160269 -0.029085 \n", - "FULL_OOBM850104 -0.230561 -0.336297 0.275640 \n", - "NT_EFC195 1.000000 0.178683 -0.036844 \n", - "AS_MeanAmphiMoment 0.178683 1.000000 -0.322378 \n", - "AS_DAYM780201 -0.036844 -0.322378 1.000000 \n", - "AS_FUKS010112 0.145924 0.025580 0.045562 \n", - "CT_RACS820104 0.080898 0.171524 -0.256060 \n", - "CLASS 0.260702 0.693552 -0.437168 \n", - "\n", - " AS_FUKS010112 CT_RACS820104 CLASS \n", - "FULL_Charge -0.090570 0.232929 0.534602 \n", - "FULL_AcidicMolPerc 0.002334 -0.213543 -0.598816 \n", - "FULL_AURR980107 0.032958 -0.403599 -0.584111 \n", - "FULL_DAYM780201 0.055915 -0.326792 -0.554838 \n", - "FULL_GEOR030101 0.040480 -0.151935 -0.260470 \n", - "FULL_OOBM850104 -0.452769 0.155304 -0.453287 \n", - "NT_EFC195 0.145924 0.080898 0.260702 \n", - "AS_MeanAmphiMoment 0.025580 0.171524 0.693552 \n", - "AS_DAYM780201 0.045562 -0.256060 -0.437168 \n", - "AS_FUKS010112 1.000000 -0.445284 0.033432 \n", - "CT_RACS820104 -0.445284 1.000000 0.267652 \n", - "CLASS 0.033432 0.267652 1.000000 " - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#Correlations or influence between the attributes\n", - "df.corr()" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "#Visualize the correlation \n", - "#NOTE: To see the numbers within the cell ==> sns.heatmap(df.corr(), annot=True)\n", - "plt.figure(figsize=(20,20)) #This is used to change the size of the figure/ heatmap\n", - "sns.heatmap(df.corr(), annot=True, fmt='.0%')" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "#Scatter Plot Matrix: Scatter plots are useful for spotting structured relationships between variables, \n", - "#like whether you could summarize the relationship between two variables with a line\n", - "#AKA “pairs plot” in which one variable in the same data row is matched with another variable's value\n", - "\n", - "plt.figure(figsize=(20,20))\n", - "sns.pairplot(df)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**#STEP: 3 -MODELLING**" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "#Split the data into independent 'X' and dependent 'Y' variables\n", - "X = df.iloc[:, 0:11].values #Notice I started from index 0 to 11, essentially removing the id column & CLASS cloumn at the end\n", - "Y = df['CLASS'].values #Get the target variable 'CLASS' located at index=12\n" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "# Split the dataset into 75% Training set and 25% Testing set\n", - "from sklearn.model_selection import train_test_split\n", - "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size = 0.25, random_state = 0)" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [], - "source": [ - "# I Scaleed the data to bring all features to the same level of magnitude\n", - "# This means the data will be within a specific range for example 0 -100 or 0 - 1\n", - "\n", - "#Feature Scaling\n", - "from sklearn.preprocessing import StandardScaler\n", - "sc = StandardScaler()\n", - "X_train = sc.fit_transform(X_train)\n", - "X_test = sc.transform(X_test)" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [], - "source": [ - "#Create a function within many Machine Learning Models to the Training Set\n", - "def modelsT(X_train,Y_train):\n", - " \n", - " #1. Logistic Regression Algorithm to the Training Set\n", - " from sklearn.linear_model import LogisticRegression\n", - " log = LogisticRegression(random_state = 0)\n", - " log.fit(X_train, Y_train)\n", - " \n", - " #2. Using KNeighborsClassifier Method of neighbors class to use Nearest Neighbor algorithm\n", - " from sklearn.neighbors import KNeighborsClassifier\n", - " knn = KNeighborsClassifier(n_neighbors = 5, metric = 'minkowski', p = 2)\n", - " knn.fit(X_train, Y_train)\n", - " \n", - "\n", - " #3. Using SVC method of svm class to use Support Vector Machine Algorithm\n", - " from sklearn.svm import SVC\n", - " svc_lin = SVC(kernel = 'linear', random_state = 0)\n", - " svc_lin.fit(X_train, Y_train)\n", - " \n", - "\n", - " #4. Using SVC method of svm class to use Kernel SVM Algorithm\n", - " from sklearn.svm import SVC\n", - " svc_rbf = SVC(kernel = 'rbf', random_state = 0)\n", - " svc_rbf.fit(X_train, Y_train)\n", - " \n", - " #5. Using GaussianNB method of naïve_bayes class to use Naïve Bayes Algorithm\n", - " from sklearn.naive_bayes import GaussianNB\n", - " gauss = GaussianNB()\n", - " gauss.fit(X_train, Y_train)\n", - "\n", - "\n", - " #6. Using DecisionTreeClassifier of tree class to use Decision Tree Algorithm\n", - " from sklearn.tree import DecisionTreeClassifier\n", - " tree = DecisionTreeClassifier(criterion = 'entropy', random_state = 0)\n", - " tree.fit(X_train, Y_train)\n", - "\n", - "\n", - " #7. Using RandomForestClassifier method of ensemble class\n", - " from sklearn.ensemble import RandomForestClassifier\n", - " forest = RandomForestClassifier(n_estimators = 10, criterion = 'entropy', random_state = 0)\n", - " forest.fit(X_train, Y_train)\n", - " \n", - " #8. Using Perceptron\n", - " from sklearn.linear_model import Perceptron\n", - " perceptron = Perceptron()\n", - " perceptron.fit(X_train, Y_train)\n", - " \n", - "\n", - " #9. Stochastic Gradient Descent\n", - " from sklearn.linear_model import SGDClassifier\n", - " sgd = SGDClassifier()\n", - " sgd.fit(X_train, Y_train)\n", - " \n", - " \n", - " #10. Linear Discriminant Analysis \n", - " from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", - " lda = LinearDiscriminantAnalysis(n_components=2)\n", - " lda.fit(X_train, Y_train)\n", - " \n", - " \n", - " #print model accuracy on the Training data.\n", - " \n", - " print('[1]Logistic Regression Training Accuracy:',log.score(X_train, Y_train)) \n", - " print('[2]K Nearest Neighbor Training Accuracy:',knn.score(X_train, Y_train))\n", - " print('[3]Support Vector Machine (Linear Classifier) Training Accuracy:', svc_lin.score(X_train, Y_train)) \n", - " print('[4]Support Vector Machine (RBF Classifier) Training Accuracy:', svc_rbf.score(X_train, Y_train)) \n", - " print('[5]Gaussian Naive Bayes Training Accuracy:', gauss.score(X_train, Y_train)) \n", - " print('[6]Decision Tree Classifier Training Accuracy:', tree.score(X_train, Y_train)) \n", - " print('[7]Random Forest Classifier Training Accuracy:', forest.score(X_train, Y_train)) \n", - " print('[8]Perceptron Training Accuracy:', perceptron.score(X_train, Y_train)) \n", - " print('[9]Stochastic Gradient Descent Training Accuracy:', sgd.score(X_train, Y_train)) \n", - " print('[10]Linear Discriminant Analysis Training Accuracy:', lda.score(X_train, Y_train)) \n", - " \n", - " return log, knn, svc_lin, svc_rbf, gauss, tree, forest, perceptron, sgd, lda" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[1]Logistic Regression Training Accuracy: 0.9187884108867428\n", - "[2]K Nearest Neighbor Training Accuracy: 0.9433713784021072\n", - "[3]Support Vector Machine (Linear Classifier) Training Accuracy: 0.9183494293239683\n", - "[4]Support Vector Machine (RBF Classifier) Training Accuracy: 0.9477611940298507\n", - "[5]Gaussian Naive Bayes Training Accuracy: 0.9192273924495171\n", - "[6]Decision Tree Classifier Training Accuracy: 1.0\n", - "[7]Random Forest Classifier Training Accuracy: 0.9947322212467077\n", - "[8]Perceptron Training Accuracy: 0.8762071992976295\n", - "[9]Stochastic Gradient Descent Training Accuracy: 0.9100087796312555\n", - "[10]Linear Discriminant Analysis Training Accuracy: 0.9135206321334504\n" - ] - } - ], - "source": [ - "#Printing out accuracy of each Model\n", - "modelT = modelsT(X_train,Y_train)" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Model 0\n", - " precision recall f1-score support\n", - "\n", - " 0 0.91 0.93 0.92 353\n", - " 1 0.94 0.92 0.93 407\n", - "\n", - " accuracy 0.93 760\n", - " macro avg 0.93 0.93 0.93 760\n", - "weighted avg 0.93 0.93 0.93 760\n", - "\n", - "0.9263157894736842\n", - "\n", - "Model 1\n", - " precision recall f1-score support\n", - "\n", - " 0 0.90 0.95 0.92 353\n", - " 1 0.95 0.91 0.93 407\n", - "\n", - " accuracy 0.93 760\n", - " macro avg 0.92 0.93 0.92 760\n", - "weighted avg 0.93 0.93 0.93 760\n", - "\n", - "0.925\n", - "\n", - "Model 2\n", - " precision recall f1-score support\n", - "\n", - " 0 0.90 0.95 0.92 353\n", - " 1 0.95 0.91 0.93 407\n", - "\n", - " accuracy 0.93 760\n", - " macro avg 0.92 0.93 0.92 760\n", - "weighted avg 0.93 0.93 0.93 760\n", - "\n", - "0.925\n", - "\n", - "Model 3\n", - " precision recall f1-score support\n", - "\n", - " 0 0.93 0.95 0.94 353\n", - " 1 0.95 0.93 0.94 407\n", - "\n", - " accuracy 0.94 760\n", - " macro avg 0.94 0.94 0.94 760\n", - "weighted avg 0.94 0.94 0.94 760\n", - "\n", - "0.9407894736842105\n", - "\n", - "Model 4\n", - " precision recall f1-score support\n", - "\n", - " 0 0.91 0.92 0.92 353\n", - " 1 0.93 0.92 0.93 407\n", - "\n", - " accuracy 0.92 760\n", - " macro avg 0.92 0.92 0.92 760\n", - "weighted avg 0.92 0.92 0.92 760\n", - "\n", - "0.9210526315789473\n", - "\n", - "Model 5\n", - " precision recall f1-score support\n", - "\n", - " 0 0.91 0.88 0.89 353\n", - " 1 0.90 0.92 0.91 407\n", - "\n", - " accuracy 0.90 760\n", - " macro avg 0.90 0.90 0.90 760\n", - "weighted avg 0.90 0.90 0.90 760\n", - "\n", - "0.9013157894736842\n", - "\n", - "Model 6\n", - " precision recall f1-score support\n", - "\n", - " 0 0.92 0.95 0.93 353\n", - " 1 0.96 0.92 0.94 407\n", - "\n", - " accuracy 0.94 760\n", - " macro avg 0.94 0.94 0.94 760\n", - "weighted avg 0.94 0.94 0.94 760\n", - "\n", - "0.9368421052631579\n", - "\n", - "Model 7\n", - " precision recall f1-score support\n", - "\n", - " 0 0.89 0.88 0.89 353\n", - " 1 0.90 0.91 0.90 407\n", - "\n", - " accuracy 0.89 760\n", - " macro avg 0.89 0.89 0.89 760\n", - "weighted avg 0.89 0.89 0.89 760\n", - "\n", - "0.8947368421052632\n", - "\n", - "Model 8\n", - " precision recall f1-score support\n", - "\n", - " 0 0.88 0.96 0.92 353\n", - " 1 0.96 0.89 0.92 407\n", - "\n", - " accuracy 0.92 760\n", - " macro avg 0.92 0.92 0.92 760\n", - "weighted avg 0.92 0.92 0.92 760\n", - "\n", - "0.9210526315789473\n", - "\n", - "Model 9\n", - " precision recall f1-score support\n", - "\n", - " 0 0.90 0.96 0.93 353\n", - " 1 0.96 0.90 0.93 407\n", - "\n", - " accuracy 0.93 760\n", - " macro avg 0.93 0.93 0.93 760\n", - "weighted avg 0.93 0.93 0.93 760\n", - "\n", - "0.9302631578947368\n", - "\n" - ] - } - ], - "source": [ - "#Showing the confusion matrix and accuracy for all of the models on the test data\n", - "#Classification accuracy is the ratio of correct predictions to total predictions made.\n", - "\n", - "from sklearn.metrics import classification_report\n", - "from sklearn.metrics import accuracy_score\n", - "\n", - "for i in range(len(modelT)):\n", - " print('Model ',i)\n", - " #Check precision, recall, f1-score\n", - " print( classification_report(Y_test, modelT[i].predict(X_test)) )\n", - " #Another way to get the models accuracy on the test data\n", - " print( accuracy_score(Y_test, modelT[i].predict(X_test)))\n", - " print()#Print a new line" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "('LR', 0.835359128018065, 0.2708521320979506)\n", - "('LDA', 0.8535044293903076, 0.2571395669719574)\n", - "('KNN', 0.8027933385443807, 0.2521136100771112)\n", - "('TREE', 0.7368681605002605, 0.2833452298920867)\n", - "('NB', 0.880815746048289, 0.11642272449162755)\n", - "('SVM', 0.8350280093798853, 0.25836507020625044)\n", - "('FOREST', 0.8087067917318048, 0.2909686308113511)\n", - "('PERC', 0.8350964043772798, 0.2645271720286034)\n", - "('SGD', 0.7037432690637486, 0.3108465910214562)\n", - "('RVM', 0.8350280093798853, 0.25836507020625044)\n" - ] - }, - { - "data": { - "image/png": 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\n", 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "#Compare Machine Learning Algorithms Consistently\n", - "# Compare Algorithms\n", - "\n", - "from sklearn.model_selection import KFold\n", - "from sklearn.model_selection import cross_val_score\n", - "from sklearn.linear_model import LogisticRegression\n", - "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", - "from sklearn.neighbors import KNeighborsClassifier\n", - "from sklearn.tree import DecisionTreeClassifier\n", - "from sklearn.naive_bayes import GaussianNB\n", - "from sklearn.svm import SVC\n", - "from sklearn.ensemble import RandomForestClassifier\n", - "from sklearn.linear_model import Perceptron\n", - "from sklearn.linear_model import SGDClassifier\n", - "\n", - "array = df.values\n", - "\n", - "#split the dataset \n", - "X = array[:,0:11]\n", - "Y = array[:,11]\n", - "\n", - "# prepare models and add them to a list\n", - "models = []\n", - "models.append(('LR', LogisticRegression()))\n", - "models.append(('LDA', LinearDiscriminantAnalysis()))\n", - "models.append(('KNN', KNeighborsClassifier()))\n", - "models.append(('TREE', DecisionTreeClassifier()))\n", - "models.append(('NB', GaussianNB()))\n", - "models.append(('SVM', SVC()))\n", - "models.append(('FOREST', RandomForestClassifier()))\n", - "models.append(('PERC', Perceptron()))\n", - "models.append(('SGD', SGDClassifier()))\n", - "models.append(('RVM', SVC()))\n", - "\n", - "\n", - "\n", - "# evaluate each model in turn\n", - "results = []\n", - "names = []\n", - "scoring = 'accuracy'\n", - "\n", - "for name, model in models:\n", - " kfold = KFold(n_splits=10, random_state=7)\n", - " cv_results = cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\n", - " results.append(cv_results)\n", - " names.append(name)\n", - " msg = (name, cv_results.mean(), cv_results.std())\n", - " print(msg)\n", - "\n", - "# boxplot algorithm comparison\n", - "fig = plt.figure()\n", - "fig.suptitle('Algorithm Comparison')\n", - "ax = fig.add_subplot(111)\n", - "plt.figure(figsize=(20,20))\n", - "plt.boxplot(results)\n", - "ax.set_xticklabels(names)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "> **##Exporting BEST Results to CSV**" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MCC: 0.8402064856722555\n", - "Accuracy: 90.0\n", - "370\n", - "388\n" - ] - } - ], - "source": [ - "from sklearn.metrics import matthews_corrcoef\n", - "\n", - "selected_features_train, selected_features_test, Y_train, Y_test = train_test_split(X, Y, test_size = 10, random_state = 10)\n", - "modelG = GaussianNB()\n", - "modelG.fit(selected_features_train, Y_train)\n", - "result = modelG.score(selected_features_test, Y_test)\n", - "\n", - "Prediction = modelG.predict(selected_features_train)\n", - "print(\"MCC:\", (matthews_corrcoef(Y_train, Prediction)))\n", - "print(\"Accuracy:\", (result*100.0))\n", - "\n", - "outputG = modelG.predict(Test.values) #Assigning the preditions of the model to variable AssignmentOutPut\n", - "\n", - "outputG = pd.DataFrame(outputG)\n", - "# Converting AssignmentOutPut to a dataframe since its output is an array\n", - "outputG.columns = ['Class'] # Naming the out\n", - "outputG.index.name = \"Index\" #Creating a column called index\n", - "outputG['Class'] = outputG['Class'].map({0.0:False, 1.0:True}) # Converting 0.0 to false and 1.0 to true\n", - "\n", - "outputG.to_csv('outputG.csv') # Writing AssignmentOutPut1 to a csv file\n", - "#Printing the number of False and Trues\n", - "print(outputG.groupby('Class').size()[0].sum())\n", - "print(outputG.groupby('Class').size()[1].sum())" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.6" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} From ee519ccee90728287304b78d8fb27c8b4fecafa8 Mon Sep 17 00:00:00 2001 From: Maria_Magdalene_Namaganda Date: Sat, 14 Mar 2020 20:45:29 +0300 Subject: [PATCH 24/29] Maria Final Submission --- Assignment Colab/MARIA MAGDALENE NAMAGANDA FINAL.ipynb | 1 - Assignment Colab/MARIA MAGDALENE NAMAGANDA FINAL_UPDATE.ipynb | 1 + Assignment Colab/MARIA MAGDALENE NAMAGANDA.ipynb | 1 - 3 files changed, 1 insertion(+), 2 deletions(-) delete mode 100644 Assignment Colab/MARIA MAGDALENE NAMAGANDA FINAL.ipynb create mode 100644 Assignment Colab/MARIA MAGDALENE NAMAGANDA FINAL_UPDATE.ipynb delete mode 100644 Assignment Colab/MARIA MAGDALENE NAMAGANDA.ipynb diff --git a/Assignment Colab/MARIA MAGDALENE NAMAGANDA FINAL.ipynb b/Assignment Colab/MARIA MAGDALENE NAMAGANDA FINAL.ipynb deleted file mode 100644 index 64c2fef..0000000 --- a/Assignment Colab/MARIA MAGDALENE NAMAGANDA FINAL.ipynb +++ /dev/null @@ -1 +0,0 @@ -{"cells":[{"metadata":{},"cell_type":"markdown","source":"# MARIA MAGDALENE NAMAGANDA\n# 2019/HD07/24853U\n# Ace_class Kaggle assignment_1"},{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n for filename in filenames:\n print(os.path.join(dirname, filename))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Importing some of the needed packages and libraries"},{"metadata":{"trusted":true},"cell_type":"code","source":"import pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib import pyplot\nimport seaborn as sns\n\nfrom sklearn.model_selection import KFold\nfrom pandas import read_csv\nfrom sklearn.metrics import confusion_matrix\nfrom sklearn.metrics import classification_report\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.model_selection import train_test_split\n\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis\nfrom sklearn.svm import SVC\nfrom sklearn.ensemble import AdaBoostClassifier\nfrom sklearn.ensemble import GradientBoostingClassifier\nfrom sklearn.ensemble import ExtraTreesClassifier\nfrom sklearn.ensemble import RandomForestClassifier\nfrom xgboost import XGBClassifier\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> *Now i need to get rid of some unnecessary warnings by ignoring them*"},{"metadata":{"trusted":true},"cell_type":"code","source":"#To avoid unnecessary warnings, I will ignore them in the code below\nimport warnings\nwarnings.filterwarnings('ignore')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Loading the datasets \n### There are two datasets given; \n1. AMP_TrainSet.csv and \n2. Test.csv "},{"metadata":{"_cell_guid":"","_uuid":"","trusted":true},"cell_type":"code","source":"#Loading the datasets, \n\nTrain = pd.read_csv(\"../input/amp-data-set/AMP_TrainSet.csv\")\nTest = pd.read_csv(\"../input/amp-data-set/Test.csv\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### For training the model, I will first use the training set which I will further split into the train and validation set. \n### Then I will test the model on the Test set provided to gauge its performance."},{"metadata":{},"cell_type":"markdown","source":"# Exploring my data\n## Exploring data helps one understand what kind of data is given. That is to say knowing how much data it is, the shape, type, dimensions, missing values, data summary, correlation of attributes among others as am going to do in the following steps."},{"metadata":{"trusted":true},"cell_type":"code","source":"#here, am trying to find the type of data\ntype(Train)\ntype(Test)\nTrain.dtypes, Test.dtypes","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# checking the dimensions of the data\n# this retuns the number of rows and columns in the data\n\nTrain.shape, Test.shape\n\n#this helps to know how big the data is in terms of rows and columns.\n#also from here I can tell which data is labeled","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Data description\n>For now, I will focus more on the train dataset because its what I will use to train the model "},{"metadata":{"trusted":true},"cell_type":"code","source":"#getting a description of the train dataset\n#description gives a summary of the data.\n\nTrain.describe()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#looking at the first 5 entries of my data\nTrain.head()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Class Distribution\n> From the Train dataset, i see there is an extra 'CLASS' column which will be my validation set.\n### I need to know how this class is distributed to guide me on what to do with it."},{"metadata":{"trusted":true},"cell_type":"code","source":"#to see the class distribution, I will plot a bar graph\nTrain.groupby('CLASS').size().plot(kind='bar')\npyplot.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> I would like to know how many instaces i have for each class"},{"metadata":{"trusted":true},"cell_type":"code","source":"#getting the number of instances in each class\nTrain.groupby('CLASS').size()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### There are 1519 intances for each class which is proof for even distribution.\n### From the above barplot and class instances, I can see that the classes are evenly distributed so no need to use smote."},{"metadata":{},"cell_type":"markdown","source":"# Data Visualisation\n### Data visualization is the technique to present the data in a pictorial or graphical format. It enables one to analyze data visually. The data in a graphical format allows identification of new trends and patterns easily.\n### Visualisation identifies the relationship between data points and variables."},{"metadata":{},"cell_type":"markdown","source":"## Density plots"},{"metadata":{},"cell_type":"markdown","source":"> I chose to use density plots because they are better at determing the distribution shape as they are not affected by the number of bins as is the case with Histograms."},{"metadata":{"trusted":true},"cell_type":"code","source":"#now plotting density subplots\n#setting the figsize to 12 so that my graphs are not congested\nTrain.plot(kind='density', subplots = True, layout=(3,4), sharex= False, sharey= False, figsize=(12,12))\nplt.show()\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> From the above density subpots, I can see that most of the data follows a Gaussian distribution given some of the characteristics such as bell shaped curves and graphs being symmetrical about the mean."},{"metadata":{},"cell_type":"markdown","source":"## Box and whisker plots\n> A box plot is a type of graph that displays a summary of a large amount of data in terms of the median, upper quartile, lower quartile, minimum and maximum data values.\n\n> It handles large data easily, gives a clear summary and displays outliers."},{"metadata":{"trusted":true},"cell_type":"code","source":"#plotting a box and whisker graph\n#setting the figsize to 10 so that the plots are not congested.\nTrain.plot(kind='box', subplots = True, layout=(3,4), sharex= False, sharey= False, figsize=(10,10))\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Looking at the correlation of the data"},{"metadata":{},"cell_type":"markdown","source":"> Correlation is the relationship between two variables. The commonly used method is Pearson's correlation coefficient. It assumes a normal distribution of the attributes involved.\n\n> -1 shows full negative correlation, \n\n> +1 shows full negative correlation and \n\n> 0 shows no correlation at all."},{"metadata":{"trusted":true},"cell_type":"code","source":"#first I will checkfor the pairwise correlation of the attributes.\nTrain.corr(method='pearson')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Then now am reviewing the inter-correlation of attributes using heatmap\n#graphical representation\nplt.figure(figsize=(6,6))\nsns.heatmap(Train.corr(method='pearson'))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Ill also check the correlation in regards to the 'CLASS' attribute\nTrain.corr(method='pearson')['CLASS']","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Skewnwess of the data\n> knowing data skewness allows one to perform data preparation and improve a model\n\n> If Skewness value lies above +1 or below -1 then the data is highly skewed. \n\n> If skewness value lies between +0.5 and -0.5 then the data ids moderately skewed.\n\n> If skewness is 0 then data is symmetrical"},{"metadata":{"trusted":true},"cell_type":"code","source":"#Checking out skewness of data\nTrain.skew().plot(kind='bar')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Comparing Machine Learning Algorithms\n> This helps to choose the best model for the problem at hand.\n\n> Using resampling methods like cross validation, gives an estimate for how accurate each model may be on unseen data.\n\n> It is important to ensure that each algorithm is evaluated in the same way on the same data to avoid bias."},{"metadata":{"trusted":true},"cell_type":"code","source":"#comparing different models to from which ill choose.\n\n\n# load dataset\n\narray = Train.values\n\n#split the dataset \nX = array[:,0:11] #X = Train.drop(columns=['CLASS'])\nY = array[:,11] #Y = Train['CLASS']\n\n# preparing models and adding them to a list\nmodels = []\nmodels.append(('LR', LogisticRegression()))\nmodels.append(('LDA', LinearDiscriminantAnalysis()))\nmodels.append(('KNN', KNeighborsClassifier()))\nmodels.append(('CART', DecisionTreeClassifier()))\nmodels.append(('NB', GaussianNB()))\nmodels.append(('SVM', SVC()))\nmodels.append(('AB', AdaBoostClassifier()))\nmodels.append(('GBC', GradientBoostingClassifier()))\nmodels.append(('EXT', ExtraTreesClassifier()))\nmodels.append(('RTC', RandomForestClassifier()))\n#models.append(('XGB', XGBClassifier)) \n#am commenting out XGB it does not seem to be a scikit-learn estimator as it does not implement a 'get_params' methods.\n\n# evaluating each model in turn\nresults = []\nnames = []\n\nfor name, model in models:\n kfold = KFold(n_splits=50, random_state=42)\n cv_results = cross_val_score(model, X, Y, cv=kfold, scoring='accuracy')\n results.append(cv_results)\n names.append(name)\n msg = (name, cv_results.mean(), cv_results.std())\n print(msg)\n\n# boxplot algorithm comparison\nfig = pyplot.figure()\nfig.suptitle('Algorithm Comparison')\nax = fig.add_subplot(111)\npyplot.boxplot(results)\nax.set_xticklabels(names)\npyplot.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> ## From the above algorithm comparison, I can see that Naive Bayes(NB), ExtraTreesClassifiers(EXT) and RandomForestClassifiers(RTC) are some of the best performing algorithms. \n> ## Am yet to find out the overall best valgorithm after prediction on the Test set"},{"metadata":{},"cell_type":"markdown","source":"# Feature selection \n## Using recursive feature elimination\n> Sometimes, you may asses a dataset and find out that you do not need to use all the given features. This can be because some of them are highly correlates or they are not in any way helpful in developing the model.\n* It is therefore important to get rid of some features where applicable.\n\n> For this data, I will use Recursive Feature Elimination(RFE)"},{"metadata":{"trusted":true},"cell_type":"code","source":"#feature selection using RFE\n#first i will start with choosing 4 features\nfrom sklearn.feature_selection import RFE\nfrom sklearn.linear_model import LogisticRegression\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = LogisticRegression()\nrfe = RFE(model, 4)\nfit = rfe.fit(X, Y)\nprint(\"Num Features: \", fit.n_features_)\nprint(\"Selected Features:\", fit.support_)\nprint(\"Feature Ranking: \", fit.ranking_)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Calling out the column names so I can know which features am going to drop from RFE\nTrain.columns","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Using Feature importance"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.ensemble import ExtraTreesClassifier\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = ExtraTreesClassifier()\nmodel.fit(X, Y)\nprint(model.feature_importances_)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## If am to use 4 features and drop the rest\n> I will assign the new dataset a variable 'New_Train4' after choosing the 4 features and dropping the rest."},{"metadata":{"trusted":true},"cell_type":"code","source":"# I will call the new Train data with selected features New_Train4.\nTrain\nNew_Train4 = Train.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#dropping the same features in the test dataset\nNew_Test4 = Test.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#viewing the selected features\nNew_Train4.columns","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now splitting data\n#array = New_Train.values\nX = New_Train4.values[:,0:4]\nY = New_Train4.values[:,4]\nfrom sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size=0.2, random_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# also train and test the model on Matthews correlation coefficient.\nfrom sklearn.metrics import matthews_corrcoef\n\nGS = GaussianNB()\nGS.fit(X_Train,Y_Train)\npred = GS.predict(X_Test)\n\nprint(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Using four features gives me a very low MCC and low overall score.\n## I'll therefore consider using 8 features and see what score I get."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.feature_selection import RFE\nfrom sklearn.linear_model import LogisticRegression\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = LogisticRegression()\nrfe = RFE(model, 8)\nfit = rfe.fit(X, Y)\nprint(\"Num Features: \", fit.n_features_)\nprint(\"Selected Features:\", fit.support_)\nprint(\"Feature Ranking: \", fit.ranking_)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# I will call the new Train data with selected features New_Train8.\nTrain\nNew_Train8 = Train.drop(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'AS_DAYM780201'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#dropping the same features in the test dataset\nNew_Test8 = Test.drop(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'AS_DAYM780201'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now splitting data\n#array = New_Train.values\n\n\nX = New_Train8.values[:,0:8]\nY = New_Train8.values[:,8]\nfrom sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size=0.2, random_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now creating a model and training it on 8 features\nmodel = LogisticRegression(solver='liblinear', C=0.05, multi_class='ovr', random_state=30)\nmodel.fit(X_Train, Y_Train)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2,\nrandom_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.metrics import matthews_corrcoef\n\nnv = GaussianNB()\nnv.fit(X_Train,Y_Train)\npred = nv.predict(X_Test)\n\nprint(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Standardising data\n> This is useful to transform attributes with a Gaussian distribution and it workd better with rescaled data(also known as normalistaion where attributes are scaled into a range between 0 and 1)"},{"metadata":{},"cell_type":"markdown","source":"# Below are some of the algorithms I will be using;"},{"metadata":{},"cell_type":"markdown","source":"# LINEAR ALGORITHMS\n1. Linear Regression\n2. Logistic Regression\n3. Linear Discriminant Analysis"},{"metadata":{},"cell_type":"markdown","source":"# Logistic Regression using 8 features"},{"metadata":{"trusted":true},"cell_type":"code","source":"# here am using a dataset 'New_Train8' with 8 selected features\narray = New_Train8.values\nX = array[:,0:8]\nY = array[:,8]\n\nkfold = KFold(n_splits=10, random_state=42) #spliiting my data into 10 folds and random_state of 42 for reproducibility\nmodel = LogisticRegression() #calling out the prediction algorithm\nresults = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\nprint(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n\nmodel.fit(X,Y)\noutput = model.predict(New_Test8.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_logistic = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_logistic.columns = ['CLASS'] #renaming the output column to 'CLASS'\nmaria_logistic.index.name = \"Index\" #naming the index column as 'Index'\nmaria_logistic['CLASS']=maria_logistic['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_logistic.to_csv(\"maria_logistic.csv\") #changing my output file as a 'csv' file\n\nprint(maria_logistic['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\nprint('False: ',maria_logistic.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_logistic.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Applying Linear Dicriminant Analysis (LDA) using all features "},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\nnum_folds = 10\nkfold = KFold(n_splits=10, random_state=42) #spliiting my data into 10 folds and random_state of 42 for reproducibility\nmodel = LinearDiscriminantAnalysis() #calling out the prediction algorithm\nresults = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\nprint(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n\nmodel.fit(X,Y)\noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_LDA = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_LDA.columns = ['CLASS'] #renaming the output column to 'CLASS'\nmaria_LDA.index.name = \"Index\" #naming the index column as 'Index'\nmaria_LDA['CLASS']=maria_LDA['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_LDA.to_csv(\"maria_LDA.csv\") #changing my output file as a 'csv' file\n\nprint(maria_LDA['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\nprint('False: ',maria_LDA.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_LDA.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# NON LINEAR ALGORITHMS\n1. Naive Bayes\n2. Support Vector Machines\n3. K-Nearest Neighbours\n4. Classification and Regression Trees\n5. Learning Vector Quantization"},{"metadata":{},"cell_type":"markdown","source":"# Using Naive Bayes and all the features"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\ntest_size = 0.35 \n\nkfold = KFold(n_splits=10) #spliiting my data into 10 folds \n\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size, random_state=42) #random_state of 42 for reproducibility\n\nmodel = GaussianNB() #calling out the prediction algorithm\nresults = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\nprint(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n\n\nmodel.fit(X,Y)\noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria2_bayes = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria2_bayes.columns = ['CLASS'] #renaming the output column to 'CLASS'\nmaria2_bayes.index.name = \"Index\" #naming the index column as 'Index'\nmaria2_bayes['CLASS']=maria2_bayes['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria2_bayes.to_csv(\"maria2_bayes.csv\") #changing my output file as a 'csv' file\n\n\nprint(maria2_bayes['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\nprint('False: ',maria2_bayes.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria2_bayes.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Support Vector Machines algorithm using all features"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\nkfold = KFold(n_splits=10) #spliiting my data into 10 folds\n\nmodel = SVC() #calling out the prediction algorithm\nscoring = 'acuracy'\nresults = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\nprint(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n\nmodel.fit(X, Y)\noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nmcc = matthews_corrcoef(model.predict(X), Y)\nprint('MCC: ',mcc)\n\nmaria_svc = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_svc.columns = ['CLASS'] #renaming the output column to 'CLASS'\nmaria_svc.index.name = 'Index' #naming the index column as 'Index'\nmaria_svc['CLASS'] = maria_svc['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\n\nmaria_svc.to_csv('maria_svc.csv') #changing my output file as a 'csv' file\n\nprint(maria_svc['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\nprint('False: ',maria_svc.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_svc.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Applying Classification and Regression Trees"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.tree import DecisionTreeClassifier\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\nkfold = KFold(n_splits=10, random_state=42) #spliiting my data into 10 folds and random_state of 42 for reproducibility\nmodel = DecisionTreeClassifier() #calling out the prediction algorithm\nresults = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\nprint(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n\n\nmodel.fit(X,Y)\noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_tree = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_tree.columns = ['CLASS'] #renaming the output column to 'CLASS'\nmaria_tree.index.name = \"Index\" #naming the index column as 'Index'\nmaria_tree['CLASS']=maria_tree['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_tree.to_csv(\"maria_tree.csv\") #changing my output file as a 'csv' file\n\n\nprint(maria_tree['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\nprint('False: ',maria_tree.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_tree.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# K-Nearest Neighbours"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\n\nkfold = KFold(n_splits=10, random_state=42) #spliiting my data into 10 folds and random_state of 42 for reproducibility\nmodel = KNeighborsClassifier() #calling out the prediction algorithm\nresults = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\nprint(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n\nmodel.fit(X,Y) \noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_knn = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_knn.columns = ['CLASS'] #renaming the output column to 'CLASS' \nmaria_knn.index.name = \"Index\" #naming the index column as 'Index'\nmaria_knn['CLASS']=maria_knn['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_knn.to_csv(\"maria_knn.csv\") #changing my output file as a 'csv' file\n\n\nprint(maria_knn['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\nprint('False: ',maria_knn.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_knn.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Esemble Algorithms\n1. Boosting and Adaboost\n2. Bagging and Random forest"},{"metadata":{},"cell_type":"markdown","source":"# Applying Adaboost "},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\n\nX = array[:,0:11]\nY = array[:,11]\n\nkfold = KFold(n_splits=10, random_state=42)\n\nmodel = AdaBoostClassifier(n_estimators=200, random_state=42) \nresults = cross_val_score(model, X, Y, cv=kfold)\n\nprint(results.mean())\n\n\ntest_set = Test.values\nmodel.fit(X, Y)\noutput = model.predict(test_set)\n\nmcc = matthews_corrcoef(model.predict(X), Y)\nprint('MCC: ',mcc)\n\nmaria_AB= pd.DataFrame(output)\nmaria_AB.columns = ['CLASS']\nmaria_AB.index.name = 'Index'\nmaria_AB['CLASS'] = maria_AB['CLASS'].map({0.0:False, 1.0:True})\n\nmaria_AB.to_csv('maria_AB.csv')\n\nprint(maria_AB['CLASS'].unique())\nprint('False: ',maria_AB.groupby('CLASS').size()[0].sum())\nprint('True: ',maria_AB.groupby('CLASS').size()[1].sum())","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Applying Gradient Boosting Classifier"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\n\nX = array[:,0:11]\nY = array[:,11]\n\n#num_trees = 200\n#seed =42\n\nkfold = KFold(n_splits=10, random_state=42)\nmodel = GradientBoostingClassifier(n_estimators=200, random_state=42)\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())\n\nmodel.fit(X,Y) \noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_GBC = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_GBC.columns = ['CLASS'] #renaming the output column to 'CLASS' \nmaria_GBC.index.name = \"Index\" #naming the index column as 'Index'\nmaria_GBC['CLASS']=maria_GBC['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_GBC.to_csv(\"maria_GBC.csv\") #changing my output file as a 'csv' file\n\n\nprint(maria_GBC['CLASS'].unique()) #checking out the unique instances in the \nprint('False: ',maria_GBC.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_GBC.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Using Stochastic Gradient Boosting Classification"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\n\nkfold = KFold(n_splits=10, random_state=42)\nmodel = XGBClassifier(n_estimators=200, random_state=42)\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())\n\nmodel.fit(X,Y) \noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_XGB = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_XGB.columns = ['CLASS'] #renaming the output column to 'CLASS' \nmaria_XGB.index.name = \"Index\" #naming the index column as 'Index'\nmaria_XGB['CLASS']=maria_XGB['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_XGB.to_csv(\"maria_XGB.csv\") #changing my output file as a 'csv' file\n\n\nprint(maria_GBC['CLASS'].unique()) #checking out the unique instances in the \nprint('False: ',maria_XGB.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_XGB.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Using Extra Trees Classifier"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\n\nX = array[:,0:11]\nY = array[:,11]\n\nkfold = KFold(n_splits=10, random_state=42)\nmodel = ExtraTreesClassifier(n_estimators=200) # (max_features=11)\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())\n \nmodel.fit(X,Y) \noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_ETX = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_ETX.columns = ['CLASS'] #renaming the output column to 'CLASS' \nmaria_ETX.index.name = \"Index\" #naming the index column as 'Index'\nmaria_ETX['CLASS']=maria_ETX['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_ETX.to_csv(\"maria_ETX.csv\") #changing my output file as a 'csv' file\n\n\nprint(maria_ETX['CLASS'].unique()) #checking out the unique instances in the \nprint('False: ',maria_ETX.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_ETX.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column ","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# CONCLUSION\n## From the algorithm comparisons and my prediction scores, Naive Bayes algorithm performed the best.\n## I think this is because the data was following a Gaussian distribution(normally distributed) as seen earlier from the density subplots."}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4} \ No newline at end of file diff --git a/Assignment Colab/MARIA MAGDALENE NAMAGANDA FINAL_UPDATE.ipynb b/Assignment Colab/MARIA MAGDALENE NAMAGANDA FINAL_UPDATE.ipynb new file mode 100644 index 0000000..460ea4f --- /dev/null +++ b/Assignment Colab/MARIA MAGDALENE NAMAGANDA FINAL_UPDATE.ipynb @@ -0,0 +1 @@ +{"cells":[{"metadata":{},"cell_type":"markdown","source":"# MARIA MAGDALENE NAMAGANDA\n# 2019/HD07/24853U\n# Ace_class Kaggle assignment_1"},{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n for filename in filenames:\n print(os.path.join(dirname, filename))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Importing some of the needed packages and libraries"},{"metadata":{"trusted":true},"cell_type":"code","source":"import pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib import pyplot\nimport seaborn as sns\n\nfrom sklearn.model_selection import KFold\nfrom pandas import read_csv\nfrom sklearn.metrics import confusion_matrix\nfrom sklearn.metrics import classification_report\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.model_selection import train_test_split\n\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis\nfrom sklearn.svm import SVC\nfrom sklearn.ensemble import AdaBoostClassifier\nfrom sklearn.ensemble import GradientBoostingClassifier\nfrom sklearn.ensemble import ExtraTreesClassifier\nfrom xgboost import XGBClassifier\nfrom sklearn.ensemble import RandomForestClassifier\n\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Description of Libraries used.\n* Pandas is a library in Python for data manipulation and analysis. It offers data structures and operations for manipulating numerical tables and time series.\n* Matplotlib is a plotting library for the Python.\n* Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics.\n* K-Fold cross validation is where a given data set is split into a K number of sections/folds where each fold is used as a testing set at some point.\n* A confusion matrix is a table that is often used to describe the performance of a classification model on a set of test data for which the true values are known.\n* In Train/Test Split the data we use is usually split into training data and test data. The training set contains a known output and the model learns on this data in order to be generalized to other data later on\n* Logistic Regression is used for classification problems, it is a predictive analysis algorithm and based on the concept of probability.\n* A decision tree is a flowchart-like tree structure where an internal node represents feature(attribute), the branch represents a decision rule, and each leaf node represents the outcome.\n* KNeighbours Classifier is a non-parametric algorithm whose purpose is to use a database in which the data points are separated into several classes to predict the classification of a new sample point.\n* The Naive Bayes is a classification algorithm that is suitable for binary and multiclass classification. It performs well in cases of categorical input variables compared to numerical variables. \n* The linear Discriminant analysis estimates the probability that a new set of inputs belongs to every class.\n* SVC (Support Vector Classifier) is to fit the data you provide, returning a \"best fit\" hyperplane that divides, or categorizes your data.\n* The basic concept behind Adaboost is to set the weights of classifiers and training the data sample in each iteration such that it ensures the accurate predictions of unusual observations.\n* AdaBoost works by weighting the observations, putting more weight on difficult to classify instances and less on those already handled well.\n* ExtraTreesClassifier, like RandomForest, randomizes certain decisions and subsets of data to minimize over-learning from the data and overfitting."},{"metadata":{},"cell_type":"markdown","source":"> *Now i need to get rid of some unnecessary warnings by ignoring them*"},{"metadata":{"trusted":true},"cell_type":"code","source":"#To avoid unnecessary warnings, I will ignore them in the code below\nimport warnings\nwarnings.filterwarnings('ignore')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Loading the datasets \n### There are two datasets given; \n1. AMP_TrainSet.csv and \n2. Test.csv "},{"metadata":{"_cell_guid":"","_uuid":"","trusted":true},"cell_type":"code","source":"#Loading the datasets, \n\nTrain = pd.read_csv(\"../input/amp-data-set/AMP_TrainSet.csv\")\nTest = pd.read_csv(\"../input/amp-data-set/Test.csv\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### For training the model, I will first use the training set which I will further split into the train and validation set. \n### Then I will test the model on the Test set provided to gauge its performance."},{"metadata":{},"cell_type":"markdown","source":"# Exploring my data\n## Exploring data helps one understand what kind of data is given. That is to say knowing how much data it is, the shape, type, dimensions, missing values, data summary, correlation of attributes among others as am going to do in the following steps."},{"metadata":{"trusted":true},"cell_type":"code","source":"#here, am trying to find the type of data\ntype(Train)\ntype(Test)\nTrain.dtypes, Test.dtypes","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# checking the dimensions of the data\n# this retuns the number of rows and columns in the data\n\nTrain.shape, Test.shape\n\n#this helps to know how big the data is in terms of rows and columns.\n#also from here I can tell which data is labeled","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Data description\n>For now, I will focus more on the train dataset because its what I will use to train the model "},{"metadata":{"trusted":true},"cell_type":"code","source":"#getting a description of the train dataset\n#description gives a summary of the data.\n\nTrain.describe()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#looking at the first 5 entries of my data\nTrain.head()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Class Distribution\n> From the Train dataset, i see there is an extra 'CLASS' column which will be my validation set.\n### I need to know how this class is distributed to guide me on what to do with it."},{"metadata":{"trusted":true},"cell_type":"code","source":"#to see the class distribution, I will plot a bar graph\nTrain.groupby('CLASS').size().plot(kind='bar')\npyplot.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> I would like to know how many instaces i have for each class"},{"metadata":{"trusted":true},"cell_type":"code","source":"#getting the number of instances in each class\nTrain.groupby('CLASS').size()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### There are 1519 intances for each class which is proof for even distribution.\n### From the above barplot and class instances, I can see that the classes are evenly distributed so no need to use smote."},{"metadata":{},"cell_type":"markdown","source":"# Data Visualisation\n### Data visualization is the technique to present the data in a pictorial or graphical format. It enables one to analyze data visually. The data in a graphical format allows identification of new trends and patterns easily.\n### Visualisation identifies the relationship between data points and variables."},{"metadata":{},"cell_type":"markdown","source":"## Density plots"},{"metadata":{},"cell_type":"markdown","source":"> I chose to use density plots because they are better at determing the distribution shape as they are not affected by the number of bins as is the case with Histograms."},{"metadata":{"trusted":true},"cell_type":"code","source":"#now plotting density subplots\n#setting the figsize to 12 so that my graphs are not congested\nTrain.plot(kind='density', subplots = True, layout=(3,4), sharex= False, sharey= False, figsize=(12,12))\nplt.show()\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> From the above density subpots, I can see that most of the data follows a Gaussian distribution given some of the characteristics such as bell shaped curves and graphs being symmetrical about the mean."},{"metadata":{},"cell_type":"markdown","source":"## Box and whisker plots\n> A box plot is a type of graph that displays a summary of a large amount of data in terms of the median, upper quartile, lower quartile, minimum and maximum data values.\n\n> It handles large data easily, gives a clear summary and displays outliers."},{"metadata":{"trusted":true},"cell_type":"code","source":"#plotting a box and whisker graph\n#setting the figsize to 10 so that the plots are not congested.\nTrain.plot(kind='box', subplots = True, layout=(3,4), sharex= False, sharey= False, figsize=(10,10))\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Looking at the correlation of the data"},{"metadata":{},"cell_type":"markdown","source":"> Correlation is the relationship between two variables. The commonly used method is Pearson's correlation coefficient. It assumes a normal distribution of the attributes involved.\n\n> -1 shows full negative correlation, \n\n> +1 shows full negative correlation and \n\n> 0 shows no correlation at all."},{"metadata":{"trusted":true},"cell_type":"code","source":"#first I will checkfor the pairwise correlation of the attributes.\nTrain.corr(method='pearson')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Then now am reviewing the inter-correlation of attributes using heatmap\n#graphical representation\nplt.figure(figsize=(6,6))\nsns.heatmap(Train.corr(method='pearson'))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Ill also check the correlation in regards to the 'CLASS' attribute\nTrain.corr(method='pearson')['CLASS']","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Skewnwess of the data\n> knowing data skewness allows one to perform data preparation and improve a model\n\n> If Skewness value lies above +1 or below -1 then the data is highly skewed. \n\n> If skewness value lies between +0.5 and -0.5 then the data ids moderately skewed.\n\n> If skewness is 0 then data is symmetrical"},{"metadata":{"trusted":true},"cell_type":"code","source":"#Checking out skewness of data\nTrain.skew().plot(kind='bar')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Comparing Machine Learning Algorithms\n> This helps to choose the best model for the problem at hand.\n\n> Using resampling methods like cross validation, gives an estimate for how accurate each model may be on unseen data.\n\n> It is important to ensure that each algorithm is evaluated in the same way on the same data to avoid bias."},{"metadata":{"trusted":true},"cell_type":"code","source":"#comparing different models to from which ill choose.\n\n\n# load dataset\n\narray = Train.values\n\n#split the dataset \nX = array[:,0:11] #X = Train.drop(columns=['CLASS'])\nY = array[:,11] #Y = Train['CLASS']\n\n# preparing models and adding them to a list\nmodels = []\nmodels.append(('LR', LogisticRegression()))\nmodels.append(('LDA', LinearDiscriminantAnalysis()))\nmodels.append(('KNN', KNeighborsClassifier()))\nmodels.append(('CART', DecisionTreeClassifier()))\nmodels.append(('NB', GaussianNB()))\nmodels.append(('SVM', SVC()))\nmodels.append(('AB', AdaBoostClassifier()))\nmodels.append(('GBC', GradientBoostingClassifier()))\nmodels.append(('EXT', ExtraTreesClassifier()))\nmodels.append(('RTC', RandomForestClassifier()))\n#models.append(('XGB', XGBClassifier)) \n#am commenting out XGB it does not seem to be a scikit-learn estimator as it does not implement a 'get_params' methods.\n\n# evaluating each model in turn\nresults = []\nnames = []\n\nfor name, model in models:\n kfold = KFold(n_splits=50, random_state=42)\n cv_results = cross_val_score(model, X, Y, cv=kfold, scoring='accuracy')\n results.append(cv_results)\n names.append(name)\n msg = (name, cv_results.mean(), cv_results.std())\n print(msg)\n\n# boxplot algorithm comparison\nfig = pyplot.figure()\nfig.suptitle('Algorithm Comparison')\nax = fig.add_subplot(111)\npyplot.boxplot(results)\nax.set_xticklabels(names)\npyplot.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> ## From the above algorithm comparison, I can see that Naive Bayes(NB), ExtraTreesClassifiers(EXT) and RandomForestClassifiers(RTC) are some of the best performing algorithms. \n> ## Am yet to find out the overall best valgorithm after prediction on the Test set"},{"metadata":{},"cell_type":"markdown","source":"# Feature selection \n## Using recursive feature elimination\n> Sometimes, you may asses a dataset and find out that you do not need to use all the given features. This can be because some of them are highly correlates or they are not in any way helpful in developing the model.\n* It is therefore important to get rid of some features where applicable.\n\n> For this data, I will use Recursive Feature Elimination(RFE)"},{"metadata":{"trusted":true},"cell_type":"code","source":"#feature selection using RFE\n#first i will start with choosing 4 features\nfrom sklearn.feature_selection import RFE\nfrom sklearn.linear_model import LogisticRegression\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = LogisticRegression()\nrfe = RFE(model, 4)\nfit = rfe.fit(X, Y)\nprint(\"Num Features: \", fit.n_features_)\nprint(\"Selected Features:\", fit.support_)\nprint(\"Feature Ranking: \", fit.ranking_)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Calling out the column names so I can know which features am going to drop from RFE\nTrain.columns","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Using Feature importance"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.ensemble import ExtraTreesClassifier\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = ExtraTreesClassifier()\nmodel.fit(X, Y)\nprint(model.feature_importances_)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## If am to use 4 features and drop the rest\n> I will assign the new dataset a variable 'New_Train4' after choosing the 4 features and dropping the rest."},{"metadata":{"trusted":true},"cell_type":"code","source":"# I will call the new Train data with selected features New_Train4.\nTrain\nNew_Train4 = Train.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#dropping the same features in the test dataset\nNew_Test4 = Test.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#viewing the selected features\nNew_Train4.columns","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now splitting data\n#array = New_Train.values\nX = New_Train4.values[:,0:4]\nY = New_Train4.values[:,4]\nfrom sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size=0.2, random_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# also train and test the model on Matthews correlation coefficient.\nfrom sklearn.metrics import matthews_corrcoef\n\nGS = GaussianNB()\nGS.fit(X_Train,Y_Train)\npred = GS.predict(X_Test)\n\nprint(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Using four features gives me a very low MCC and low overall score.\n## I'll therefore consider using 8 features and see what score I get."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.feature_selection import RFE\nfrom sklearn.linear_model import LogisticRegression\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = LogisticRegression()\nrfe = RFE(model, 8)\nfit = rfe.fit(X, Y)\nprint(\"Num Features: \", fit.n_features_)\nprint(\"Selected Features:\", fit.support_)\nprint(\"Feature Ranking: \", fit.ranking_)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# I will call the new Train data with selected features New_Train8.\nTrain\nNew_Train8 = Train.drop(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'AS_DAYM780201'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#dropping the same features in the test dataset\nNew_Test8 = Test.drop(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'AS_DAYM780201'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now splitting data\n#array = New_Train.values\n\n\nX = New_Train8.values[:,0:8]\nY = New_Train8.values[:,8]\nfrom sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size=0.2, random_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now creating a model and training it on 8 features\nmodel = LogisticRegression(solver='liblinear', C=0.05, multi_class='ovr', random_state=30)\nmodel.fit(X_Train, Y_Train)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2,\nrandom_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.metrics import matthews_corrcoef\n\nnv = GaussianNB()\nnv.fit(X_Train,Y_Train)\npred = nv.predict(X_Test)\n\nprint(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Standardising data\n> This is useful to transform attributes with a Gaussian distribution and it workd better with rescaled data(also known as normalistaion where attributes are scaled into a range between 0 and 1)"},{"metadata":{},"cell_type":"markdown","source":"# Below are some of the algorithms I will be using;"},{"metadata":{},"cell_type":"markdown","source":"# LINEAR ALGORITHMS\n1. Linear Regression\n2. Logistic Regression\n3. Linear Discriminant Analysis"},{"metadata":{},"cell_type":"markdown","source":"# Logistic Regression using 8 features"},{"metadata":{"trusted":true},"cell_type":"code","source":"# here am using a dataset 'New_Train8' with 8 selected features\narray = New_Train8.values\nX = array[:,0:8]\nY = array[:,8]\n\nkfold = KFold(n_splits=10, random_state=42) #spliiting my data into 10 folds and random_state of 42 for reproducibility\nmodel = LogisticRegression() #calling out the prediction algorithm\nresults = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\nprint(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n\nmodel.fit(X,Y)\noutput = model.predict(New_Test8.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_logistic = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_logistic.columns = ['CLASS'] #renaming the output column to 'CLASS'\nmaria_logistic.index.name = \"Index\" #naming the index column as 'Index'\nmaria_logistic['CLASS']=maria_logistic['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_logistic.to_csv(\"maria_logistic.csv\") #changing my output file as a 'csv' file\n\nprint(maria_logistic['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\nprint('False: ',maria_logistic.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_logistic.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# NOTE\n> I have noticed that for this particular dataset, the more I drop features, the prediction scores also keep decreasing.\n\n> With 4 features selected, the score was low, with 8 features, the score improved and with all features, the prediction score was high.\n\n> I therefore decided to work with all the features."},{"metadata":{},"cell_type":"markdown","source":"# Applying Linear Dicriminant Analysis (LDA) using all features "},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\nnum_folds = 10\nkfold = KFold(n_splits=10, random_state=42) #spliiting my data into 10 folds and random_state of 42 for reproducibility\nmodel = LinearDiscriminantAnalysis() #calling out the prediction algorithm\nresults = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\nprint(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n\nmodel.fit(X,Y)\noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_LDA = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_LDA.columns = ['CLASS'] #renaming the output column to 'CLASS'\nmaria_LDA.index.name = \"Index\" #naming the index column as 'Index'\nmaria_LDA['CLASS']=maria_LDA['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_LDA.to_csv(\"maria_LDA.csv\") #changing my output file as a 'csv' file\n\nprint(maria_LDA['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\nprint('False: ',maria_LDA.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_LDA.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# NON LINEAR ALGORITHMS\n1. Naive Bayes\n2. Support Vector Machines\n3. K-Nearest Neighbours\n4. Classification and Regression Trees\n5. Learning Vector Quantization"},{"metadata":{},"cell_type":"markdown","source":"# Using Naive Bayes and all the features"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\ntest_size = 0.35 \n\nkfold = KFold(n_splits=10) #spliiting my data into 10 folds \n\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size, random_state=42) #random_state of 42 for reproducibility\n\nmodel = GaussianNB() #calling out the prediction algorithm\nresults = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\nprint(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n\n\nmodel.fit(X,Y)\noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria2_bayes = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria2_bayes.columns = ['CLASS'] #renaming the output column to 'CLASS'\nmaria2_bayes.index.name = \"Index\" #naming the index column as 'Index'\nmaria2_bayes['CLASS']=maria2_bayes['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria2_bayes.to_csv(\"maria2_bayes.csv\") #changing my output file as a 'csv' file\n\n\nprint(maria2_bayes['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\nprint('False: ',maria2_bayes.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria2_bayes.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Support Vector Machines algorithm using all features"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\nkfold = KFold(n_splits=10) #spliiting my data into 10 folds\n\nmodel = SVC() #calling out the prediction algorithm\nscoring = 'acuracy'\nresults = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\nprint(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n\nmodel.fit(X, Y)\noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nmcc = matthews_corrcoef(model.predict(X), Y)\nprint('MCC: ',mcc)\n\nmaria_svc = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_svc.columns = ['CLASS'] #renaming the output column to 'CLASS'\nmaria_svc.index.name = 'Index' #naming the index column as 'Index'\nmaria_svc['CLASS'] = maria_svc['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\n\nmaria_svc.to_csv('maria_svc.csv') #changing my output file as a 'csv' file\n\nprint(maria_svc['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\nprint('False: ',maria_svc.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_svc.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Applying Classification and Regression Trees"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.tree import DecisionTreeClassifier\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\nkfold = KFold(n_splits=10, random_state=42) #spliiting my data into 10 folds and random_state of 42 for reproducibility\nmodel = DecisionTreeClassifier() #calling out the prediction algorithm\nresults = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\nprint(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n\n\nmodel.fit(X,Y)\noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_tree = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_tree.columns = ['CLASS'] #renaming the output column to 'CLASS'\nmaria_tree.index.name = \"Index\" #naming the index column as 'Index'\nmaria_tree['CLASS']=maria_tree['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_tree.to_csv(\"maria_tree.csv\") #changing my output file as a 'csv' file\n\n\nprint(maria_tree['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\nprint('False: ',maria_tree.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_tree.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# K-Nearest Neighbours"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\n\nkfold = KFold(n_splits=10, random_state=42) #spliiting my data into 10 folds and random_state of 42 for reproducibility\nmodel = KNeighborsClassifier() #calling out the prediction algorithm\nresults = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\nprint(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n\nmodel.fit(X,Y) \noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_knn = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_knn.columns = ['CLASS'] #renaming the output column to 'CLASS' \nmaria_knn.index.name = \"Index\" #naming the index column as 'Index'\nmaria_knn['CLASS']=maria_knn['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_knn.to_csv(\"maria_knn.csv\") #changing my output file as a 'csv' file\n\n\nprint(maria_knn['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\nprint('False: ',maria_knn.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_knn.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Esemble Algorithms\n1. Boosting and Adaboost\n2. Bagging and Random forest"},{"metadata":{},"cell_type":"markdown","source":"# Applying Adaboost "},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\n\nX = array[:,0:11]\nY = array[:,11]\n\nkfold = KFold(n_splits=10, random_state=42)\n\nmodel = AdaBoostClassifier(n_estimators=200, random_state=42) \nresults = cross_val_score(model, X, Y, cv=kfold)\n\nprint(results.mean())\n\n\ntest_set = Test.values\nmodel.fit(X, Y)\noutput = model.predict(test_set)\n\nmcc = matthews_corrcoef(model.predict(X), Y)\nprint('MCC: ',mcc)\n\nmaria_AB= pd.DataFrame(output)\nmaria_AB.columns = ['CLASS']\nmaria_AB.index.name = 'Index'\nmaria_AB['CLASS'] = maria_AB['CLASS'].map({0.0:False, 1.0:True})\n\nmaria_AB.to_csv('maria_AB.csv')\n\nprint(maria_AB['CLASS'].unique())\nprint('False: ',maria_AB.groupby('CLASS').size()[0].sum())\nprint('True: ',maria_AB.groupby('CLASS').size()[1].sum())","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Applying Gradient Boosting Classifier"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\n\nX = array[:,0:11]\nY = array[:,11]\n\n#num_trees = 200\n#seed =42\n\nkfold = KFold(n_splits=10, random_state=42)\nmodel = GradientBoostingClassifier(n_estimators=200, random_state=42)\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())\n\nmodel.fit(X,Y) \noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_GBC = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_GBC.columns = ['CLASS'] #renaming the output column to 'CLASS' \nmaria_GBC.index.name = \"Index\" #naming the index column as 'Index'\nmaria_GBC['CLASS']=maria_GBC['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_GBC.to_csv(\"maria_GBC.csv\") #changing my output file as a 'csv' file\n\n\nprint(maria_GBC['CLASS'].unique()) #checking out the unique instances in the \nprint('False: ',maria_GBC.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_GBC.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Using Stochastic Gradient Boosting Classification"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\n\nkfold = KFold(n_splits=10, random_state=42)\nmodel = XGBClassifier(n_estimators=200, random_state=42)\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())\n\nmodel.fit(X,Y) \noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_XGB = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_XGB.columns = ['CLASS'] #renaming the output column to 'CLASS' \nmaria_XGB.index.name = \"Index\" #naming the index column as 'Index'\nmaria_XGB['CLASS']=maria_XGB['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_XGB.to_csv(\"maria_XGB.csv\") #changing my output file as a 'csv' file\n\n\nprint(maria_GBC['CLASS'].unique()) #checking out the unique instances in the \nprint('False: ',maria_XGB.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_XGB.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Using Extra Trees Classifier"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\n\nX = array[:,0:11]\nY = array[:,11]\n\nkfold = KFold(n_splits=10, random_state=42)\nmodel = ExtraTreesClassifier(n_estimators=200) # (max_features=11)\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())\n \nmodel.fit(X,Y) \noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_ETX = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_ETX.columns = ['CLASS'] #renaming the output column to 'CLASS' \nmaria_ETX.index.name = \"Index\" #naming the index column as 'Index'\nmaria_ETX['CLASS']=maria_ETX['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_ETX.to_csv(\"maria_ETX.csv\") #changing my output file as a 'csv' file\n\n\nprint(maria_ETX['CLASS'].unique()) #checking out the unique instances in the \nprint('False: ',maria_ETX.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_ETX.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column ","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# CONCLUSION\n## From the algorithm comparisons and my prediction scores, Naive Bayes algorithm performed the best.\n## I think this is because the data was following a Gaussian distribution(normally distributed) as seen earlier from the density subplots."},{"metadata":{},"cell_type":"markdown","source":"# REFERENCES\n1. https://realpython.com/logistic-regression-python/\n2. https://www.tutorialspoint.com/machine_learning_with_python/machine_learning_with_python_extra_trees.htm\n3. https://stackabuse.com/gradient-boosting-classifiers-in-python-with-scikit-learn/\n4. https://machinelearningmastery.com/stochastic-gradient-boosting-xgboost-scikit-learn-python/\n5. https://machinelearningmastery.com/stochastic-gradient-boosting-xgboost-scikit-learn-python/\n6. https://machinelearningmastery.com/compare-machine-learning-algorithms-python-scikit-learn/\n7. https://machinelearningmastery.com/master-machine-learning-algorithms/\n8. https://machinelearningmastery.com/compare-machine-learning-algorithms-python-scikit-learn/\n9. https://github.com/search?q=data-analysis-and-visualization-with-python&type=Repositories\n10. https://stackabuse.com/applying-filter-methods-in-python-for-feature-selection/\n11. https://towardsdatascience.com/decision-tree-in-machine-learning-e380942a4c96\n12. https://machinelearningmastery.com/compare-machine-learning-algorithms-python-scikit-learn/"}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4} \ No newline at end of file diff --git a/Assignment Colab/MARIA MAGDALENE NAMAGANDA.ipynb b/Assignment Colab/MARIA MAGDALENE NAMAGANDA.ipynb deleted file mode 100644 index 2f53cab..0000000 --- a/Assignment Colab/MARIA MAGDALENE NAMAGANDA.ipynb +++ /dev/null @@ -1 +0,0 @@ -{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n for filename in filenames:\n print(os.path.join(dirname, filename))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#import the necessary libraries you are going to use\nimport warnings\nwarnings.filterwarnings('ignore')\n\n# -----> Put your code here below:\n\n\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Working with AMP_Data_set\n## `Training and testing data in Machine Learning`\n"},{"metadata":{"_cell_guid":"","_uuid":"","trusted":true},"cell_type":"code","source":"#Load the datasets, there are two i.e the Train and Test datasets\n\nTrain = pd.read_csv(\"../input/amp-data-set/AMP_TrainSet.csv\")\nTest = pd.read_csv(\"../input/amp-data-set/Test.csv\")\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":">Getting to know more about the data"},{"metadata":{"trusted":true},"cell_type":"code","source":"#here, am trying to find the kind of data am dealing with.\nprint(type(Train))\nprint(type(Test))\nprint(Train.dtypes)\nprint(Test.dtypes)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# check the dimensions of your data\n# this retuns the number of rows and columns in the data\n\nTrain.shape, Test.shape\n\n#this helps to know how big the data is in terms of rows and columns.\n#it also informs one of which data is labeled","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> The data is pre-prepared so ill just continue to work with it, since the Train dataset is already labeled with a CLASS attribute."},{"metadata":{"trusted":true},"cell_type":"code","source":"#getting a description of the data\n#Train.describe, Test.describe\nTrain.describe()\nTest.describe()\n#description gives a summary of the data.","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#looking at the first 5 entries of my data\nTrain.head()\nTest.head()\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":">Looking at the skewness of the data"},{"metadata":{"trusted":true},"cell_type":"code","source":"#knowing data skewness allows one to perform data preparation and improve a model\nTrain.skew().plot(kind='bar')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> Data correlation."},{"metadata":{"trusted":true},"cell_type":"code","source":"#first ill review the pairwise correlation of the attributes.\nTrain.corr(method='pearson')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Reviewing inter-correlation of attributes using heatmap\n#graphical representation\nplt.figure(figsize=(6,6))\nsns.heatmap(Train.corr(method='pearson'))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Ill also check the correlation in regards to the 'CLASS' attribute\nTrain.corr(method='pearson')['CLASS']","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Train['CLASS'].value_counts","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#I need to know the distribution of the class attribute of my data.\nprint(Train.groupby('CLASS').size().plot(kind='bar'))\n#train.CLASS.value_counts().plot(kind='bar')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"\n### From the above bar graph, the Class distribution is even which means am dealing with balanced data."},{"metadata":{},"cell_type":"markdown","source":"# Feature selection \n## Using recursive feature elimination"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.feature_selection import RFE\nfrom sklearn.linear_model import LogisticRegression\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = LogisticRegression()\nrfe = RFE(model, 4)\nfit = rfe.fit(X, Y)\nprint(\"Num Features: \", fit.n_features_)\nprint(\"Selected Features:\", fit.support_)\nprint(\"Feature Ranking: \", fit.ranking_)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Calling out the column names so I can know which features am going to drop from RFE\nTrain.columns","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Using Feature importance"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.ensemble import ExtraTreesClassifier\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = ExtraTreesClassifier()\nmodel.fit(X, Y)\nprint(model.feature_importances_)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Am going to use 4 features and drop the rest"},{"metadata":{"trusted":true},"cell_type":"code","source":"# I will call the new Train data with selected features New_Train.\nTrain\nNew_Train = Train.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#dropping the same features in the test dataset\nNew_Test = Test.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#viewing tselected features\nNew_Train.columns","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Rescaling data"},{"metadata":{"trusted":true},"cell_type":"code","source":"from numpy import set_printoptions\nfrom sklearn.preprocessing import MinMaxScaler\narray = New_Train.values\n\n#seperating data into onput and output options\nX = array[:,0:4]\nY = array[:,4]\nscaler = MinMaxScaler(feature_range = (0,1))\nrescaledX = scaler.fit_transform(X)\n\n#summarising transformed data\nset_printoptions(precision = 3)\nprint(rescaledX[0:4,:])\n ","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Standardising data"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.preprocessing import StandardScaler\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Comparing models to use"},{"metadata":{"trusted":true},"cell_type":"code","source":"#comparing different models to from which ill choose.\nfrom matplotlib import pyplot\nfrom sklearn.model_selection import KFold\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.svm import SVC\n\n\n# load dataset\n\narray = New_Train.values\n\n#split the dataset \nX = array[:,0:4] #X = Train.drop(columns=['CLASS'])\nY = array[:,4] #Y = Train['CLASS']\n\n# prepare models and add them to a list\nmodels = []\nmodels.append(('LR', LogisticRegression()))\nmodels.append(('LDA', LinearDiscriminantAnalysis()))\nmodels.append(('KNN', KNeighborsClassifier()))\nmodels.append(('CART', DecisionTreeClassifier()))\nmodels.append(('NB', GaussianNB()))\nmodels.append(('SVM', SVC()))\n\n# evaluate each model in turn\nresults = []\nnames = []\n\nfor name, model in models:\n kfold = KFold(n_splits=40, random_state=10)\n cv_results = cross_val_score(model, X, Y, cv=kfold, scoring='accuracy')\n results.append(cv_results)\n names.append(name)\n msg = (name, cv_results.mean(), cv_results.std())\n print(msg)\n\n# boxplot algorithm comparison\nfig = pyplot.figure()\nfig.suptitle('Algorithm Comparison')\nax = fig.add_subplot(111)\npyplot.boxplot(results)\nax.set_xticklabels(names)\npyplot.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now slitting data\n#array = New_Train.values\nX = New_Train.values[:,0:4]\nY = New_Train.values[:,4]\nfrom sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size=0.2, random_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# also train and test the model on Matthews correlation coefficient.\nfrom sklearn.metrics import matthews_corrcoef\n\nGS = GaussianNB()\nGS.fit(X_Train,Y_Train)\npred = GS.predict(X_Test)\n\nprint(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now creating a model and training it\nmodel = LogisticRegression(solver='liblinear', C=0.05, multi_class='ovr', random_state=30)\nmodel.fit(X_Train, Y_Train)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2,\nrandom_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.metrics import matthews_corrcoef\n\nnv = GaussianNB()\nnv.fit(X_Train,Y_Train)\npred = nv.predict(X_Test)\n\nprint(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#model = DecisionTreeClassifier()\n\n#model.fit(X_train, y_train)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Test.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#we now need to predict on the test dataset\nmd = pd.DataFrame((New_Test.index,nv.predict(New_Test))).T\nmd = md.rename(columns={0:\"Index\",1:\"CLASS\"}).set_index('Index')\nmd.to_csv('maria.csv')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"import os\nos.listdir()\n!ls ../../kaggle/working/","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4} \ No newline at end of file From 46a9efb96676f8af83e90417ef81815867c4558f Mon Sep 17 00:00:00 2001 From: Atwine Date: Thu, 19 Mar 2020 12:25:38 +0300 Subject: [PATCH 25/29] gitignore --- .gitignore | 0 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 .gitignore diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..e69de29 From f6c4862bf16985d7b72d013970615122d15805f9 Mon Sep 17 00:00:00 2001 From: Atwine Date: Fri, 27 Mar 2020 11:41:16 +0300 Subject: [PATCH 26/29] Maria --- ...RIA MAGDALENE NAMAGANDA FINAL_UPDATE.ipynb | 1281 ++++++++++++++++- 1 file changed, 1280 insertions(+), 1 deletion(-) diff --git a/Assignment Colab/MARIA MAGDALENE NAMAGANDA FINAL_UPDATE.ipynb b/Assignment Colab/MARIA MAGDALENE NAMAGANDA FINAL_UPDATE.ipynb index 460ea4f..78f6e08 100644 --- a/Assignment Colab/MARIA MAGDALENE NAMAGANDA FINAL_UPDATE.ipynb +++ b/Assignment Colab/MARIA MAGDALENE NAMAGANDA FINAL_UPDATE.ipynb @@ -1 +1,1280 @@ -{"cells":[{"metadata":{},"cell_type":"markdown","source":"# MARIA MAGDALENE NAMAGANDA\n# 2019/HD07/24853U\n# Ace_class Kaggle assignment_1"},{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n for filename in filenames:\n print(os.path.join(dirname, filename))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Importing some of the needed packages and libraries"},{"metadata":{"trusted":true},"cell_type":"code","source":"import pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib import pyplot\nimport seaborn as sns\n\nfrom sklearn.model_selection import KFold\nfrom pandas import read_csv\nfrom sklearn.metrics import confusion_matrix\nfrom sklearn.metrics import classification_report\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.model_selection import train_test_split\n\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis\nfrom sklearn.svm import SVC\nfrom sklearn.ensemble import AdaBoostClassifier\nfrom sklearn.ensemble import GradientBoostingClassifier\nfrom sklearn.ensemble import ExtraTreesClassifier\nfrom xgboost import XGBClassifier\nfrom sklearn.ensemble import RandomForestClassifier\n\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Description of Libraries used.\n* Pandas is a library in Python for data manipulation and analysis. It offers data structures and operations for manipulating numerical tables and time series.\n* Matplotlib is a plotting library for the Python.\n* Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics.\n* K-Fold cross validation is where a given data set is split into a K number of sections/folds where each fold is used as a testing set at some point.\n* A confusion matrix is a table that is often used to describe the performance of a classification model on a set of test data for which the true values are known.\n* In Train/Test Split the data we use is usually split into training data and test data. The training set contains a known output and the model learns on this data in order to be generalized to other data later on\n* Logistic Regression is used for classification problems, it is a predictive analysis algorithm and based on the concept of probability.\n* A decision tree is a flowchart-like tree structure where an internal node represents feature(attribute), the branch represents a decision rule, and each leaf node represents the outcome.\n* KNeighbours Classifier is a non-parametric algorithm whose purpose is to use a database in which the data points are separated into several classes to predict the classification of a new sample point.\n* The Naive Bayes is a classification algorithm that is suitable for binary and multiclass classification. It performs well in cases of categorical input variables compared to numerical variables. \n* The linear Discriminant analysis estimates the probability that a new set of inputs belongs to every class.\n* SVC (Support Vector Classifier) is to fit the data you provide, returning a \"best fit\" hyperplane that divides, or categorizes your data.\n* The basic concept behind Adaboost is to set the weights of classifiers and training the data sample in each iteration such that it ensures the accurate predictions of unusual observations.\n* AdaBoost works by weighting the observations, putting more weight on difficult to classify instances and less on those already handled well.\n* ExtraTreesClassifier, like RandomForest, randomizes certain decisions and subsets of data to minimize over-learning from the data and overfitting."},{"metadata":{},"cell_type":"markdown","source":"> *Now i need to get rid of some unnecessary warnings by ignoring them*"},{"metadata":{"trusted":true},"cell_type":"code","source":"#To avoid unnecessary warnings, I will ignore them in the code below\nimport warnings\nwarnings.filterwarnings('ignore')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Loading the datasets \n### There are two datasets given; \n1. AMP_TrainSet.csv and \n2. Test.csv "},{"metadata":{"_cell_guid":"","_uuid":"","trusted":true},"cell_type":"code","source":"#Loading the datasets, \n\nTrain = pd.read_csv(\"../input/amp-data-set/AMP_TrainSet.csv\")\nTest = pd.read_csv(\"../input/amp-data-set/Test.csv\")\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### For training the model, I will first use the training set which I will further split into the train and validation set. \n### Then I will test the model on the Test set provided to gauge its performance."},{"metadata":{},"cell_type":"markdown","source":"# Exploring my data\n## Exploring data helps one understand what kind of data is given. That is to say knowing how much data it is, the shape, type, dimensions, missing values, data summary, correlation of attributes among others as am going to do in the following steps."},{"metadata":{"trusted":true},"cell_type":"code","source":"#here, am trying to find the type of data\ntype(Train)\ntype(Test)\nTrain.dtypes, Test.dtypes","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# checking the dimensions of the data\n# this retuns the number of rows and columns in the data\n\nTrain.shape, Test.shape\n\n#this helps to know how big the data is in terms of rows and columns.\n#also from here I can tell which data is labeled","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Data description\n>For now, I will focus more on the train dataset because its what I will use to train the model "},{"metadata":{"trusted":true},"cell_type":"code","source":"#getting a description of the train dataset\n#description gives a summary of the data.\n\nTrain.describe()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#looking at the first 5 entries of my data\nTrain.head()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Class Distribution\n> From the Train dataset, i see there is an extra 'CLASS' column which will be my validation set.\n### I need to know how this class is distributed to guide me on what to do with it."},{"metadata":{"trusted":true},"cell_type":"code","source":"#to see the class distribution, I will plot a bar graph\nTrain.groupby('CLASS').size().plot(kind='bar')\npyplot.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> I would like to know how many instaces i have for each class"},{"metadata":{"trusted":true},"cell_type":"code","source":"#getting the number of instances in each class\nTrain.groupby('CLASS').size()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### There are 1519 intances for each class which is proof for even distribution.\n### From the above barplot and class instances, I can see that the classes are evenly distributed so no need to use smote."},{"metadata":{},"cell_type":"markdown","source":"# Data Visualisation\n### Data visualization is the technique to present the data in a pictorial or graphical format. It enables one to analyze data visually. The data in a graphical format allows identification of new trends and patterns easily.\n### Visualisation identifies the relationship between data points and variables."},{"metadata":{},"cell_type":"markdown","source":"## Density plots"},{"metadata":{},"cell_type":"markdown","source":"> I chose to use density plots because they are better at determing the distribution shape as they are not affected by the number of bins as is the case with Histograms."},{"metadata":{"trusted":true},"cell_type":"code","source":"#now plotting density subplots\n#setting the figsize to 12 so that my graphs are not congested\nTrain.plot(kind='density', subplots = True, layout=(3,4), sharex= False, sharey= False, figsize=(12,12))\nplt.show()\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> From the above density subpots, I can see that most of the data follows a Gaussian distribution given some of the characteristics such as bell shaped curves and graphs being symmetrical about the mean."},{"metadata":{},"cell_type":"markdown","source":"## Box and whisker plots\n> A box plot is a type of graph that displays a summary of a large amount of data in terms of the median, upper quartile, lower quartile, minimum and maximum data values.\n\n> It handles large data easily, gives a clear summary and displays outliers."},{"metadata":{"trusted":true},"cell_type":"code","source":"#plotting a box and whisker graph\n#setting the figsize to 10 so that the plots are not congested.\nTrain.plot(kind='box', subplots = True, layout=(3,4), sharex= False, sharey= False, figsize=(10,10))\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Looking at the correlation of the data"},{"metadata":{},"cell_type":"markdown","source":"> Correlation is the relationship between two variables. The commonly used method is Pearson's correlation coefficient. It assumes a normal distribution of the attributes involved.\n\n> -1 shows full negative correlation, \n\n> +1 shows full negative correlation and \n\n> 0 shows no correlation at all."},{"metadata":{"trusted":true},"cell_type":"code","source":"#first I will checkfor the pairwise correlation of the attributes.\nTrain.corr(method='pearson')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Then now am reviewing the inter-correlation of attributes using heatmap\n#graphical representation\nplt.figure(figsize=(6,6))\nsns.heatmap(Train.corr(method='pearson'))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Ill also check the correlation in regards to the 'CLASS' attribute\nTrain.corr(method='pearson')['CLASS']","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Skewnwess of the data\n> knowing data skewness allows one to perform data preparation and improve a model\n\n> If Skewness value lies above +1 or below -1 then the data is highly skewed. \n\n> If skewness value lies between +0.5 and -0.5 then the data ids moderately skewed.\n\n> If skewness is 0 then data is symmetrical"},{"metadata":{"trusted":true},"cell_type":"code","source":"#Checking out skewness of data\nTrain.skew().plot(kind='bar')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Comparing Machine Learning Algorithms\n> This helps to choose the best model for the problem at hand.\n\n> Using resampling methods like cross validation, gives an estimate for how accurate each model may be on unseen data.\n\n> It is important to ensure that each algorithm is evaluated in the same way on the same data to avoid bias."},{"metadata":{"trusted":true},"cell_type":"code","source":"#comparing different models to from which ill choose.\n\n\n# load dataset\n\narray = Train.values\n\n#split the dataset \nX = array[:,0:11] #X = Train.drop(columns=['CLASS'])\nY = array[:,11] #Y = Train['CLASS']\n\n# preparing models and adding them to a list\nmodels = []\nmodels.append(('LR', LogisticRegression()))\nmodels.append(('LDA', LinearDiscriminantAnalysis()))\nmodels.append(('KNN', KNeighborsClassifier()))\nmodels.append(('CART', DecisionTreeClassifier()))\nmodels.append(('NB', GaussianNB()))\nmodels.append(('SVM', SVC()))\nmodels.append(('AB', AdaBoostClassifier()))\nmodels.append(('GBC', GradientBoostingClassifier()))\nmodels.append(('EXT', ExtraTreesClassifier()))\nmodels.append(('RTC', RandomForestClassifier()))\n#models.append(('XGB', XGBClassifier)) \n#am commenting out XGB it does not seem to be a scikit-learn estimator as it does not implement a 'get_params' methods.\n\n# evaluating each model in turn\nresults = []\nnames = []\n\nfor name, model in models:\n kfold = KFold(n_splits=50, random_state=42)\n cv_results = cross_val_score(model, X, Y, cv=kfold, scoring='accuracy')\n results.append(cv_results)\n names.append(name)\n msg = (name, cv_results.mean(), cv_results.std())\n print(msg)\n\n# boxplot algorithm comparison\nfig = pyplot.figure()\nfig.suptitle('Algorithm Comparison')\nax = fig.add_subplot(111)\npyplot.boxplot(results)\nax.set_xticklabels(names)\npyplot.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> ## From the above algorithm comparison, I can see that Naive Bayes(NB), ExtraTreesClassifiers(EXT) and RandomForestClassifiers(RTC) are some of the best performing algorithms. \n> ## Am yet to find out the overall best valgorithm after prediction on the Test set"},{"metadata":{},"cell_type":"markdown","source":"# Feature selection \n## Using recursive feature elimination\n> Sometimes, you may asses a dataset and find out that you do not need to use all the given features. This can be because some of them are highly correlates or they are not in any way helpful in developing the model.\n* It is therefore important to get rid of some features where applicable.\n\n> For this data, I will use Recursive Feature Elimination(RFE)"},{"metadata":{"trusted":true},"cell_type":"code","source":"#feature selection using RFE\n#first i will start with choosing 4 features\nfrom sklearn.feature_selection import RFE\nfrom sklearn.linear_model import LogisticRegression\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = LogisticRegression()\nrfe = RFE(model, 4)\nfit = rfe.fit(X, Y)\nprint(\"Num Features: \", fit.n_features_)\nprint(\"Selected Features:\", fit.support_)\nprint(\"Feature Ranking: \", fit.ranking_)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#Calling out the column names so I can know which features am going to drop from RFE\nTrain.columns","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Using Feature importance"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.ensemble import ExtraTreesClassifier\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = ExtraTreesClassifier()\nmodel.fit(X, Y)\nprint(model.feature_importances_)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## If am to use 4 features and drop the rest\n> I will assign the new dataset a variable 'New_Train4' after choosing the 4 features and dropping the rest."},{"metadata":{"trusted":true},"cell_type":"code","source":"# I will call the new Train data with selected features New_Train4.\nTrain\nNew_Train4 = Train.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#dropping the same features in the test dataset\nNew_Test4 = Test.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#viewing the selected features\nNew_Train4.columns","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now splitting data\n#array = New_Train.values\nX = New_Train4.values[:,0:4]\nY = New_Train4.values[:,4]\nfrom sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size=0.2, random_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# also train and test the model on Matthews correlation coefficient.\nfrom sklearn.metrics import matthews_corrcoef\n\nGS = GaussianNB()\nGS.fit(X_Train,Y_Train)\npred = GS.predict(X_Test)\n\nprint(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Using four features gives me a very low MCC and low overall score.\n## I'll therefore consider using 8 features and see what score I get."},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.feature_selection import RFE\nfrom sklearn.linear_model import LogisticRegression\n\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\n# feature extraction\nmodel = LogisticRegression()\nrfe = RFE(model, 8)\nfit = rfe.fit(X, Y)\nprint(\"Num Features: \", fit.n_features_)\nprint(\"Selected Features:\", fit.support_)\nprint(\"Feature Ranking: \", fit.ranking_)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# I will call the new Train data with selected features New_Train8.\nTrain\nNew_Train8 = Train.drop(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'AS_DAYM780201'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#dropping the same features in the test dataset\nNew_Test8 = Test.drop(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'AS_DAYM780201'], axis =1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now splitting data\n#array = New_Train.values\n\n\nX = New_Train8.values[:,0:8]\nY = New_Train8.values[:,8]\nfrom sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size=0.2, random_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#now creating a model and training it on 8 features\nmodel = LogisticRegression(solver='liblinear', C=0.05, multi_class='ovr', random_state=30)\nmodel.fit(X_Train, Y_Train)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import train_test_split\nX_Train, X_Test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2,\nrandom_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.metrics import matthews_corrcoef\n\nnv = GaussianNB()\nnv.fit(X_Train,Y_Train)\npred = nv.predict(X_Test)\n\nprint(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Standardising data\n> This is useful to transform attributes with a Gaussian distribution and it workd better with rescaled data(also known as normalistaion where attributes are scaled into a range between 0 and 1)"},{"metadata":{},"cell_type":"markdown","source":"# Below are some of the algorithms I will be using;"},{"metadata":{},"cell_type":"markdown","source":"# LINEAR ALGORITHMS\n1. Linear Regression\n2. Logistic Regression\n3. Linear Discriminant Analysis"},{"metadata":{},"cell_type":"markdown","source":"# Logistic Regression using 8 features"},{"metadata":{"trusted":true},"cell_type":"code","source":"# here am using a dataset 'New_Train8' with 8 selected features\narray = New_Train8.values\nX = array[:,0:8]\nY = array[:,8]\n\nkfold = KFold(n_splits=10, random_state=42) #spliiting my data into 10 folds and random_state of 42 for reproducibility\nmodel = LogisticRegression() #calling out the prediction algorithm\nresults = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\nprint(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n\nmodel.fit(X,Y)\noutput = model.predict(New_Test8.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_logistic = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_logistic.columns = ['CLASS'] #renaming the output column to 'CLASS'\nmaria_logistic.index.name = \"Index\" #naming the index column as 'Index'\nmaria_logistic['CLASS']=maria_logistic['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_logistic.to_csv(\"maria_logistic.csv\") #changing my output file as a 'csv' file\n\nprint(maria_logistic['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\nprint('False: ',maria_logistic.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_logistic.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# NOTE\n> I have noticed that for this particular dataset, the more I drop features, the prediction scores also keep decreasing.\n\n> With 4 features selected, the score was low, with 8 features, the score improved and with all features, the prediction score was high.\n\n> I therefore decided to work with all the features."},{"metadata":{},"cell_type":"markdown","source":"# Applying Linear Dicriminant Analysis (LDA) using all features "},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\nnum_folds = 10\nkfold = KFold(n_splits=10, random_state=42) #spliiting my data into 10 folds and random_state of 42 for reproducibility\nmodel = LinearDiscriminantAnalysis() #calling out the prediction algorithm\nresults = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\nprint(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n\nmodel.fit(X,Y)\noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_LDA = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_LDA.columns = ['CLASS'] #renaming the output column to 'CLASS'\nmaria_LDA.index.name = \"Index\" #naming the index column as 'Index'\nmaria_LDA['CLASS']=maria_LDA['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_LDA.to_csv(\"maria_LDA.csv\") #changing my output file as a 'csv' file\n\nprint(maria_LDA['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\nprint('False: ',maria_LDA.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_LDA.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# NON LINEAR ALGORITHMS\n1. Naive Bayes\n2. Support Vector Machines\n3. K-Nearest Neighbours\n4. Classification and Regression Trees\n5. Learning Vector Quantization"},{"metadata":{},"cell_type":"markdown","source":"# Using Naive Bayes and all the features"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\ntest_size = 0.35 \n\nkfold = KFold(n_splits=10) #spliiting my data into 10 folds \n\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size, random_state=42) #random_state of 42 for reproducibility\n\nmodel = GaussianNB() #calling out the prediction algorithm\nresults = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\nprint(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n\n\nmodel.fit(X,Y)\noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria2_bayes = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria2_bayes.columns = ['CLASS'] #renaming the output column to 'CLASS'\nmaria2_bayes.index.name = \"Index\" #naming the index column as 'Index'\nmaria2_bayes['CLASS']=maria2_bayes['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria2_bayes.to_csv(\"maria2_bayes.csv\") #changing my output file as a 'csv' file\n\n\nprint(maria2_bayes['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\nprint('False: ',maria2_bayes.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria2_bayes.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Support Vector Machines algorithm using all features"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\nkfold = KFold(n_splits=10) #spliiting my data into 10 folds\n\nmodel = SVC() #calling out the prediction algorithm\nscoring = 'acuracy'\nresults = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\nprint(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n\nmodel.fit(X, Y)\noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nmcc = matthews_corrcoef(model.predict(X), Y)\nprint('MCC: ',mcc)\n\nmaria_svc = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_svc.columns = ['CLASS'] #renaming the output column to 'CLASS'\nmaria_svc.index.name = 'Index' #naming the index column as 'Index'\nmaria_svc['CLASS'] = maria_svc['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\n\nmaria_svc.to_csv('maria_svc.csv') #changing my output file as a 'csv' file\n\nprint(maria_svc['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\nprint('False: ',maria_svc.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_svc.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Applying Classification and Regression Trees"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.tree import DecisionTreeClassifier\narray = Train.values\nX = array[:,0:11]\nY = array[:,11]\nkfold = KFold(n_splits=10, random_state=42) #spliiting my data into 10 folds and random_state of 42 for reproducibility\nmodel = DecisionTreeClassifier() #calling out the prediction algorithm\nresults = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\nprint(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n\n\nmodel.fit(X,Y)\noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_tree = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_tree.columns = ['CLASS'] #renaming the output column to 'CLASS'\nmaria_tree.index.name = \"Index\" #naming the index column as 'Index'\nmaria_tree['CLASS']=maria_tree['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_tree.to_csv(\"maria_tree.csv\") #changing my output file as a 'csv' file\n\n\nprint(maria_tree['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\nprint('False: ',maria_tree.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_tree.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# K-Nearest Neighbours"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\n\nkfold = KFold(n_splits=10, random_state=42) #spliiting my data into 10 folds and random_state of 42 for reproducibility\nmodel = KNeighborsClassifier() #calling out the prediction algorithm\nresults = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\nprint(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n\nmodel.fit(X,Y) \noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_knn = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_knn.columns = ['CLASS'] #renaming the output column to 'CLASS' \nmaria_knn.index.name = \"Index\" #naming the index column as 'Index'\nmaria_knn['CLASS']=maria_knn['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_knn.to_csv(\"maria_knn.csv\") #changing my output file as a 'csv' file\n\n\nprint(maria_knn['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\nprint('False: ',maria_knn.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_knn.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Esemble Algorithms\n1. Boosting and Adaboost\n2. Bagging and Random forest"},{"metadata":{},"cell_type":"markdown","source":"# Applying Adaboost "},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\n\nX = array[:,0:11]\nY = array[:,11]\n\nkfold = KFold(n_splits=10, random_state=42)\n\nmodel = AdaBoostClassifier(n_estimators=200, random_state=42) \nresults = cross_val_score(model, X, Y, cv=kfold)\n\nprint(results.mean())\n\n\ntest_set = Test.values\nmodel.fit(X, Y)\noutput = model.predict(test_set)\n\nmcc = matthews_corrcoef(model.predict(X), Y)\nprint('MCC: ',mcc)\n\nmaria_AB= pd.DataFrame(output)\nmaria_AB.columns = ['CLASS']\nmaria_AB.index.name = 'Index'\nmaria_AB['CLASS'] = maria_AB['CLASS'].map({0.0:False, 1.0:True})\n\nmaria_AB.to_csv('maria_AB.csv')\n\nprint(maria_AB['CLASS'].unique())\nprint('False: ',maria_AB.groupby('CLASS').size()[0].sum())\nprint('True: ',maria_AB.groupby('CLASS').size()[1].sum())","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Applying Gradient Boosting Classifier"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\n\nX = array[:,0:11]\nY = array[:,11]\n\n#num_trees = 200\n#seed =42\n\nkfold = KFold(n_splits=10, random_state=42)\nmodel = GradientBoostingClassifier(n_estimators=200, random_state=42)\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())\n\nmodel.fit(X,Y) \noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_GBC = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_GBC.columns = ['CLASS'] #renaming the output column to 'CLASS' \nmaria_GBC.index.name = \"Index\" #naming the index column as 'Index'\nmaria_GBC['CLASS']=maria_GBC['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_GBC.to_csv(\"maria_GBC.csv\") #changing my output file as a 'csv' file\n\n\nprint(maria_GBC['CLASS'].unique()) #checking out the unique instances in the \nprint('False: ',maria_GBC.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_GBC.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Using Stochastic Gradient Boosting Classification"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\nX = array[:,0:11]\nY = array[:,11]\n\nkfold = KFold(n_splits=10, random_state=42)\nmodel = XGBClassifier(n_estimators=200, random_state=42)\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())\n\nmodel.fit(X,Y) \noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_XGB = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_XGB.columns = ['CLASS'] #renaming the output column to 'CLASS' \nmaria_XGB.index.name = \"Index\" #naming the index column as 'Index'\nmaria_XGB['CLASS']=maria_XGB['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_XGB.to_csv(\"maria_XGB.csv\") #changing my output file as a 'csv' file\n\n\nprint(maria_GBC['CLASS'].unique()) #checking out the unique instances in the \nprint('False: ',maria_XGB.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_XGB.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Using Extra Trees Classifier"},{"metadata":{"trusted":true},"cell_type":"code","source":"array = Train.values\n\nX = array[:,0:11]\nY = array[:,11]\n\nkfold = KFold(n_splits=10, random_state=42)\nmodel = ExtraTreesClassifier(n_estimators=200) # (max_features=11)\nresults = cross_val_score(model, X, Y, cv=kfold)\nprint(results.mean())\n \nmodel.fit(X,Y) \noutput = model.predict(Test.values) #testing the model on the test_set (Test.values)\n\nfrom sklearn.metrics import matthews_corrcoef\nmcc = matthews_corrcoef(model.predict(X),Y)\nprint('MCC:',mcc)\n \nmaria_ETX = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\nmaria_ETX.columns = ['CLASS'] #renaming the output column to 'CLASS' \nmaria_ETX.index.name = \"Index\" #naming the index column as 'Index'\nmaria_ETX['CLASS']=maria_ETX['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\nmaria_ETX.to_csv(\"maria_ETX.csv\") #changing my output file as a 'csv' file\n\n\nprint(maria_ETX['CLASS'].unique()) #checking out the unique instances in the \nprint('False: ',maria_ETX.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\nprint('True: ',maria_ETX.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column ","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# CONCLUSION\n## From the algorithm comparisons and my prediction scores, Naive Bayes algorithm performed the best.\n## I think this is because the data was following a Gaussian distribution(normally distributed) as seen earlier from the density subplots."},{"metadata":{},"cell_type":"markdown","source":"# REFERENCES\n1. https://realpython.com/logistic-regression-python/\n2. https://www.tutorialspoint.com/machine_learning_with_python/machine_learning_with_python_extra_trees.htm\n3. https://stackabuse.com/gradient-boosting-classifiers-in-python-with-scikit-learn/\n4. https://machinelearningmastery.com/stochastic-gradient-boosting-xgboost-scikit-learn-python/\n5. https://machinelearningmastery.com/stochastic-gradient-boosting-xgboost-scikit-learn-python/\n6. https://machinelearningmastery.com/compare-machine-learning-algorithms-python-scikit-learn/\n7. https://machinelearningmastery.com/master-machine-learning-algorithms/\n8. https://machinelearningmastery.com/compare-machine-learning-algorithms-python-scikit-learn/\n9. https://github.com/search?q=data-analysis-and-visualization-with-python&type=Repositories\n10. https://stackabuse.com/applying-filter-methods-in-python-for-feature-selection/\n11. https://towardsdatascience.com/decision-tree-in-machine-learning-e380942a4c96\n12. https://machinelearningmastery.com/compare-machine-learning-algorithms-python-scikit-learn/"}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4} \ No newline at end of file +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# MARIA MAGDALENE NAMAGANDA\n", + "# 2019/HD07/24853U\n", + "# Ace_class Kaggle assignment_1" + ] + }, + { + "cell_type": "raw", + "metadata": { + "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", + "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" + }, + "source": [ + "# This Python 3 environment comes with many helpful analytics libraries installed\n", + "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", + "# For example, here's several helpful packages to load in \n", + "\n", + "import numpy as np # linear algebra\n", + "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", + "\n", + "# Input data files are available in the \"../input/\" directory.\n", + "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", + "\n", + "import os\n", + "for dirname, _, filenames in os.walk('/kaggle/input'):\n", + " for filename in filenames:\n", + " print(os.path.join(dirname, filename))\n", + "\n", + "# Any results you write to the current directory are saved as output." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Importing some of the needed packages and libraries" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from matplotlib import pyplot\n", + "import seaborn as sns\n", + "\n", + "from sklearn.model_selection import KFold\n", + "from pandas import read_csv\n", + "from sklearn.metrics import confusion_matrix\n", + "from sklearn.metrics import classification_report\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.model_selection import train_test_split\n", + "\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "from sklearn.neighbors import KNeighborsClassifier\n", + "from sklearn.naive_bayes import GaussianNB\n", + "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", + "from sklearn.svm import SVC\n", + "from sklearn.ensemble import AdaBoostClassifier\n", + "from sklearn.ensemble import GradientBoostingClassifier\n", + "from sklearn.ensemble import ExtraTreesClassifier\n", + "from xgboost import XGBClassifier\n", + "from sklearn.ensemble import RandomForestClassifier\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Description of Libraries used.\n", + "* Pandas is a library in Python for data manipulation and analysis. It offers data structures and operations for manipulating numerical tables and time series.\n", + "* Matplotlib is a plotting library for the Python.\n", + "* Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics.\n", + "* K-Fold cross validation is where a given data set is split into a K number of sections/folds where each fold is used as a testing set at some point.\n", + "* A confusion matrix is a table that is often used to describe the performance of a classification model on a set of test data for which the true values are known.\n", + "* In Train/Test Split the data we use is usually split into training data and test data. The training set contains a known output and the model learns on this data in order to be generalized to other data later on\n", + "* Logistic Regression is used for classification problems, it is a predictive analysis algorithm and based on the concept of probability.\n", + "* A decision tree is a flowchart-like tree structure where an internal node represents feature(attribute), the branch represents a decision rule, and each leaf node represents the outcome.\n", + "* KNeighbours Classifier is a non-parametric algorithm whose purpose is to use a database in which the data points are separated into several classes to predict the classification of a new sample point.\n", + "* The Naive Bayes is a classification algorithm that is suitable for binary and multiclass classification. It performs well in cases of categorical input variables compared to numerical variables. \n", + "* The linear Discriminant analysis estimates the probability that a new set of inputs belongs to every class.\n", + "* SVC (Support Vector Classifier) is to fit the data you provide, returning a \"best fit\" hyperplane that divides, or categorizes your data.\n", + "* The basic concept behind Adaboost is to set the weights of classifiers and training the data sample in each iteration such that it ensures the accurate predictions of unusual observations.\n", + "* AdaBoost works by weighting the observations, putting more weight on difficult to classify instances and less on those already handled well.\n", + "* ExtraTreesClassifier, like RandomForest, randomizes certain decisions and subsets of data to minimize over-learning from the data and overfitting." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> *Now i need to get rid of some unnecessary warnings by ignoring them*" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "#To avoid unnecessary warnings, I will ignore them in the code below\n", + "import warnings\n", + "warnings.filterwarnings('ignore')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Loading the datasets \n", + "### There are two datasets given; \n", + "1. AMP_TrainSet.csv and \n", + "2. Test.csv " + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "_cell_guid": "", + "_uuid": "" + }, + "outputs": [], + "source": [ + "#Loading the datasets, \n", + "\n", + "Train = pd.read_csv(\"../Data/AMP_TrainSet.csv\")\n", + "Test = pd.read_csv(\"../Data/Test.csv\")\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### For training the model, I will first use the training set which I will further split into the train and validation set. \n", + "\n", + "
\n", + " @atwine: Did not explain why they are splitting, I need to see why they are doing this.\n", + "
\n", + "### Then I will test the model on the Test set provided to gauge its performance." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Exploring my data\n", + "## Exploring data helps one understand what kind of data is given. That is to say knowing how much data it is, the shape, type, dimensions, missing values, data summary, correlation of attributes among others as am going to do in the following steps." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#here, am trying to find the type of data\n", + "type(Train)\n", + "type(Test)\n", + "Train.dtypes, Test.dtypes" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# checking the dimensions of the data\n", + "# this retuns the number of rows and columns in the data\n", + "\n", + "Train.shape, Test.shape\n", + "\n", + "#this helps to know how big the data is in terms of rows and columns.\n", + "#also from here I can tell which data is labeled" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Data description\n", + ">For now, I will focus more on the train dataset because its what I will use to train the model " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#getting a description of the train dataset\n", + "#description gives a summary of the data.\n", + "\n", + "Train.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#looking at the first 5 entries of my data\n", + "Train.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Class Distribution\n", + "> From the Train dataset, i see there is an extra 'CLASS' column which will be my validation set.\n", + "### I need to know how this class is distributed to guide me on what to do with it." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#to see the class distribution, I will plot a bar graph\n", + "Train.groupby('CLASS').size().plot(kind='bar')\n", + "pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> I would like to know how many instaces i have for each class" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#getting the number of instances in each class\n", + "Train.groupby('CLASS').size()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### There are 1519 intances for each class which is proof for even distribution.\n", + "### From the above barplot and class instances, I can see that the classes are evenly distributed so no need to use smote." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Data Visualisation\n", + "### Data visualization is the technique to present the data in a pictorial or graphical format. It enables one to analyze data visually. The data in a graphical format allows identification of new trends and patterns easily.\n", + "### Visualisation identifies the relationship between data points and variables." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Density plots" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> I chose to use density plots because they are better at determing the distribution shape as they are not affected by the number of bins as is the case with Histograms." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#now plotting density subplots\n", + "#setting the figsize to 12 so that my graphs are not congested\n", + "Train.plot(kind='density', subplots = True, layout=(3,4), sharex= False, sharey= False, figsize=(12,12))\n", + "plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> From the above density subpots, I can see that most of the data follows a Gaussian distribution given some of the characteristics such as bell shaped curves and graphs being symmetrical about the mean." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Box and whisker plots\n", + "> A box plot is a type of graph that displays a summary of a large amount of data in terms of the median, upper quartile, lower quartile, minimum and maximum data values.\n", + "\n", + "> It handles large data easily, gives a clear summary and displays outliers." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#plotting a box and whisker graph\n", + "#setting the figsize to 10 so that the plots are not congested.\n", + "Train.plot(kind='box', subplots = True, layout=(3,4), sharex= False, sharey= False, figsize=(10,10))\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Looking at the correlation of the data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> Correlation is the relationship between two variables. The commonly used method is Pearson's correlation coefficient. It assumes a normal distribution of the attributes involved.\n", + "\n", + "> -1 shows full negative correlation, \n", + "\n", + "> +1 shows full negative correlation and \n", + "\n", + "> 0 shows no correlation at all." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#first I will checkfor the pairwise correlation of the attributes.\n", + "Train.corr(method='pearson')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Then now am reviewing the inter-correlation of attributes using heatmap\n", + "#graphical representation\n", + "plt.figure(figsize=(6,6))\n", + "sns.heatmap(Train.corr(method='pearson'))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Ill also check the correlation in regards to the 'CLASS' attribute\n", + "Train.corr(method='pearson')['CLASS']" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Skewnwess of the data\n", + "> knowing data skewness allows one to perform data preparation and improve a model\n", + "\n", + "> If Skewness value lies above +1 or below -1 then the data is highly skewed. \n", + "\n", + "> If skewness value lies between +0.5 and -0.5 then the data ids moderately skewed.\n", + "\n", + "> If skewness is 0 then data is symmetrical" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Checking out skewness of data\n", + "Train.skew().plot(kind='bar')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Comparing Machine Learning Algorithms\n", + "> This helps to choose the best model for the problem at hand.\n", + "\n", + "> Using resampling methods like cross validation, gives an estimate for how accurate each model may be on unseen data.\n", + "\n", + "> It is important to ensure that each algorithm is evaluated in the same way on the same data to avoid bias." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#comparing different models to from which ill choose.\n", + "\n", + "\n", + "# load dataset\n", + "\n", + "array = Train.values\n", + "\n", + "#split the dataset \n", + "X = array[:,0:11] #X = Train.drop(columns=['CLASS'])\n", + "Y = array[:,11] #Y = Train['CLASS']\n", + "\n", + "# preparing models and adding them to a list\n", + "models = []\n", + "models.append(('LR', LogisticRegression()))\n", + "models.append(('LDA', LinearDiscriminantAnalysis()))\n", + "models.append(('KNN', KNeighborsClassifier()))\n", + "models.append(('CART', DecisionTreeClassifier()))\n", + "models.append(('NB', GaussianNB()))\n", + "models.append(('SVM', SVC()))\n", + "models.append(('AB', AdaBoostClassifier()))\n", + "models.append(('GBC', GradientBoostingClassifier()))\n", + "models.append(('EXT', ExtraTreesClassifier()))\n", + "models.append(('RTC', RandomForestClassifier()))\n", + "#models.append(('XGB', XGBClassifier)) \n", + "#am commenting out XGB it does not seem to be a scikit-learn estimator as it does not implement a 'get_params' methods.\n", + "\n", + "# evaluating each model in turn\n", + "results = []\n", + "names = []\n", + "\n", + "for name, model in models:\n", + " kfold = KFold(n_splits=50, random_state=42)\n", + " cv_results = cross_val_score(model, X, Y, cv=kfold, scoring='accuracy')\n", + " results.append(cv_results)\n", + " names.append(name)\n", + " msg = (name, cv_results.mean(), cv_results.std())\n", + " print(msg)\n", + "\n", + "# boxplot algorithm comparison\n", + "fig = pyplot.figure()\n", + "fig.suptitle('Algorithm Comparison')\n", + "ax = fig.add_subplot(111)\n", + "pyplot.boxplot(results)\n", + "ax.set_xticklabels(names)\n", + "pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> ## From the above algorithm comparison, I can see that Naive Bayes(NB), ExtraTreesClassifiers(EXT) and RandomForestClassifiers(RTC) are some of the best performing algorithms. \n", + "> ## Am yet to find out the overall best valgorithm after prediction on the Test set" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Feature selection \n", + "## Using recursive feature elimination\n", + "> Sometimes, you may asses a dataset and find out that you do not need to use all the given features. This can be because some of them are highly correlates or they are not in any way helpful in developing the model.\n", + "* It is therefore important to get rid of some features where applicable.\n", + "\n", + "> For this data, I will use Recursive Feature Elimination(RFE)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#feature selection using RFE\n", + "#first i will start with choosing 4 features\n", + "from sklearn.feature_selection import RFE\n", + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "# feature extraction\n", + "model = LogisticRegression()\n", + "rfe = RFE(model, 4)\n", + "fit = rfe.fit(X, Y)\n", + "print(\"Num Features: \", fit.n_features_)\n", + "print(\"Selected Features:\", fit.support_)\n", + "print(\"Feature Ranking: \", fit.ranking_)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Calling out the column names so I can know which features am going to drop from RFE\n", + "Train.columns" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Using Feature importance" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.ensemble import ExtraTreesClassifier\n", + "\n", + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "# feature extraction\n", + "model = ExtraTreesClassifier()\n", + "model.fit(X, Y)\n", + "print(model.feature_importances_)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## If am to use 4 features and drop the rest\n", + "> I will assign the new dataset a variable 'New_Train4' after choosing the 4 features and dropping the rest." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# I will call the new Train data with selected features New_Train4.\n", + "Train\n", + "New_Train4 = Train.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#dropping the same features in the test dataset\n", + "New_Test4 = Test.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#viewing the selected features\n", + "New_Train4.columns" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#now splitting data\n", + "#array = New_Train.values\n", + "X = New_Train4.values[:,0:4]\n", + "Y = New_Train4.values[:,4]\n", + "from sklearn.model_selection import train_test_split\n", + "X_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size=0.2, random_state=42)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# also train and test the model on Matthews correlation coefficient.\n", + "from sklearn.metrics import matthews_corrcoef\n", + "\n", + "GS = GaussianNB()\n", + "GS.fit(X_Train,Y_Train)\n", + "pred = GS.predict(X_Test)\n", + "\n", + "print(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Using four features gives me a very low MCC and low overall score.\n", + "## I'll therefore consider using 8 features and see what score I get." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.feature_selection import RFE\n", + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "# feature extraction\n", + "model = LogisticRegression()\n", + "rfe = RFE(model, 8)\n", + "fit = rfe.fit(X, Y)\n", + "print(\"Num Features: \", fit.n_features_)\n", + "print(\"Selected Features:\", fit.support_)\n", + "print(\"Feature Ranking: \", fit.ranking_)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# I will call the new Train data with selected features New_Train8.\n", + "Train\n", + "New_Train8 = Train.drop(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'AS_DAYM780201'], axis =1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#dropping the same features in the test dataset\n", + "New_Test8 = Test.drop(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'AS_DAYM780201'], axis =1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#now splitting data\n", + "#array = New_Train.values\n", + "\n", + "\n", + "X = New_Train8.values[:,0:8]\n", + "Y = New_Train8.values[:,8]\n", + "from sklearn.model_selection import train_test_split\n", + "X_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size=0.2, random_state=42)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#now creating a model and training it on 8 features\n", + "model = LogisticRegression(solver='liblinear', C=0.05, multi_class='ovr', random_state=30)\n", + "model.fit(X_Train, Y_Train)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "X_Train, X_Test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2,\n", + "random_state=42)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.metrics import matthews_corrcoef\n", + "\n", + "nv = GaussianNB()\n", + "nv.fit(X_Train,Y_Train)\n", + "pred = nv.predict(X_Test)\n", + "\n", + "print(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Standardising data\n", + "> This is useful to transform attributes with a Gaussian distribution and it workd better with rescaled data(also known as normalistaion where attributes are scaled into a range between 0 and 1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Below are some of the algorithms I will be using;" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# LINEAR ALGORITHMS\n", + "1. Linear Regression\n", + "2. Logistic Regression\n", + "3. Linear Discriminant Analysis" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Logistic Regression using 8 features" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# here am using a dataset 'New_Train8' with 8 selected features\n", + "array = New_Train8.values\n", + "X = array[:,0:8]\n", + "Y = array[:,8]\n", + "\n", + "kfold = KFold(n_splits=10, random_state=42) #spliiting my data into 10 folds and random_state of 42 for reproducibility\n", + "model = LogisticRegression() #calling out the prediction algorithm\n", + "results = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\n", + "print(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n", + "\n", + "model.fit(X,Y)\n", + "output = model.predict(New_Test8.values) #testing the model on the test_set (Test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "maria_logistic = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\n", + "maria_logistic.columns = ['CLASS'] #renaming the output column to 'CLASS'\n", + "maria_logistic.index.name = \"Index\" #naming the index column as 'Index'\n", + "maria_logistic['CLASS']=maria_logistic['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\n", + "maria_logistic.to_csv(\"maria_logistic.csv\") #changing my output file as a 'csv' file\n", + "\n", + "print(maria_logistic['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\n", + "print('False: ',maria_logistic.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\n", + "print('True: ',maria_logistic.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# NOTE\n", + "> I have noticed that for this particular dataset, the more I drop features, the prediction scores also keep decreasing.\n", + "\n", + "> With 4 features selected, the score was low, with 8 features, the score improved and with all features, the prediction score was high.\n", + "\n", + "> I therefore decided to work with all the features." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Applying Linear Dicriminant Analysis (LDA) using all features " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "num_folds = 10\n", + "kfold = KFold(n_splits=10, random_state=42) #spliiting my data into 10 folds and random_state of 42 for reproducibility\n", + "model = LinearDiscriminantAnalysis() #calling out the prediction algorithm\n", + "results = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\n", + "print(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n", + "\n", + "model.fit(X,Y)\n", + "output = model.predict(Test.values) #testing the model on the test_set (Test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "maria_LDA = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\n", + "maria_LDA.columns = ['CLASS'] #renaming the output column to 'CLASS'\n", + "maria_LDA.index.name = \"Index\" #naming the index column as 'Index'\n", + "maria_LDA['CLASS']=maria_LDA['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\n", + "maria_LDA.to_csv(\"maria_LDA.csv\") #changing my output file as a 'csv' file\n", + "\n", + "print(maria_LDA['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\n", + "print('False: ',maria_LDA.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\n", + "print('True: ',maria_LDA.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# NON LINEAR ALGORITHMS\n", + "1. Naive Bayes\n", + "2. Support Vector Machines\n", + "3. K-Nearest Neighbours\n", + "4. Classification and Regression Trees\n", + "5. Learning Vector Quantization" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Using Naive Bayes and all the features" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "test_size = 0.35 \n", + "\n", + "kfold = KFold(n_splits=10) #spliiting my data into 10 folds \n", + "\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size, random_state=42) #random_state of 42 for reproducibility\n", + "\n", + "model = GaussianNB() #calling out the prediction algorithm\n", + "results = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\n", + "print(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n", + "\n", + "\n", + "model.fit(X,Y)\n", + "output = model.predict(Test.values) #testing the model on the test_set (Test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "maria2_bayes = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\n", + "maria2_bayes.columns = ['CLASS'] #renaming the output column to 'CLASS'\n", + "maria2_bayes.index.name = \"Index\" #naming the index column as 'Index'\n", + "maria2_bayes['CLASS']=maria2_bayes['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\n", + "maria2_bayes.to_csv(\"maria2_bayes.csv\") #changing my output file as a 'csv' file\n", + "\n", + "\n", + "print(maria2_bayes['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\n", + "print('False: ',maria2_bayes.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\n", + "print('True: ',maria2_bayes.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Support Vector Machines algorithm using all features" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "kfold = KFold(n_splits=10) #spliiting my data into 10 folds\n", + "\n", + "model = SVC() #calling out the prediction algorithm\n", + "scoring = 'acuracy'\n", + "results = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\n", + "print(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n", + "\n", + "model.fit(X, Y)\n", + "output = model.predict(Test.values) #testing the model on the test_set (Test.values)\n", + "\n", + "mcc = matthews_corrcoef(model.predict(X), Y)\n", + "print('MCC: ',mcc)\n", + "\n", + "maria_svc = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\n", + "maria_svc.columns = ['CLASS'] #renaming the output column to 'CLASS'\n", + "maria_svc.index.name = 'Index' #naming the index column as 'Index'\n", + "maria_svc['CLASS'] = maria_svc['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\n", + "\n", + "maria_svc.to_csv('maria_svc.csv') #changing my output file as a 'csv' file\n", + "\n", + "print(maria_svc['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\n", + "print('False: ',maria_svc.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\n", + "print('True: ',maria_svc.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Applying Classification and Regression Trees" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.tree import DecisionTreeClassifier\n", + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "kfold = KFold(n_splits=10, random_state=42) #spliiting my data into 10 folds and random_state of 42 for reproducibility\n", + "model = DecisionTreeClassifier() #calling out the prediction algorithm\n", + "results = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\n", + "print(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n", + "\n", + "\n", + "model.fit(X,Y)\n", + "output = model.predict(Test.values) #testing the model on the test_set (Test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "maria_tree = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\n", + "maria_tree.columns = ['CLASS'] #renaming the output column to 'CLASS'\n", + "maria_tree.index.name = \"Index\" #naming the index column as 'Index'\n", + "maria_tree['CLASS']=maria_tree['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\n", + "maria_tree.to_csv(\"maria_tree.csv\") #changing my output file as a 'csv' file\n", + "\n", + "\n", + "print(maria_tree['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\n", + "print('False: ',maria_tree.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\n", + "print('True: ',maria_tree.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# K-Nearest Neighbours" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "\n", + "kfold = KFold(n_splits=10, random_state=42) #spliiting my data into 10 folds and random_state of 42 for reproducibility\n", + "model = KNeighborsClassifier() #calling out the prediction algorithm\n", + "results = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\n", + "print(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n", + "\n", + "model.fit(X,Y) \n", + "output = model.predict(Test.values) #testing the model on the test_set (Test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "maria_knn = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\n", + "maria_knn.columns = ['CLASS'] #renaming the output column to 'CLASS' \n", + "maria_knn.index.name = \"Index\" #naming the index column as 'Index'\n", + "maria_knn['CLASS']=maria_knn['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\n", + "maria_knn.to_csv(\"maria_knn.csv\") #changing my output file as a 'csv' file\n", + "\n", + "\n", + "print(maria_knn['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\n", + "print('False: ',maria_knn.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\n", + "print('True: ',maria_knn.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Esemble Algorithms\n", + "1. Boosting and Adaboost\n", + "2. Bagging and Random forest" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Applying Adaboost " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "array = Train.values\n", + "\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "\n", + "kfold = KFold(n_splits=10, random_state=42)\n", + "\n", + "model = AdaBoostClassifier(n_estimators=200, random_state=42) \n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "\n", + "print(results.mean())\n", + "\n", + "\n", + "test_set = Test.values\n", + "model.fit(X, Y)\n", + "output = model.predict(test_set)\n", + "\n", + "mcc = matthews_corrcoef(model.predict(X), Y)\n", + "print('MCC: ',mcc)\n", + "\n", + "maria_AB= pd.DataFrame(output)\n", + "maria_AB.columns = ['CLASS']\n", + "maria_AB.index.name = 'Index'\n", + "maria_AB['CLASS'] = maria_AB['CLASS'].map({0.0:False, 1.0:True})\n", + "\n", + "maria_AB.to_csv('maria_AB.csv')\n", + "\n", + "print(maria_AB['CLASS'].unique())\n", + "print('False: ',maria_AB.groupby('CLASS').size()[0].sum())\n", + "print('True: ',maria_AB.groupby('CLASS').size()[1].sum())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Applying Gradient Boosting Classifier" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "array = Train.values\n", + "\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "\n", + "#num_trees = 200\n", + "#seed =42\n", + "\n", + "kfold = KFold(n_splits=10, random_state=42)\n", + "model = GradientBoostingClassifier(n_estimators=200, random_state=42)\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(results.mean())\n", + "\n", + "model.fit(X,Y) \n", + "output = model.predict(Test.values) #testing the model on the test_set (Test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "maria_GBC = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\n", + "maria_GBC.columns = ['CLASS'] #renaming the output column to 'CLASS' \n", + "maria_GBC.index.name = \"Index\" #naming the index column as 'Index'\n", + "maria_GBC['CLASS']=maria_GBC['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\n", + "maria_GBC.to_csv(\"maria_GBC.csv\") #changing my output file as a 'csv' file\n", + "\n", + "\n", + "print(maria_GBC['CLASS'].unique()) #checking out the unique instances in the \n", + "print('False: ',maria_GBC.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\n", + "print('True: ',maria_GBC.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Using Stochastic Gradient Boosting Classification" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "\n", + "kfold = KFold(n_splits=10, random_state=42)\n", + "model = XGBClassifier(n_estimators=200, random_state=42)\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(results.mean())\n", + "\n", + "model.fit(X,Y) \n", + "output = model.predict(Test.values) #testing the model on the test_set (Test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "maria_XGB = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\n", + "maria_XGB.columns = ['CLASS'] #renaming the output column to 'CLASS' \n", + "maria_XGB.index.name = \"Index\" #naming the index column as 'Index'\n", + "maria_XGB['CLASS']=maria_XGB['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\n", + "maria_XGB.to_csv(\"maria_XGB.csv\") #changing my output file as a 'csv' file\n", + "\n", + "\n", + "print(maria_GBC['CLASS'].unique()) #checking out the unique instances in the \n", + "print('False: ',maria_XGB.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\n", + "print('True: ',maria_XGB.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Using Extra Trees Classifier" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "array = Train.values\n", + "\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "\n", + "kfold = KFold(n_splits=10, random_state=42)\n", + "model = ExtraTreesClassifier(n_estimators=200) # (max_features=11)\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(results.mean())\n", + " \n", + "model.fit(X,Y) \n", + "output = model.predict(Test.values) #testing the model on the test_set (Test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "maria_ETX = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\n", + "maria_ETX.columns = ['CLASS'] #renaming the output column to 'CLASS' \n", + "maria_ETX.index.name = \"Index\" #naming the index column as 'Index'\n", + "maria_ETX['CLASS']=maria_ETX['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\n", + "maria_ETX.to_csv(\"maria_ETX.csv\") #changing my output file as a 'csv' file\n", + "\n", + "\n", + "print(maria_ETX['CLASS'].unique()) #checking out the unique instances in the \n", + "print('False: ',maria_ETX.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\n", + "print('True: ',maria_ETX.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# CONCLUSION\n", + "## From the algorithm comparisons and my prediction scores, Naive Bayes algorithm performed the best.\n", + "## I think this is because the data was following a Gaussian distribution(normally distributed) as seen earlier from the density subplots." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# REFERENCES\n", + "1. https://realpython.com/logistic-regression-python/\n", + "2. https://www.tutorialspoint.com/machine_learning_with_python/machine_learning_with_python_extra_trees.htm\n", + "3. https://stackabuse.com/gradient-boosting-classifiers-in-python-with-scikit-learn/\n", + "4. https://machinelearningmastery.com/stochastic-gradient-boosting-xgboost-scikit-learn-python/\n", + "5. https://machinelearningmastery.com/stochastic-gradient-boosting-xgboost-scikit-learn-python/\n", + "6. https://machinelearningmastery.com/compare-machine-learning-algorithms-python-scikit-learn/\n", + "7. https://machinelearningmastery.com/master-machine-learning-algorithms/\n", + "8. https://machinelearningmastery.com/compare-machine-learning-algorithms-python-scikit-learn/\n", + "9. https://github.com/search?q=data-analysis-and-visualization-with-python&type=Repositories\n", + "10. https://stackabuse.com/applying-filter-methods-in-python-for-feature-selection/\n", + "11. https://towardsdatascience.com/decision-tree-in-machine-learning-e380942a4c96\n", + "12. https://machinelearningmastery.com/compare-machine-learning-algorithms-python-scikit-learn/" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", 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"# Ace_class Kaggle assignment_1" + ] + }, + { + "cell_type": "raw", + "metadata": { + "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", + "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" + }, + "source": [ + "# This Python 3 environment comes with many helpful analytics libraries installed\n", + "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", + "# For example, here's several helpful packages to load in \n", + "\n", + "import numpy as np # linear algebra\n", + "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", + "\n", + "# Input data files are available in the \"../input/\" directory.\n", + "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", + "\n", + "import os\n", + "for dirname, _, filenames in os.walk('/kaggle/input'):\n", + " for filename in filenames:\n", + " print(os.path.join(dirname, filename))\n", + "\n", + "# Any results you write to the current directory are saved as output." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Importing some of the needed packages and libraries" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from matplotlib import pyplot\n", + "import seaborn as sns\n", + "\n", + "from sklearn.model_selection import KFold\n", + "from pandas import read_csv\n", + "from sklearn.metrics import confusion_matrix\n", + "from sklearn.metrics import classification_report\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.model_selection import train_test_split\n", + "\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "from sklearn.neighbors import KNeighborsClassifier\n", + "from sklearn.naive_bayes import GaussianNB\n", + "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", + "from sklearn.svm import SVC\n", + "from sklearn.ensemble import AdaBoostClassifier\n", + "from sklearn.ensemble import GradientBoostingClassifier\n", + "from sklearn.ensemble import ExtraTreesClassifier\n", + "from xgboost import XGBClassifier\n", + "from sklearn.ensemble import RandomForestClassifier\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Description of Libraries used.\n", + "* Pandas is a library in Python for data manipulation and analysis. It offers data structures and operations for manipulating numerical tables and time series.\n", + "* Matplotlib is a plotting library for the Python.\n", + "* Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics.\n", + "* K-Fold cross validation is where a given data set is split into a K number of sections/folds where each fold is used as a testing set at some point.\n", + "* A confusion matrix is a table that is often used to describe the performance of a classification model on a set of test data for which the true values are known.\n", + "* In Train/Test Split the data we use is usually split into training data and test data. The training set contains a known output and the model learns on this data in order to be generalized to other data later on\n", + "* Logistic Regression is used for classification problems, it is a predictive analysis algorithm and based on the concept of probability.\n", + "* A decision tree is a flowchart-like tree structure where an internal node represents feature(attribute), the branch represents a decision rule, and each leaf node represents the outcome.\n", + "* KNeighbours Classifier is a non-parametric algorithm whose purpose is to use a database in which the data points are separated into several classes to predict the classification of a new sample point.\n", + "* The Naive Bayes is a classification algorithm that is suitable for binary and multiclass classification. It performs well in cases of categorical input variables compared to numerical variables. \n", + "* The linear Discriminant analysis estimates the probability that a new set of inputs belongs to every class.\n", + "* SVC (Support Vector Classifier) is to fit the data you provide, returning a \"best fit\" hyperplane that divides, or categorizes your data.\n", + "* The basic concept behind Adaboost is to set the weights of classifiers and training the data sample in each iteration such that it ensures the accurate predictions of unusual observations.\n", + "* AdaBoost works by weighting the observations, putting more weight on difficult to classify instances and less on those already handled well.\n", + "* ExtraTreesClassifier, like RandomForest, randomizes certain decisions and subsets of data to minimize over-learning from the data and overfitting." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> *Now i need to get rid of some unnecessary warnings by ignoring them*" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "#To avoid unnecessary warnings, I will ignore them in the code below\n", + "import warnings\n", + "warnings.filterwarnings('ignore')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Loading the datasets \n", + "### There are two datasets given; \n", + "1. AMP_TrainSet.csv and \n", + "2. Test.csv " + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "_cell_guid": "", + "_uuid": "" + }, + "outputs": [], + "source": [ + "#Loading the datasets, \n", + "\n", + "Train = pd.read_csv(\"../Data/AMP_TrainSet.csv\")\n", + "Test = pd.read_csv(\"../Data/Test.csv\")\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### For training the model, I will first use the training set which I will further split into the train and validation set. \n", + "\n", + "
\n", + " @atwine: Did not explain why they are splitting, I need to see why they are doing this.\n", + "
\n", + "### Then I will test the model on the Test set provided to gauge its performance." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Exploring my data\n", + "## Exploring data helps one understand what kind of data is given. That is to say knowing how much data it is, the shape, type, dimensions, missing values, data summary, correlation of attributes among others as am going to do in the following steps." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#here, am trying to find the type of data\n", + "type(Train)\n", + "type(Test)\n", + "Train.dtypes, Test.dtypes" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# checking the dimensions of the data\n", + "# this retuns the number of rows and columns in the data\n", + "\n", + "Train.shape, Test.shape\n", + "\n", + "#this helps to know how big the data is in terms of rows and columns.\n", + "#also from here I can tell which data is labeled" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Data description\n", + ">For now, I will focus more on the train dataset because its what I will use to train the model " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#getting a description of the train dataset\n", + "#description gives a summary of the data.\n", + "\n", + "Train.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#looking at the first 5 entries of my data\n", + "Train.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Class Distribution\n", + "> From the Train dataset, i see there is an extra 'CLASS' column which will be my validation set.\n", + "### I need to know how this class is distributed to guide me on what to do with it." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#to see the class distribution, I will plot a bar graph\n", + "Train.groupby('CLASS').size().plot(kind='bar')\n", + "pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> I would like to know how many instaces i have for each class" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#getting the number of instances in each class\n", + "Train.groupby('CLASS').size()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### There are 1519 intances for each class which is proof for even distribution.\n", + "### From the above barplot and class instances, I can see that the classes are evenly distributed so no need to use smote." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Data Visualisation\n", + "### Data visualization is the technique to present the data in a pictorial or graphical format. It enables one to analyze data visually. The data in a graphical format allows identification of new trends and patterns easily.\n", + "### Visualisation identifies the relationship between data points and variables." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Density plots" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> I chose to use density plots because they are better at determing the distribution shape as they are not affected by the number of bins as is the case with Histograms." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#now plotting density subplots\n", + "#setting the figsize to 12 so that my graphs are not congested\n", + "Train.plot(kind='density', subplots = True, layout=(3,4), sharex= False, sharey= False, figsize=(12,12))\n", + "plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> From the above density subpots, I can see that most of the data follows a Gaussian distribution given some of the characteristics such as bell shaped curves and graphs being symmetrical about the mean." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Box and whisker plots\n", + "> A box plot is a type of graph that displays a summary of a large amount of data in terms of the median, upper quartile, lower quartile, minimum and maximum data values.\n", + "\n", + "> It handles large data easily, gives a clear summary and displays outliers." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#plotting a box and whisker graph\n", + "#setting the figsize to 10 so that the plots are not congested.\n", + "Train.plot(kind='box', subplots = True, layout=(3,4), sharex= False, sharey= False, figsize=(10,10))\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Looking at the correlation of the data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> Correlation is the relationship between two variables. The commonly used method is Pearson's correlation coefficient. It assumes a normal distribution of the attributes involved.\n", + "\n", + "> -1 shows full negative correlation, \n", + "\n", + "> +1 shows full negative correlation and \n", + "\n", + "> 0 shows no correlation at all." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#first I will checkfor the pairwise correlation of the attributes.\n", + "Train.corr(method='pearson')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Then now am reviewing the inter-correlation of attributes using heatmap\n", + "#graphical representation\n", + "plt.figure(figsize=(6,6))\n", + "sns.heatmap(Train.corr(method='pearson'))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Ill also check the correlation in regards to the 'CLASS' attribute\n", + "Train.corr(method='pearson')['CLASS']" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Skewnwess of the data\n", + "> knowing data skewness allows one to perform data preparation and improve a model\n", + "\n", + "> If Skewness value lies above +1 or below -1 then the data is highly skewed. \n", + "\n", + "> If skewness value lies between +0.5 and -0.5 then the data ids moderately skewed.\n", + "\n", + "> If skewness is 0 then data is symmetrical" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Checking out skewness of data\n", + "Train.skew().plot(kind='bar')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Comparing Machine Learning Algorithms\n", + "> This helps to choose the best model for the problem at hand.\n", + "\n", + "> Using resampling methods like cross validation, gives an estimate for how accurate each model may be on unseen data.\n", + "\n", + "> It is important to ensure that each algorithm is evaluated in the same way on the same data to avoid bias." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#comparing different models to from which ill choose.\n", + "\n", + "\n", + "# load dataset\n", + "\n", + "array = Train.values\n", + "\n", + "#split the dataset \n", + "X = array[:,0:11] #X = Train.drop(columns=['CLASS'])\n", + "Y = array[:,11] #Y = Train['CLASS']\n", + "\n", + "# preparing models and adding them to a list\n", + "models = []\n", + "models.append(('LR', LogisticRegression()))\n", + "models.append(('LDA', LinearDiscriminantAnalysis()))\n", + "models.append(('KNN', KNeighborsClassifier()))\n", + "models.append(('CART', DecisionTreeClassifier()))\n", + "models.append(('NB', GaussianNB()))\n", + "models.append(('SVM', SVC()))\n", + "models.append(('AB', AdaBoostClassifier()))\n", + "models.append(('GBC', GradientBoostingClassifier()))\n", + "models.append(('EXT', ExtraTreesClassifier()))\n", + "models.append(('RTC', RandomForestClassifier()))\n", + "#models.append(('XGB', XGBClassifier)) \n", + "#am commenting out XGB it does not seem to be a scikit-learn estimator as it does not implement a 'get_params' methods.\n", + "\n", + "# evaluating each model in turn\n", + "results = []\n", + "names = []\n", + "\n", + "for name, model in models:\n", + " kfold = KFold(n_splits=50, random_state=42)\n", + " cv_results = cross_val_score(model, X, Y, cv=kfold, scoring='accuracy')\n", + " results.append(cv_results)\n", + " names.append(name)\n", + " msg = (name, cv_results.mean(), cv_results.std())\n", + " print(msg)\n", + "\n", + "# boxplot algorithm comparison\n", + "fig = pyplot.figure()\n", + "fig.suptitle('Algorithm Comparison')\n", + "ax = fig.add_subplot(111)\n", + "pyplot.boxplot(results)\n", + "ax.set_xticklabels(names)\n", + "pyplot.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> ## From the above algorithm comparison, I can see that Naive Bayes(NB), ExtraTreesClassifiers(EXT) and RandomForestClassifiers(RTC) are some of the best performing algorithms. \n", + "> ## Am yet to find out the overall best valgorithm after prediction on the Test set" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Feature selection \n", + "## Using recursive feature elimination\n", + "> Sometimes, you may asses a dataset and find out that you do not need to use all the given features. This can be because some of them are highly correlates or they are not in any way helpful in developing the model.\n", + "* It is therefore important to get rid of some features where applicable.\n", + "\n", + "> For this data, I will use Recursive Feature Elimination(RFE)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#feature selection using RFE\n", + "#first i will start with choosing 4 features\n", + "from sklearn.feature_selection import RFE\n", + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "# feature extraction\n", + "model = LogisticRegression()\n", + "rfe = RFE(model, 4)\n", + "fit = rfe.fit(X, Y)\n", + "print(\"Num Features: \", fit.n_features_)\n", + "print(\"Selected Features:\", fit.support_)\n", + "print(\"Feature Ranking: \", fit.ranking_)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Calling out the column names so I can know which features am going to drop from RFE\n", + "Train.columns" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Using Feature importance" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.ensemble import ExtraTreesClassifier\n", + "\n", + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "# feature extraction\n", + "model = ExtraTreesClassifier()\n", + "model.fit(X, Y)\n", + "print(model.feature_importances_)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## If am to use 4 features and drop the rest\n", + "> I will assign the new dataset a variable 'New_Train4' after choosing the 4 features and dropping the rest." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# I will call the new Train data with selected features New_Train4.\n", + "Train\n", + "New_Train4 = Train.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#dropping the same features in the test dataset\n", + "New_Test4 = Test.drop(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_DAYM780201', 'FULL_GEOR030101', 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112'], axis =1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#viewing the selected features\n", + "New_Train4.columns" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#now splitting data\n", + "#array = New_Train.values\n", + "X = New_Train4.values[:,0:4]\n", + "Y = New_Train4.values[:,4]\n", + "from sklearn.model_selection import train_test_split\n", + "X_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size=0.2, random_state=42)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# also train and test the model on Matthews correlation coefficient.\n", + "from sklearn.metrics import matthews_corrcoef\n", + "\n", + "GS = GaussianNB()\n", + "GS.fit(X_Train,Y_Train)\n", + "pred = GS.predict(X_Test)\n", + "\n", + "print(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Using four features gives me a very low MCC and low overall score.\n", + "## I'll therefore consider using 8 features and see what score I get." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.feature_selection import RFE\n", + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "# feature extraction\n", + "model = LogisticRegression()\n", + "rfe = RFE(model, 8)\n", + "fit = rfe.fit(X, Y)\n", + "print(\"Num Features: \", fit.n_features_)\n", + "print(\"Selected Features:\", fit.support_)\n", + "print(\"Feature Ranking: \", fit.ranking_)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# I will call the new Train data with selected features New_Train8.\n", + "Train\n", + "New_Train8 = Train.drop(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'AS_DAYM780201'], axis =1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#dropping the same features in the test dataset\n", + "New_Test8 = Test.drop(['FULL_AcidicMolPerc', 'FULL_DAYM780201', 'AS_DAYM780201'], axis =1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#now splitting data\n", + "#array = New_Train.values\n", + "\n", + "\n", + "X = New_Train8.values[:,0:8]\n", + "Y = New_Train8.values[:,8]\n", + "from sklearn.model_selection import train_test_split\n", + "X_Train, X_Test, Y_Train, Y_Test = train_test_split(X, Y, test_size=0.2, random_state=42)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#now creating a model and training it on 8 features\n", + "model = LogisticRegression(solver='liblinear', C=0.05, multi_class='ovr', random_state=30)\n", + "model.fit(X_Train, Y_Train)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "X_Train, X_Test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2,\n", + "random_state=42)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.metrics import matthews_corrcoef\n", + "\n", + "nv = GaussianNB()\n", + "nv.fit(X_Train,Y_Train)\n", + "pred = nv.predict(X_Test)\n", + "\n", + "print(\"The result is: \",np.round(matthews_corrcoef(Y_Test,pred) *100,2),\" Mathew's Coef\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Standardising data\n", + "> This is useful to transform attributes with a Gaussian distribution and it workd better with rescaled data(also known as normalistaion where attributes are scaled into a range between 0 and 1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Below are some of the algorithms I will be using;" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# LINEAR ALGORITHMS\n", + "1. Linear Regression\n", + "2. Logistic Regression\n", + "3. Linear Discriminant Analysis" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Logistic Regression using 8 features" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# here am using a dataset 'New_Train8' with 8 selected features\n", + "array = New_Train8.values\n", + "X = array[:,0:8]\n", + "Y = array[:,8]\n", + "\n", + "kfold = KFold(n_splits=10, random_state=42) #spliiting my data into 10 folds and random_state of 42 for reproducibility\n", + "model = LogisticRegression() #calling out the prediction algorithm\n", + "results = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\n", + "print(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n", + "\n", + "model.fit(X,Y)\n", + "output = model.predict(New_Test8.values) #testing the model on the test_set (Test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "maria_logistic = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\n", + "maria_logistic.columns = ['CLASS'] #renaming the output column to 'CLASS'\n", + "maria_logistic.index.name = \"Index\" #naming the index column as 'Index'\n", + "maria_logistic['CLASS']=maria_logistic['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\n", + "maria_logistic.to_csv(\"maria_logistic.csv\") #changing my output file as a 'csv' file\n", + "\n", + "print(maria_logistic['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\n", + "print('False: ',maria_logistic.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\n", + "print('True: ',maria_logistic.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# NOTE\n", + "> I have noticed that for this particular dataset, the more I drop features, the prediction scores also keep decreasing.\n", + "\n", + "> With 4 features selected, the score was low, with 8 features, the score improved and with all features, the prediction score was high.\n", + "\n", + "> I therefore decided to work with all the features." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Applying Linear Dicriminant Analysis (LDA) using all features " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "num_folds = 10\n", + "kfold = KFold(n_splits=10, random_state=42) #spliiting my data into 10 folds and random_state of 42 for reproducibility\n", + "model = LinearDiscriminantAnalysis() #calling out the prediction algorithm\n", + "results = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\n", + "print(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n", + "\n", + "model.fit(X,Y)\n", + "output = model.predict(Test.values) #testing the model on the test_set (Test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "maria_LDA = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\n", + "maria_LDA.columns = ['CLASS'] #renaming the output column to 'CLASS'\n", + "maria_LDA.index.name = \"Index\" #naming the index column as 'Index'\n", + "maria_LDA['CLASS']=maria_LDA['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\n", + "maria_LDA.to_csv(\"maria_LDA.csv\") #changing my output file as a 'csv' file\n", + "\n", + "print(maria_LDA['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\n", + "print('False: ',maria_LDA.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\n", + "print('True: ',maria_LDA.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# NON LINEAR ALGORITHMS\n", + "1. Naive Bayes\n", + "2. Support Vector Machines\n", + "3. K-Nearest Neighbours\n", + "4. Classification and Regression Trees\n", + "5. Learning Vector Quantization" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Using Naive Bayes and all the features" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "test_size = 0.35 \n", + "\n", + "kfold = KFold(n_splits=10) #spliiting my data into 10 folds \n", + "\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size, random_state=42) #random_state of 42 for reproducibility\n", + "\n", + "model = GaussianNB() #calling out the prediction algorithm\n", + "results = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\n", + "print(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n", + "\n", + "\n", + "model.fit(X,Y)\n", + "output = model.predict(Test.values) #testing the model on the test_set (Test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "maria2_bayes = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\n", + "maria2_bayes.columns = ['CLASS'] #renaming the output column to 'CLASS'\n", + "maria2_bayes.index.name = \"Index\" #naming the index column as 'Index'\n", + "maria2_bayes['CLASS']=maria2_bayes['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\n", + "maria2_bayes.to_csv(\"maria2_bayes.csv\") #changing my output file as a 'csv' file\n", + "\n", + "\n", + "print(maria2_bayes['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\n", + "print('False: ',maria2_bayes.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\n", + "print('True: ',maria2_bayes.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Support Vector Machines algorithm using all features" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "kfold = KFold(n_splits=10) #spliiting my data into 10 folds\n", + "\n", + "model = SVC() #calling out the prediction algorithm\n", + "scoring = 'acuracy'\n", + "results = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\n", + "print(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n", + "\n", + "model.fit(X, Y)\n", + "output = model.predict(Test.values) #testing the model on the test_set (Test.values)\n", + "\n", + "mcc = matthews_corrcoef(model.predict(X), Y)\n", + "print('MCC: ',mcc)\n", + "\n", + "maria_svc = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\n", + "maria_svc.columns = ['CLASS'] #renaming the output column to 'CLASS'\n", + "maria_svc.index.name = 'Index' #naming the index column as 'Index'\n", + "maria_svc['CLASS'] = maria_svc['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\n", + "\n", + "maria_svc.to_csv('maria_svc.csv') #changing my output file as a 'csv' file\n", + "\n", + "print(maria_svc['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\n", + "print('False: ',maria_svc.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\n", + "print('True: ',maria_svc.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Applying Classification and Regression Trees" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.tree import DecisionTreeClassifier\n", + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "kfold = KFold(n_splits=10, random_state=42) #spliiting my data into 10 folds and random_state of 42 for reproducibility\n", + "model = DecisionTreeClassifier() #calling out the prediction algorithm\n", + "results = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\n", + "print(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n", + "\n", + "\n", + "model.fit(X,Y)\n", + "output = model.predict(Test.values) #testing the model on the test_set (Test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "maria_tree = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\n", + "maria_tree.columns = ['CLASS'] #renaming the output column to 'CLASS'\n", + "maria_tree.index.name = \"Index\" #naming the index column as 'Index'\n", + "maria_tree['CLASS']=maria_tree['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\n", + "maria_tree.to_csv(\"maria_tree.csv\") #changing my output file as a 'csv' file\n", + "\n", + "\n", + "print(maria_tree['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\n", + "print('False: ',maria_tree.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\n", + "print('True: ',maria_tree.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# K-Nearest Neighbours" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "\n", + "kfold = KFold(n_splits=10, random_state=42) #spliiting my data into 10 folds and random_state of 42 for reproducibility\n", + "model = KNeighborsClassifier() #calling out the prediction algorithm\n", + "results = cross_val_score(model, X, Y, cv=kfold) #estimating the model on new data and assigning it to results variable\n", + "print(results.mean()) #getting the mean of the accuracy scores from cross validation scores\n", + "\n", + "model.fit(X,Y) \n", + "output = model.predict(Test.values) #testing the model on the test_set (Test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "maria_knn = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\n", + "maria_knn.columns = ['CLASS'] #renaming the output column to 'CLASS' \n", + "maria_knn.index.name = \"Index\" #naming the index column as 'Index'\n", + "maria_knn['CLASS']=maria_knn['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\n", + "maria_knn.to_csv(\"maria_knn.csv\") #changing my output file as a 'csv' file\n", + "\n", + "\n", + "print(maria_knn['CLASS'].unique()) #checking out the unique instances in the 'CLASS' column\n", + "print('False: ',maria_knn.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\n", + "print('True: ',maria_knn.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Esemble Algorithms\n", + "1. Boosting and Adaboost\n", + "2. Bagging and Random forest" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Applying Adaboost " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "array = Train.values\n", + "\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "\n", + "kfold = KFold(n_splits=10, random_state=42)\n", + "\n", + "model = AdaBoostClassifier(n_estimators=200, random_state=42) \n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "\n", + "print(results.mean())\n", + "\n", + "\n", + "test_set = Test.values\n", + "model.fit(X, Y)\n", + "output = model.predict(test_set)\n", + "\n", + "mcc = matthews_corrcoef(model.predict(X), Y)\n", + "print('MCC: ',mcc)\n", + "\n", + "maria_AB= pd.DataFrame(output)\n", + "maria_AB.columns = ['CLASS']\n", + "maria_AB.index.name = 'Index'\n", + "maria_AB['CLASS'] = maria_AB['CLASS'].map({0.0:False, 1.0:True})\n", + "\n", + "maria_AB.to_csv('maria_AB.csv')\n", + "\n", + "print(maria_AB['CLASS'].unique())\n", + "print('False: ',maria_AB.groupby('CLASS').size()[0].sum())\n", + "print('True: ',maria_AB.groupby('CLASS').size()[1].sum())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Applying Gradient Boosting Classifier" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "array = Train.values\n", + "\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "\n", + "#num_trees = 200\n", + "#seed =42\n", + "\n", + "kfold = KFold(n_splits=10, random_state=42)\n", + "model = GradientBoostingClassifier(n_estimators=200, random_state=42)\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(results.mean())\n", + "\n", + "model.fit(X,Y) \n", + "output = model.predict(Test.values) #testing the model on the test_set (Test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "maria_GBC = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\n", + "maria_GBC.columns = ['CLASS'] #renaming the output column to 'CLASS' \n", + "maria_GBC.index.name = \"Index\" #naming the index column as 'Index'\n", + "maria_GBC['CLASS']=maria_GBC['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\n", + "maria_GBC.to_csv(\"maria_GBC.csv\") #changing my output file as a 'csv' file\n", + "\n", + "\n", + "print(maria_GBC['CLASS'].unique()) #checking out the unique instances in the \n", + "print('False: ',maria_GBC.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\n", + "print('True: ',maria_GBC.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Using Stochastic Gradient Boosting Classification" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "\n", + "kfold = KFold(n_splits=10, random_state=42)\n", + "model = XGBClassifier(n_estimators=200, random_state=42)\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(results.mean())\n", + "\n", + "model.fit(X,Y) \n", + "output = model.predict(Test.values) #testing the model on the test_set (Test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "maria_XGB = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\n", + "maria_XGB.columns = ['CLASS'] #renaming the output column to 'CLASS' \n", + "maria_XGB.index.name = \"Index\" #naming the index column as 'Index'\n", + "maria_XGB['CLASS']=maria_XGB['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\n", + "maria_XGB.to_csv(\"maria_XGB.csv\") #changing my output file as a 'csv' file\n", + "\n", + "\n", + "print(maria_GBC['CLASS'].unique()) #checking out the unique instances in the \n", + "print('False: ',maria_XGB.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\n", + "print('True: ',maria_XGB.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Using Extra Trees Classifier" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "array = Train.values\n", + "\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "\n", + "kfold = KFold(n_splits=10, random_state=42)\n", + "model = ExtraTreesClassifier(n_estimators=200) # (max_features=11)\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(results.mean())\n", + " \n", + "model.fit(X,Y) \n", + "output = model.predict(Test.values) #testing the model on the test_set (Test.values)\n", + "\n", + "from sklearn.metrics import matthews_corrcoef\n", + "mcc = matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',mcc)\n", + " \n", + "maria_ETX = pd.DataFrame(output) #here we are converting the array into a pandas dataframe which will give a single column\n", + "maria_ETX.columns = ['CLASS'] #renaming the output column to 'CLASS' \n", + "maria_ETX.index.name = \"Index\" #naming the index column as 'Index'\n", + "maria_ETX['CLASS']=maria_ETX['CLASS'].map({0.0:False, 1.0:True}) #converting '0.0' to' False' and '1.0' to 'True'\n", + "maria_ETX.to_csv(\"maria_ETX.csv\") #changing my output file as a 'csv' file\n", + "\n", + "\n", + "print(maria_ETX['CLASS'].unique()) #checking out the unique instances in the \n", + "print('False: ',maria_ETX.groupby('CLASS').size()[0].sum()) #summing up the '0' instances in the 'CLASS' column\n", + "print('True: ',maria_ETX.groupby('CLASS').size()[1].sum()) #summing up the '1' instances in the 'CLASS' column " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# CONCLUSION\n", + "## From the algorithm comparisons and my prediction scores, Naive Bayes algorithm performed the best.\n", + "## I think this is because the data was following a Gaussian distribution(normally distributed) as seen earlier from the density subplots." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# REFERENCES\n", + "1. https://realpython.com/logistic-regression-python/\n", + "2. https://www.tutorialspoint.com/machine_learning_with_python/machine_learning_with_python_extra_trees.htm\n", + "3. https://stackabuse.com/gradient-boosting-classifiers-in-python-with-scikit-learn/\n", + "4. https://machinelearningmastery.com/stochastic-gradient-boosting-xgboost-scikit-learn-python/\n", + "5. https://machinelearningmastery.com/stochastic-gradient-boosting-xgboost-scikit-learn-python/\n", + "6. https://machinelearningmastery.com/compare-machine-learning-algorithms-python-scikit-learn/\n", + "7. https://machinelearningmastery.com/master-machine-learning-algorithms/\n", + "8. https://machinelearningmastery.com/compare-machine-learning-algorithms-python-scikit-learn/\n", + "9. https://github.com/search?q=data-analysis-and-visualization-with-python&type=Repositories\n", + "10. https://stackabuse.com/applying-filter-methods-in-python-for-feature-selection/\n", + "11. https://towardsdatascience.com/decision-tree-in-machine-learning-e380942a4c96\n", + "12. https://machinelearningmastery.com/compare-machine-learning-algorithms-python-scikit-learn/" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", 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Colab/MARIA MAGDALENE NAMAGANDA FINAL_UPDATE.ipynb @@ -162,9 +162,43 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(FULL_Charge float64\n", + " FULL_AcidicMolPerc float64\n", + " FULL_AURR980107 float64\n", + " FULL_DAYM780201 float64\n", + " FULL_GEOR030101 float64\n", + " FULL_OOBM850104 float64\n", + " NT_EFC195 int64\n", + " AS_MeanAmphiMoment float64\n", + " AS_DAYM780201 float64\n", + " AS_FUKS010112 float64\n", + " CT_RACS820104 float64\n", + " CLASS int64\n", + " dtype: object, FULL_Charge float64\n", + " FULL_AcidicMolPerc float64\n", + " FULL_AURR980107 float64\n", + " FULL_DAYM780201 float64\n", + " FULL_GEOR030101 float64\n", + " FULL_OOBM850104 float64\n", + " NT_EFC195 int64\n", + " AS_MeanAmphiMoment float64\n", + " AS_DAYM780201 float64\n", + " AS_FUKS010112 float64\n", + " CT_RACS820104 float64\n", + " dtype: object)" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "#here, am trying to find the type of data\n", "type(Train)\n", @@ -174,9 +208,20 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "((3038, 12), (758, 11))" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# checking the dimensions of the data\n", "# this retuns the number of rows and columns in the data\n", @@ -197,9 +242,206 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n", + "0 5.0 0.000 0.951 74.842 \n", + "1 4.0 5.405 0.931 71.595 \n", + "2 5.5 5.405 0.873 73.595 \n", + "3 5.0 4.167 0.895 66.250 \n", + "4 7.5 8.537 0.932 64.720 \n", + "\n", + " FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n", + "0 0.975 -3.663 0 0.282 \n", + "1 0.957 -4.011 1 0.600 \n", + "2 0.961 -2.512 0 0.593 \n", + "3 0.999 -1.362 0 0.614 \n", + "4 0.979 -2.091 0 0.616 \n", + "\n", + " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 CLASS \n", + "0 73.444 5.661 1.041 1 \n", + "1 68.222 6.537 1.453 1 \n", + "2 69.444 4.934 1.722 1 \n", + "3 67.222 4.316 1.382 1 \n", + "4 72.944 4.540 1.539 1 " + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "#looking at the first 5 entries of my data\n", "Train.head()" @@ -228,9 +613,22 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "#to see the class distribution, I will plot a bar graph\n", "Train.groupby('CLASS').size().plot(kind='bar')\n", @@ -246,9 +644,23 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "CLASS\n", + "0 1519\n", + "1 1519\n", + "dtype: int64" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "#getting the number of instances in each class\n", "Train.groupby('CLASS').size()" @@ -287,9 +699,22 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "#now plotting density subplots\n", "#setting the figsize to 12 so that my graphs are not congested\n", @@ -316,9 +741,22 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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FULL_OOBM850104-0.2837580.5133440.4627120.3347780.3191571.000000-0.230561-0.3362970.275640-0.4527690.155304-0.453287
NT_EFC1950.088068-0.143168-0.169540-0.090058-0.230417-0.2305611.0000000.178683-0.0368440.1459240.0808980.260702
AS_MeanAmphiMoment0.355477-0.431590-0.426097-0.408793-0.160269-0.3362970.1786831.000000-0.3223780.0255800.1715240.693552
AS_DAYM780201-0.3653740.4496210.4562600.894191-0.0290850.275640-0.036844-0.3223781.0000000.045562-0.256060-0.437168
AS_FUKS010112-0.0905700.0023340.0329580.0559150.040480-0.4527690.1459240.0255800.0455621.000000-0.4452840.033432
CT_RACS8201040.232929-0.213543-0.403599-0.326792-0.1519350.1553040.0808980.171524-0.256060-0.4452841.0000000.267652
CLASS0.534602-0.598816-0.584111-0.554838-0.260470-0.4532870.2607020.693552-0.4371680.0334320.2676521.000000
\n", + "
" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 \\\n", + "FULL_Charge 1.000000 -0.612996 -0.490977 \n", + "FULL_AcidicMolPerc -0.612996 1.000000 0.794796 \n", + "FULL_AURR980107 -0.490977 0.794796 1.000000 \n", + "FULL_DAYM780201 -0.434603 0.541481 0.548253 \n", + "FULL_GEOR030101 -0.058725 0.115201 0.346139 \n", + "FULL_OOBM850104 -0.283758 0.513344 0.462712 \n", + "NT_EFC195 0.088068 -0.143168 -0.169540 \n", + "AS_MeanAmphiMoment 0.355477 -0.431590 -0.426097 \n", + "AS_DAYM780201 -0.365374 0.449621 0.456260 \n", + "AS_FUKS010112 -0.090570 0.002334 0.032958 \n", + "CT_RACS820104 0.232929 -0.213543 -0.403599 \n", + "CLASS 0.534602 -0.598816 -0.584111 \n", + "\n", + " FULL_DAYM780201 FULL_GEOR030101 FULL_OOBM850104 \\\n", + "FULL_Charge -0.434603 -0.058725 -0.283758 \n", + "FULL_AcidicMolPerc 0.541481 0.115201 0.513344 \n", + "FULL_AURR980107 0.548253 0.346139 0.462712 \n", + "FULL_DAYM780201 1.000000 0.010118 0.334778 \n", + "FULL_GEOR030101 0.010118 1.000000 0.319157 \n", + "FULL_OOBM850104 0.334778 0.319157 1.000000 \n", + "NT_EFC195 -0.090058 -0.230417 -0.230561 \n", + "AS_MeanAmphiMoment -0.408793 -0.160269 -0.336297 \n", + "AS_DAYM780201 0.894191 -0.029085 0.275640 \n", + "AS_FUKS010112 0.055915 0.040480 -0.452769 \n", + "CT_RACS820104 -0.326792 -0.151935 0.155304 \n", + "CLASS -0.554838 -0.260470 -0.453287 \n", + "\n", + " NT_EFC195 AS_MeanAmphiMoment AS_DAYM780201 \\\n", + "FULL_Charge 0.088068 0.355477 -0.365374 \n", + "FULL_AcidicMolPerc -0.143168 -0.431590 0.449621 \n", + "FULL_AURR980107 -0.169540 -0.426097 0.456260 \n", + "FULL_DAYM780201 -0.090058 -0.408793 0.894191 \n", + "FULL_GEOR030101 -0.230417 -0.160269 -0.029085 \n", + "FULL_OOBM850104 -0.230561 -0.336297 0.275640 \n", + "NT_EFC195 1.000000 0.178683 -0.036844 \n", + "AS_MeanAmphiMoment 0.178683 1.000000 -0.322378 \n", + "AS_DAYM780201 -0.036844 -0.322378 1.000000 \n", + "AS_FUKS010112 0.145924 0.025580 0.045562 \n", + "CT_RACS820104 0.080898 0.171524 -0.256060 \n", + "CLASS 0.260702 0.693552 -0.437168 \n", + "\n", + " AS_FUKS010112 CT_RACS820104 CLASS \n", + "FULL_Charge -0.090570 0.232929 0.534602 \n", + "FULL_AcidicMolPerc 0.002334 -0.213543 -0.598816 \n", + "FULL_AURR980107 0.032958 -0.403599 -0.584111 \n", + "FULL_DAYM780201 0.055915 -0.326792 -0.554838 \n", + "FULL_GEOR030101 0.040480 -0.151935 -0.260470 \n", + "FULL_OOBM850104 -0.452769 0.155304 -0.453287 \n", + "NT_EFC195 0.145924 0.080898 0.260702 \n", + "AS_MeanAmphiMoment 0.025580 0.171524 0.693552 \n", + "AS_DAYM780201 0.045562 -0.256060 -0.437168 \n", + "AS_FUKS010112 1.000000 -0.445284 0.033432 \n", + "CT_RACS820104 -0.445284 1.000000 0.267652 \n", + "CLASS 0.033432 0.267652 1.000000 " + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "#first I will checkfor the pairwise correlation of the attributes.\n", "Train.corr(method='pearson')" @@ -358,9 +1079,32 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "#Then now am reviewing the inter-correlation of attributes using heatmap\n", "#graphical representation\n", @@ -370,9 +1114,32 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "FULL_Charge 0.534602\n", + "FULL_AcidicMolPerc -0.598816\n", + "FULL_AURR980107 -0.584111\n", + "FULL_DAYM780201 -0.554838\n", + "FULL_GEOR030101 -0.260470\n", + "FULL_OOBM850104 -0.453287\n", + "NT_EFC195 0.260702\n", + "AS_MeanAmphiMoment 0.693552\n", + "AS_DAYM780201 -0.437168\n", + "AS_FUKS010112 0.033432\n", + "CT_RACS820104 0.267652\n", + "CLASS 1.000000\n", + "Name: CLASS, dtype: float64" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "#Ill also check the correlation in regards to the 'CLASS' attribute\n", "Train.corr(method='pearson')['CLASS']" @@ -394,9 +1161,32 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "#Checking out skewness of data\n", "Train.skew().plot(kind='bar')" @@ -416,9 +1206,38 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('LR', 0.9063005464480876, 0.13577589382538835)\n", + "('LDA', 0.9081202185792349, 0.16200541794052895)\n", + "('KNN', 0.8893770491803281, 0.15039644863318388)\n", + "('CART', 0.8810109289617487, 0.12535175208835309)\n", + "('NB', 0.9150163934426229, 0.06671294103051226)\n", + "('SVM', 0.8977868852459018, 0.16388180621798357)\n", + "('AB', 0.9005573770491805, 0.14889029794369535)\n", + "('GBC', 0.9146939890710383, 0.1271369611553431)\n", + "('EXT', 0.9265300546448089, 0.09354977798111189)\n", + "('RTC', 0.9218852459016393, 0.10656696397955046)\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "#comparing different models to from which ill choose.\n", "\n", @@ -489,9 +1308,19 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Num Features: 4\n", + "Selected Features: [False False True False False True True False False False True]\n", + "Feature Ranking: [3 7 1 6 2 1 1 4 8 5 1]\n" + ] + } + ], "source": [ "#feature selection using RFE\n", "#first i will start with choosing 4 features\n", @@ -512,9 +1341,24 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", + " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", + " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", + " 'CLASS'],\n", + " dtype='object')" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "#Calling out the column names so I can know which features am going to drop from RFE\n", "Train.columns" @@ -529,9 +1373,18 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0.08227437 0.14418508 0.08895859 0.08005117 0.05746269 0.07433544\n", + " 0.03416612 0.30382632 0.05147578 0.03226204 0.0510024 ]\n" + ] + } + ], "source": [ "from sklearn.ensemble import ExtraTreesClassifier\n", "\n", @@ -554,7 +1407,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, "outputs": [], "source": [ @@ -565,7 +1418,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": {}, "outputs": [], "source": [ @@ -575,9 +1428,22 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['FULL_AURR980107', 'FULL_OOBM850104', 'NT_EFC195', 'CT_RACS820104',\n", + " 'CLASS'],\n", + " dtype='object')" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "#viewing the selected features\n", "New_Train4.columns" @@ -585,7 +1451,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "metadata": {}, "outputs": [], "source": [ @@ -599,9 +1465,17 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The result is: 62.28 Mathew's Coef\n" + ] + } + ], "source": [ "# also train and test the model on Matthews correlation coefficient.\n", "from sklearn.metrics import matthews_corrcoef\n", diff --git a/AMP Data Sets/.ipynb_checkpoints/Starter ACE_Assignment-checkpoint.ipynb b/Data/.ipynb_checkpoints/Starter ACE_Assignment-checkpoint.ipynb similarity index 100% rename from AMP Data Sets/.ipynb_checkpoints/Starter ACE_Assignment-checkpoint.ipynb rename to Data/.ipynb_checkpoints/Starter ACE_Assignment-checkpoint.ipynb diff --git a/AMP Data Sets/.ipynb_checkpoints/Untitled-checkpoint.ipynb b/Data/.ipynb_checkpoints/Untitled-checkpoint.ipynb similarity index 100% rename from AMP Data Sets/.ipynb_checkpoints/Untitled-checkpoint.ipynb rename to Data/.ipynb_checkpoints/Untitled-checkpoint.ipynb diff --git a/AMP Data Sets/AMP_TestSet.arff b/Data/AMP_TestSet.arff similarity index 100% rename from AMP Data Sets/AMP_TestSet.arff rename to Data/AMP_TestSet.arff diff --git a/AMP Data Sets/AMP_TestSet.csv b/Data/AMP_TestSet.csv similarity index 100% rename from AMP Data Sets/AMP_TestSet.csv rename to Data/AMP_TestSet.csv diff --git a/AMP Data Sets/AMP_TrainSet.arff b/Data/AMP_TrainSet.arff similarity index 100% rename from AMP Data Sets/AMP_TrainSet.arff rename to Data/AMP_TrainSet.arff diff --git a/AMP Data Sets/AMP_TrainSet.csv b/Data/AMP_TrainSet.csv similarity index 100% rename from AMP Data Sets/AMP_TrainSet.csv rename to Data/AMP_TrainSet.csv diff --git a/AMP Data Sets/Test.csv b/Data/Test.csv similarity index 100% rename from AMP Data Sets/Test.csv rename to Data/Test.csv diff --git a/AMP Data Sets/Untitled.ipynb b/Data/Untitled.ipynb similarity index 100% rename from AMP Data Sets/Untitled.ipynb rename to Data/Untitled.ipynb diff --git a/AMP Data Sets/handin.csv b/Data/handin.csv similarity index 100% rename from AMP Data Sets/handin.csv rename to Data/handin.csv diff --git a/AMP Data Sets/nu_hand.csv b/Data/nu_hand.csv similarity index 100% rename from AMP Data Sets/nu_hand.csv rename to Data/nu_hand.csv diff --git a/AMP Data Sets/nu_handin.csv b/Data/nu_handin.csv similarity index 100% rename from AMP Data Sets/nu_handin.csv rename to Data/nu_handin.csv diff --git a/AMP Data Sets/sample_handin.csv b/Data/sample_handin.csv similarity index 100% rename from AMP Data Sets/sample_handin.csv rename to Data/sample_handin.csv diff --git a/pandas_exercises b/pandas_exercises new file mode 160000 index 0000000..eb62966 --- /dev/null +++ b/pandas_exercises @@ -0,0 +1 @@ +Subproject commit eb629669319f161fbe4b82e8387771ae8b64789d From 9285cc00b651a1f45d77249b6c809b1b82688fa7 Mon Sep 17 00:00:00 2001 From: Atwine Date: Mon, 30 Mar 2020 11:56:04 +0300 Subject: [PATCH 28/29] late submission --- Eva Akurut.final.ipynb | 3365 ++++++++++++++++++++++++++++++++++++++++ Jupiter Marina.ipynb | 1 + 2 files changed, 3366 insertions(+) create mode 100644 Eva Akurut.final.ipynb create mode 100644 Jupiter Marina.ipynb diff --git a/Eva Akurut.final.ipynb b/Eva Akurut.final.ipynb new file mode 100644 index 0000000..8d8e19b --- /dev/null +++ b/Eva Akurut.final.ipynb @@ -0,0 +1,3365 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## ACE_COMPETITION\n", + "#### Eva Akurut\n", + "#### REG Number:2019/HD07/24850U\n", + "\n", + "#### Exploration Data Analysis assignment\n", + "* Import the datasets into the notebook\n", + "* Find out the Dimensions of the data imported\n", + "* Descibe the data using statistics(Descriptive statistics)\n", + "* Looking at how the variables correlate with each other\n", + "* Data Visualisation\n", + "* Preparation of data for Machine Learning\n", + "* Evaluate the Performance of Machine Learning Algorithms with Resampling\n", + "* Spot-Checking Classiffication Algorithms" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", + "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5" + }, + "outputs": [], + "source": [ + "# Importing the tools to use for the assignment\n", + "import numpy as np # linear algebra\n", + "import pandas as pd # data structure analysis\n", + "import matplotlib.pyplot as plt # for visualisation\n", + "import seaborn as sns#\n", + "import warnings\n", + "warnings.filterwarnings('ignore')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 1)Loading the data to be used into my notebook\n", + "The data to be analyzed was read in using the pandas method of pd.read_csv(),\n", + "* Two data sets were loaded in AMP_Trainset.csv \n", + "* Test.csv\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "###Importing the data sets into the notebook using read.csv\n", + "Train=pd.read_csv(\"Data/AMP_TrainSet.csv\")\n", + "Test=pd.read_csv(\"Data/Test.csv\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2)Checking the dimensions of my data\n", + "* Dimensions give a deep insight into the data to be analysed\n", + "* It helps to give sumarry of all the data types present in our data using data.info()function\n", + "* Determines the Number of columns and rows using data.shape()function\n", + "* Finds out if there are missing values in the data using is.null()function\n", + "* The data.head() Funstion gives mre the top 5 rows with all the columns present" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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+ "text/plain": [ + "(FULL_Charge float64\n", + " FULL_AcidicMolPerc float64\n", + " FULL_AURR980107 float64\n", + " FULL_DAYM780201 float64\n", + " FULL_GEOR030101 float64\n", + " FULL_OOBM850104 float64\n", + " NT_EFC195 int64\n", + " AS_MeanAmphiMoment float64\n", + " AS_DAYM780201 float64\n", + " AS_FUKS010112 float64\n", + " CT_RACS820104 float64\n", + " CLASS int64\n", + " dtype: object, FULL_Charge float64\n", + " FULL_AcidicMolPerc float64\n", + " FULL_AURR980107 float64\n", + " FULL_DAYM780201 float64\n", + " FULL_GEOR030101 float64\n", + " FULL_OOBM850104 float64\n", + " NT_EFC195 int64\n", + " AS_MeanAmphiMoment float64\n", + " AS_DAYM780201 float64\n", + " AS_FUKS010112 float64\n", + " CT_RACS820104 float64\n", + " dtype: object)" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Checking the datatype of of my data to determine the class of my data\n", + "Train.dtypes ,Test.dtypes\n" + ] + }, + { + "cell_type": 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False \n", + " 27 False False False \n", + " 28 False False False \n", + " 29 False False False \n", + " .. ... ... ... \n", + " 728 False False False \n", + " 729 False False False \n", + " 730 False False False \n", + " 731 False False False \n", + " 732 False False False \n", + " 733 False False False \n", + " 734 False False False \n", + " 735 False False False \n", + " 736 False False False \n", + " 737 False False False \n", + " 738 False False False \n", + " 739 False False False \n", + " 740 False False False \n", + " 741 False False False \n", + " 742 False False False \n", + " 743 False False False \n", + " 744 False False False \n", + " 745 False False False \n", + " 746 False False False \n", + " 747 False False False \n", + " 748 False False False \n", + " 749 False False False \n", + " 750 False False False \n", + " 751 False False False \n", + " 752 False False False \n", + " 753 False False False \n", + " 754 False False False \n", + " 755 False False False \n", + " 756 False False False \n", + " 757 False False False \n", + " \n", + " [758 rows x 11 columns])" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Verifying if there are no missing values in the data\n", + "Train.isnull(), Test.isnull()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# visualization to check for missing data\n", + "import missingno as msno\n", + "msno.bar(Train)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['FULL_Charge', 'FULL_AcidicMolPerc', 'FULL_AURR980107',\n", + " 'FULL_DAYM780201', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n", + " 'AS_MeanAmphiMoment', 'AS_DAYM780201', 'AS_FUKS010112', 'CT_RACS820104',\n", + " 'CLASS'],\n", + " dtype='object')" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Printing the column names to get to know the names of the columns\n", + "Train.columns" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* In general, both the train and Test datasets have float and intenger data types\n", + "* The Train Data set has 3038 rows and 12 columns\n", + "* The Test Data set has 758 rows plus 11 columns\n", + "* The data has no missing values since the data.info() as well as the isnull() show none missing\n", + "* Having obtained the above results, It shows that i should classify my data using the column not preset in the Test data set \n", + "* There is no need for further data cleaning since we have no missing values, therefore i proceed to the next stage of descriptive stattistics" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 3)Descriptive statistics\n", + "* Descriptive statistics can give you deeper insight into the spread of the data and shape of each attribute/Variable making the data easily readible and creating summaries of our data.\n", + "* This is done using the describe() function on the Pandas DataFrame lists 8 statistical properties of each attribute:-\n", + " * Count-Indicating the number of times the variable was carried out,\n", + " * Mean(or average) which is the sum of all of the data values divided by the number of data values.\n", + " * Standard Deviation which is a measure of the average distance between the values of the data in the set and the mean. If the data values are all similar, then the standard deviation will be low (closer to zero).\n", + " * Minimum Value which the smallest mathematical value in hich the data \n", + " * Maximum Value which is the largest mathematical value in the data \n", + " * 25th Percentile which are the values which are in the 25% range (First quatile)\n", + " * 50th Percentile (Median) which shows the number of values which are either 50% higher or lower\n", + " * 75th Percentile also known as Q3 are the number of values in the 75% range\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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mean2.0602378.5215200.97141073.6687600.994007-2.4329270.08854515.68323373.6508285.9113611.2352550.500000
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\n", + "
" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 FULL_DAYM780201 \\\n", + "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", + "mean 2.060237 8.521520 0.971410 73.668760 \n", + "std 3.819929 7.586652 0.107413 8.527489 \n", + "min -16.000000 0.000000 0.684000 42.750000 \n", + "25% 0.000000 2.516000 0.895000 68.294000 \n", + "50% 2.000000 7.143000 0.963000 74.059500 \n", + "75% 4.000000 13.158000 1.041000 79.343750 \n", + "max 30.000000 46.667000 1.451000 101.682000 \n", + "\n", + " FULL_GEOR030101 FULL_OOBM850104 NT_EFC195 AS_MeanAmphiMoment \\\n", + "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", + "mean 0.994007 -2.432927 0.088545 15.683233 \n", + "std 0.031333 1.707223 0.284133 11.575665 \n", + "min 0.866000 -10.432000 0.000000 0.041000 \n", + "25% 0.974000 -3.606000 0.000000 5.587500 \n", + "50% 0.994000 -2.296500 0.000000 14.988500 \n", + "75% 1.011000 -1.283250 0.000000 26.807750 \n", + "max 1.196000 3.576000 1.000000 51.280000 \n", + "\n", + " AS_DAYM780201 AS_FUKS010112 CT_RACS820104 CLASS \n", + "count 3038.000000 3038.000000 3038.000000 3038.000000 \n", + "mean 73.650828 5.911361 1.235255 0.500000 \n", + "std 9.166092 0.693689 0.210012 0.500082 \n", + "min 42.778000 3.533000 0.785000 0.000000 \n", + "25% 67.556000 5.459250 1.082000 0.000000 \n", + "50% 73.697000 5.925500 1.184000 0.500000 \n", + "75% 79.778000 6.382000 1.351000 1.000000 \n", + "max 103.167000 8.662000 2.192000 1.000000 " + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Getting the spread of my data\n", + "Train.describe()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "*The count values in all the columns are 3038 which corellates with the number of rows\n", + "* The columns are 12\n", + "* The highest mean is in the FULL_DAYM780201 which is 73.668760\n", + "* The column with the lowest min value is FULL_Charge with -16.0\n", + "* The highest deviation is in the AS_MeanAmphiMoment and lowest in FULL_AURR980107" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Splitting my data into by classfication to find out how balanced the through classification\n", + "* A groupby() operation will be used\n", + "* It involves a combination of splitting the object,then anapplication of a function, and combining the results.\n", + "* It entails categorizing identical data into groups." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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SOmLoS1JHHnfX6WvxJHkOg288r2ylPcCOqrp96UYlaSl5pn+YSvIOBj9zEeAr7RFguz90p8ezJG9c6jEczrx65zCV5JvAc6vqp7PqRwK3VtW6pRmZdGBJ7qmqE5Z6HIcrp3cOXz8Hng7cPat+fGuTlkySm/bXBKwY51h6Y+gfvt4CXJnkTh79kbsTgGcCb1qyUUkDK4CXAw/Oqgf4j/EPpx+G/mGqqr6Y5FkMfs56+IPc66vqZ0s3MgmAzwNPqaqvz25Ics34h9MP5/QlqSNevSNJHTH0Jakjhr66luRpSS5L8l9JbkhyRZJnJbllP/2XJZlJcuGs+quSfC3JjUluS/Lnrf7sJNck+XqS25P4S5JaUn6Qq24lCfA5YFtVndVqL+DAlwz+IfBN4LVJzq+qSvIEBj8LfHJV7U5yFLCm9b8YuKiqLm/7/+1D82qkg+OZvnr2B8BPq+of9xaq6kZ+8T7Os20EPgTcA7y41X6NwQnU99o+flxVe+/tfDyDe0Hv3f/NizZ6aQEMffXsecANB9s5yROBlwH/Cmxn8AZAVT3A4A5wdyfZnuT1Sfb+27oIuCrJF5K8NcnyRX0F0jwZ+tLBexVwdVX9EPgMcGaSIwCq6s+A0xj8xtHfAFtb/aPAbwH/ApwKXNumf6QlYeirZ7cCvzuP/huBlyX5NoP/IRwLvHRvY1XdXFUXMZj3/6Oh+n9X1daq2gA8wuB/GNKSMPTVs6uAo5Js3ltI8nxg9eyOSX4d+D3ghKpaU1VrgHOAjUmekuTUoe6/Q/vNoyTr2we9JHkagzeKPYfm5Uhz8xu56lqSpwMfZHDG/yPg2wx+t+g24DtDXd8FnLH3Kp+27THAHQx+z2g78Azgh8APgDdX1VSSDwCvbPsGeH9V/fOhfE3SgRj6ktQRp3ckqSOGviR1xNCXpI4Y+pLUEUNfkjpi6EtSRwx9SeqIoS9JHfl/A81OO47ZVDkAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Train.groupby(\"CLASS\").size().plot(kind=\"bar\", color=(\"green\",\"skyblue\")) " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* According to the results above, the data got split into two equal groups with values that are balancing out\n", + "* There was therefor no need to manipulate the data to become balanced out\n", + "* There will therefore be no alogarithm balance" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### A count plot \n", + "* It can be thought of as a histogram across a categorical, instead of quantitative, variable. \n", + "* The basic API and options are identical to those for barplot(), so you can compare counts across nested variables.\n", + "* I intended to see the spread of the data across a variable FULL_Charge" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.countplot(x = 'FULL_Charge', data = Train)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* The data in the FULL_Charge variable is normally distributed attaining a bell shaped so it gives me an insight in the data contained in the variable FULL_Charge " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 4)Checking how my data correlates with each other \n", + "* Correlation helps us determine how the different attributes relate with one another.\n", + "* It also helps us when deciding which attributes to select especially in the presence of highly correlated attributes in which case one of the two attributes would be sufficient.\n", + "* The corr function is used with Pearson's correlation method since most of the attributes are continous with the exception of NT_EFC195 and CLASS.In statistics, correlation or dependence is any statistical relationship, whether causal or not, between two random variables or bivariate data.\n", + "* Here the intension was to find out if there is a relationship between the variables" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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FULL_AcidicMolPerc-0.6129961.0000000.7947960.5414810.1152010.513344-0.143168-0.4315900.4496210.002334-0.213543-0.598816
FULL_AURR980107-0.4909770.7947961.0000000.5482530.3461390.462712-0.169540-0.4260970.4562600.032958-0.403599-0.584111
FULL_DAYM780201-0.4346030.5414810.5482531.0000000.0101180.334778-0.090058-0.4087930.8941910.055915-0.326792-0.554838
FULL_GEOR030101-0.0587250.1152010.3461390.0101181.0000000.319157-0.230417-0.160269-0.0290850.040480-0.151935-0.260470
FULL_OOBM850104-0.2837580.5133440.4627120.3347780.3191571.000000-0.230561-0.3362970.275640-0.4527690.155304-0.453287
NT_EFC1950.088068-0.143168-0.169540-0.090058-0.230417-0.2305611.0000000.178683-0.0368440.1459240.0808980.260702
AS_MeanAmphiMoment0.355477-0.431590-0.426097-0.408793-0.160269-0.3362970.1786831.000000-0.3223780.0255800.1715240.693552
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AS_FUKS010112-0.0905700.0023340.0329580.0559150.040480-0.4527690.1459240.0255800.0455621.000000-0.4452840.033432
CT_RACS8201040.232929-0.213543-0.403599-0.326792-0.1519350.1553040.0808980.171524-0.256060-0.4452841.0000000.267652
CLASS0.534602-0.598816-0.584111-0.554838-0.260470-0.4532870.2607020.693552-0.4371680.0334320.2676521.000000
\n", + "
" + ], + "text/plain": [ + " FULL_Charge FULL_AcidicMolPerc FULL_AURR980107 \\\n", + "FULL_Charge 1.000000 -0.612996 -0.490977 \n", + "FULL_AcidicMolPerc -0.612996 1.000000 0.794796 \n", + "FULL_AURR980107 -0.490977 0.794796 1.000000 \n", + "FULL_DAYM780201 -0.434603 0.541481 0.548253 \n", + "FULL_GEOR030101 -0.058725 0.115201 0.346139 \n", + "FULL_OOBM850104 -0.283758 0.513344 0.462712 \n", + "NT_EFC195 0.088068 -0.143168 -0.169540 \n", + "AS_MeanAmphiMoment 0.355477 -0.431590 -0.426097 \n", + "AS_DAYM780201 -0.365374 0.449621 0.456260 \n", + "AS_FUKS010112 -0.090570 0.002334 0.032958 \n", + "CT_RACS820104 0.232929 -0.213543 -0.403599 \n", + "CLASS 0.534602 -0.598816 -0.584111 \n", + "\n", + " FULL_DAYM780201 FULL_GEOR030101 FULL_OOBM850104 \\\n", + "FULL_Charge -0.434603 -0.058725 -0.283758 \n", + "FULL_AcidicMolPerc 0.541481 0.115201 0.513344 \n", + "FULL_AURR980107 0.548253 0.346139 0.462712 \n", + "FULL_DAYM780201 1.000000 0.010118 0.334778 \n", + "FULL_GEOR030101 0.010118 1.000000 0.319157 \n", + "FULL_OOBM850104 0.334778 0.319157 1.000000 \n", + "NT_EFC195 -0.090058 -0.230417 -0.230561 \n", + "AS_MeanAmphiMoment -0.408793 -0.160269 -0.336297 \n", + "AS_DAYM780201 0.894191 -0.029085 0.275640 \n", + "AS_FUKS010112 0.055915 0.040480 -0.452769 \n", + "CT_RACS820104 -0.326792 -0.151935 0.155304 \n", + "CLASS -0.554838 -0.260470 -0.453287 \n", + "\n", + " NT_EFC195 AS_MeanAmphiMoment AS_DAYM780201 \\\n", + "FULL_Charge 0.088068 0.355477 -0.365374 \n", + "FULL_AcidicMolPerc -0.143168 -0.431590 0.449621 \n", + "FULL_AURR980107 -0.169540 -0.426097 0.456260 \n", + "FULL_DAYM780201 -0.090058 -0.408793 0.894191 \n", + "FULL_GEOR030101 -0.230417 -0.160269 -0.029085 \n", + "FULL_OOBM850104 -0.230561 -0.336297 0.275640 \n", + "NT_EFC195 1.000000 0.178683 -0.036844 \n", + "AS_MeanAmphiMoment 0.178683 1.000000 -0.322378 \n", + "AS_DAYM780201 -0.036844 -0.322378 1.000000 \n", + "AS_FUKS010112 0.145924 0.025580 0.045562 \n", + "CT_RACS820104 0.080898 0.171524 -0.256060 \n", + "CLASS 0.260702 0.693552 -0.437168 \n", + "\n", + " AS_FUKS010112 CT_RACS820104 CLASS \n", + "FULL_Charge -0.090570 0.232929 0.534602 \n", + "FULL_AcidicMolPerc 0.002334 -0.213543 -0.598816 \n", + "FULL_AURR980107 0.032958 -0.403599 -0.584111 \n", + "FULL_DAYM780201 0.055915 -0.326792 -0.554838 \n", + "FULL_GEOR030101 0.040480 -0.151935 -0.260470 \n", + "FULL_OOBM850104 -0.452769 0.155304 -0.453287 \n", + "NT_EFC195 0.145924 0.080898 0.260702 \n", + "AS_MeanAmphiMoment 0.025580 0.171524 0.693552 \n", + "AS_DAYM780201 0.045562 -0.256060 -0.437168 \n", + "AS_FUKS010112 1.000000 -0.445284 0.033432 \n", + "CT_RACS820104 -0.445284 1.000000 0.267652 \n", + "CLASS 0.033432 0.267652 1.000000 " + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "corr=Train.corr(method='pearson')\n", + "corr\n", + "# The correllation 1 is a positive relationship, -1 a negative relationship and 0 no relationship" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* Heatmap is a way of representing the data in a 2-dimensional form. \n", + "* The data values are represented as colors in the graph. \n", + "* It's goal is to provide a colored visual summary of information so I could easily visualise the summary of the relationships between the features" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(12,12))\n", + "sns.heatmap(Train.corr(method='pearson'),annot=True,cmap=\"YlGnBu\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* From the graphs above since correlation is informative regarding which choice of features to retain for analysis, those variables/features which highly correlate with the class Attribute are to be consindered in feature selection and those that do not correlate or correlate weakly should be eliminated\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "FULL_Charge 0.534602\n", + "FULL_AcidicMolPerc -0.598816\n", + "FULL_AURR980107 -0.584111\n", + "FULL_DAYM780201 -0.554838\n", + "FULL_GEOR030101 -0.260470\n", + "FULL_OOBM850104 -0.453287\n", + "NT_EFC195 0.260702\n", + "AS_MeanAmphiMoment 0.693552\n", + "AS_DAYM780201 -0.437168\n", + "AS_FUKS010112 0.033432\n", + "CT_RACS820104 0.267652\n", + "CLASS 1.000000\n", + "Name: CLASS, dtype: float64" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Showing how each variable correlates with the CLASS variable\n", + "Train.corr(method='pearson')['CLASS']" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* For more depth of understanding the data the clustermap method is used \n", + "* THe clustered heatmap of a pandas DataFrame shows hierarchicay of data\n", + "* The .clustermap() method uses a hierarchical clusters to order data by similarity.\n", + "* This reorganizes the data for the rows and columns and displays similar content next to one another " + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.clustermap(Train.corr(method='pearson'),annot=True, cmap=\"Paired_r\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* The heatmap went further to show me the similarity matrix between variables so i could compare with the output from the heatmap" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 5)Data Visualisation\n", + "* Data visualizations in python can be done via many packages.\n", + "* Using matplot enables one to have a visual figures for the data\n", + "* Every Axes has an x-axis and y-axis for plotting. \n", + "* Contained within the axes are titles, ticks, labels associated with each axis" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 1)To check for skewness in my dataset\n", + "* Skew refers to a distribution that is assumed Gaussian (normal or bell curve) that is shifted in one direction or another\n", + "* Positive Skew is when the curve shifts to the right \n", + "* Negative skew is when the curve shifts to the left\n", + "* Skewed data can affect the performance of a machine learning algorithm\n", + "* Skewed data should be normalized using different transformation methods which include the square transformation for negatively skewed data and log transfomations." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Train.skew().plot(kind='bar')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* From the graph above most of the attributes are positively shwed with the exceptio of 4,6,9, and 10 but since the skew is to to a small extent then the data will not be normalised since it will have little effect on our logarithm model" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 2) Use of the box plot\n", + "* Boxplots summarize the distribution of each attribute\n", + "* A line for the median (middle value) is drawn while and a box put around the 25th and 75th percentiles.\n", + "* The whiskers give an idea of the spread of the data and dots outside of the whiskers show candidate outlier values \n", + "* The data.plot(kind='box') function is used" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Train.plot(kind='box', subplots=True, layout=(4,3), sharex=True,sharey=True)\n", + "plt.subplots_adjust(bottom=1, right=2, top=3)\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* AS_MeanAmphiMoment * From the above graphs, the class with no outliers is AS_MeanAmphiMoment and has a normal distribution in its variables\n", + "* " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 3) Scatter plot: \n", + "* This is plot the relationship between two variables as dots in two dimension.\n", + "* This is done so we could spot if there is a structured relationship within the two variables" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Histograms\n", + "plt.figure(figsize=(15,15))\n", + "Train.hist(color='red')\n", + "\n", + "plt.subplots_adjust(bottom=1, right=2, top=3)\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* From the above graphs we can tell that we have 2 categorical attributes NT_EFC195 and CLASS but the numbes in each group do not balance out.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6)Preparation of data for Machine Learning\n", + "### Pre-processing of Data is carried out in this section\n", + "* I will need to preapre my data for prepossessing \n", + "* My preffered method for Data transformation is \"The Fit and Multiple Transform\" method form the scikit-learn library.\n", + "* Split the dataset into the input and output variables for machine learning.\n", + "* Apply a pre-processing transform to the input variables.\n", + "* Summarize the data to show the change.\n", + "### a)Rescaling the Data: \n", + "* Rescaling is done since the data has various scales and these need to be into a scale that fits all\n", + "* From numpy, the set_printoptions module is imported to determine the display of number of floating point values other Nump objects and from scikit learn preprocessing module.\n", + "* The MinMaxScaler option is imported to rescale the data.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[0.457 0. 0.348 0.545 0.33 0.483 0. 0.005 0.508 0.415 0.182]\n", + " [0.435 0.116 0.322 0.489 0.276 0.458 1. 0.011 0.421 0.586 0.475]\n", + " [0.467 0.116 0.246 0.523 0.288 0.565 0. 0.011 0.442 0.273 0.666]\n", + " [0.457 0.089 0.275 0.399 0.403 0.647 0. 0.011 0.405 0.153 0.424]\n", + " [0.511 0.183 0.323 0.373 0.342 0.595 0. 0.011 0.5 0.196 0.536]]\n" + ] + } + ], + "source": [ + "\n", + "from numpy import set_printoptions\n", + "from sklearn.preprocessing import MinMaxScaler\n", + "array = Train.values\n", + "# separate array into input and output components\n", + "X= array[:,0:11]\n", + "Y= array[:,11]\n", + "scaler = MinMaxScaler(feature_range=(0, 1))\n", + "rescaledX = scaler.fit_transform(X)\n", + "# summarize transformed data\n", + "set_printoptions(precision=3)\n", + "print(rescaledX[0:5,:])\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* No rescaling of data was done since predictions with rescaled data had a poor result in my analysis" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[1. 0. 1. 1. 1. 0. 0. 1. 1. 1. 1.]\n", + " [1. 1. 1. 1. 1. 0. 1. 1. 1. 1. 1.]\n", + " [1. 1. 1. 1. 1. 0. 0. 1. 1. 1. 1.]\n", + " [1. 1. 1. 1. 1. 0. 0. 1. 1. 1. 1.]\n", + " [1. 1. 1. 1. 1. 0. 0. 1. 1. 1. 1.]]\n" + ] + } + ], + "source": [ + "# Looking at when my data is binarized instead\n", + "from sklearn.preprocessing import Binarizer\n", + "\n", + "array2 = Train.values\n", + "# separate array into input and output components\n", + "X = array2[:,0:11]\n", + "Y = array2[:,11]\n", + "binarizer = Binarizer(threshold=0.0).fit(X)\n", + "binaryX = binarizer.transform(X)\n", + "# summarize transformed data\n", + "set_printoptions(precision=3)\n", + "print(binaryX[0:5,:])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "*Since my data was not boolean the data binarised was not used" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Num Features: 6\n", + "Selected Features: [ True False True False True True True False False False True]\n", + "Feature Ranking: [1 5 1 4 1 1 1 2 6 3 1]\n", + "Num Features: 6\n", + "Selected Features: [ True False True False True True True False False False True]\n", + "Feature Ranking: [1 5 1 4 1 1 1 2 6 3 1]\n" + ] + } + ], + "source": [ + "#b) Feature Selection\n", + "#Select an anttribute will will give the most to the prediction variable \n", + "#a)Selection is by The Recursive Feature Elimination (or RFE) \n", + "# This works by recursively removing attributes and building a model on those attributes that remain.\n", + "from sklearn.feature_selection import RFE\n", + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "# feature extraction\n", + "# feature extraction\n", + "model = LogisticRegression()\n", + "rfe = RFE(model, 6)\n", + "fit = rfe.fit(X, Y)\n", + "print(\"Num Features: \", fit.n_features_)\n", + "print(\"Selected Features:\", fit.support_)\n", + "print(\"Feature Ranking: \", fit.ranking_)\n", + "print(\"Num Features: \", fit.n_features_)\n", + "print(\"Selected Features:\", fit.support_)\n", + "print(\"Feature Ranking: \", fit.ranking_)\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### c)PCA\n", + "Principal component analysis is a dimensionality reduction technique. It uses linear algebra to transform the dataset into a compressed form." + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Explained Variance: [0.605 0.242 0.103]\n", + "[[ 1.409e-01 -3.557e-01 -4.743e-03 -4.935e-01 -1.975e-04 -5.101e-02\n", + " 2.877e-03 6.020e-01 -4.950e-01 -8.765e-04 4.186e-03]\n", + " [-8.867e-03 3.090e-02 4.994e-04 3.921e-01 -5.282e-04 -8.492e-03\n", + " 3.437e-03 7.629e-01 5.129e-01 5.018e-03 -2.000e-03]\n", + " [-2.731e-01 8.713e-01 8.049e-03 -1.349e-01 4.214e-04 8.143e-02\n", + " -2.941e-03 2.312e-01 -2.966e-01 -1.359e-03 -5.700e-04]]\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "from sklearn.decomposition import PCA\n", + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "# feature extraction\n", + "pca = PCA(n_components=3)\n", + "fit = pca.fit(X)\n", + "# summarize components\n", + "print(\"Explained Variance: %s\" % fit.explained_variance_ratio_)\n", + "print(fit.components_)\n", + "\n", + "high_dim = Train.drop(columns='CLASS')\n", + "\n", + "scaler.fit(high_dim)\n", + "scaled_data = scaler.transform(high_dim)\n", + "\n", + "from sklearn.decomposition import PCA\n", + "pca = PCA(n_components=2)\n", + "pca.fit(scaled_data)\n", + "\n", + "x_pca = pca.transform(scaled_data)\n", + "\n", + "plt.figure(figsize=(8,6))\n", + "plt.scatter(x_pca[:,0], x_pca[:,1], c=Train['CLASS'], cmap='Spectral')\n", + "plt.xlabel('First Principal Component')\n", + "plt.ylabel('First Principal Component')\n", + "labels = np.unique(Y)\n", + "plt.legend(labels)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "From the PCA plot, Two distinct classes are obseved. The Note is in the class distribution and region of overlap between the two classes.\n", + "The overlap problem is a critical problem in which instances appear as valid for more than one class which may be responsible for the presence of noise in datasets and thus affect the performance of the learning algorithm (Gupta and Gupta, 2018)." + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0.078 0.152 0.082 0.085 0.053 0.064 0.037 0.318 0.052 0.033 0.047]\n" + ] + } + ], + "source": [ + "# Feature importance\n", + "from sklearn.ensemble import ExtraTreesClassifier\n", + "\n", + "array = Train.values\n", + "A = array[:,0:11]\n", + "B = array[:,11]\n", + "# feature extraction\n", + "model = ExtraTreesClassifier()\n", + "model.fit(X, Y)\n", + "print(model.feature_importances_)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Calculate feature importances\n", + "importances = model.feature_importances_\n", + "# Create decision tree classifer object\n", + "clf = ExtraTreesClassifier(random_state=0, n_jobs=-1)\n", + "\n", + "# Train model\n", + "model = clf.fit(X, Y)\n", + "\n", + "# Sort feature importances in descending order\n", + "indices = np.argsort(importances)[::-1]\n", + "\n", + "# Rearrange feature names so they match the sorted feature importances\n", + "names = [Train.CLASS[i] for i in indices]\n", + "\n", + "# Create plot\n", + "plt.figure()\n", + "\n", + "# Create plot title\n", + "plt.title(\"Feature Importance\")\n", + "\n", + "# Add bars\n", + "plt.bar(range(X.shape[1]), importances[indices])\n", + "\n", + "# Add feature names as x-axis labels\n", + "plt.xticks(range(X.shape[1]), names, rotation=90)\n", + "\n", + "# Show plot\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "## According to feature importance all the features in the data set were useful hence could not be lost and therefore I kept them all therefor no rescaling was carried out" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 7)Evaluate the Performance of Machine Learning Algorithms with Resampling\n", + "##There is need to know how well the algorithms will perform on unseen data\n", + "##The best way to evaluate the performance of an algorithm is to make predictions for new data to which answers are known\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 91.63533834586465\n" + ] + } + ], + "source": [ + "## Split the Data into Test and Train\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.linear_model import LogisticRegression\n", + "test_size = 0.35\n", + "seed = 42\n", + "\n", + "X_train,X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", + "random_state=seed)\n", + "model = LogisticRegression()\n", + "model.fit(X_train, Y_train)\n", + "result = model.score(X_test, Y_test)\n", + "print(\"Accuracy: \", (result*100.0))" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[False True]\n", + "2\n", + "387\n", + "371\n" + ] + } + ], + "source": [ + "out= model.predict(Test.values)\n", + "\n", + "Eva = pd.DataFrame(out) #Converting to data frame\n", + "Eva.columns=[\"CLASS\"] #Naming the column\n", + "Eva.index.name=\"Index\" #Creating a column index\n", + "Eva[\"CLASS\"]=Eva[\"CLASS\"].map({0.0:False,1.0:True}) # Chaninging 0 to \"False\" 1 to \"True\"\n", + "\n", + "Eva.to_csv(\"Amber_csv\") ## Writing a csv file\n", + "print(Eva['CLASS'].unique())\n", + "print(Eva['CLASS'].nunique())\n", + "\n", + "#printing the numbers of False and True\n", + "print(Eva.groupby('CLASS').size()[0].sum()) #\n", + "print(Eva.groupby('CLASS').size()[1].sum())" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 91.54135338345864\n" + ] + } + ], + "source": [ + "# On rescaled Data\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.linear_model import LogisticRegression\n", + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "test_size = 0.35\n", + "seed = 42\n", + "\n", + "rescaledX_train,rescaledX_test, Y_train, Y_test = train_test_split(rescaledX, Y, test_size=test_size,\n", + "random_state=seed)\n", + "model = LogisticRegression()\n", + "model.fit(rescaledX_train, Y_train)\n", + "result = model.score(rescaledX_test, Y_test)\n", + "print(\"Accuracy: \", (result*100.0))" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[False True]\n", + "2\n", + "752\n", + "6\n" + ] + } + ], + "source": [ + "out= model.predict(Test.values)\n", + "\n", + "Eva = pd.DataFrame(out) #Converting to data frame\n", + "Eva.columns=[\"CLASS\"] #Naming the column\n", + "Eva.index.name=\"Index\" #Creating a column index\n", + "Eva[\"CLASS\"]=Eva[\"CLASS\"].map({0.0:False,1.0:True}) # Chaninging 0 to \"False\" 1 to \"True\"\n", + "\n", + "Eva.to_csv(\"Amber1_csv\") ## Writing a csv file\n", + "print(Eva['CLASS'].unique())\n", + "print(Eva['CLASS'].nunique())\n", + "\n", + "#printing the numbers of False and True\n", + "print(Eva.groupby('CLASS').size()[0].sum()) #\n", + "print(Eva.groupby('CLASS').size()[1].sum())" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [], + "source": [ + "## Despite having a similar accuracy of 91.82,the rescaled data was giving imbalanced false a.nd true values and therefore i would not use it further" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: (88.66787208086441, 18.91491119508906)\n" + ] + } + ], + "source": [ + "#Classification accuracy:is the number of correct predictions made as a ratio of all predictions made.\n", + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "array = Train.values\n", + "\n", + "num_folds = 20#number of folds to use\n", + "seed = 42#reproducibility\n", + "\n", + "kfold = KFold(n_splits=num_folds, random_state=None)\n", + "model = LogisticRegression()\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\n", + "random_state=seed)\n", + "model.fit(X_train, Y_train)\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "\n", + "print(f\"Accuracy:\", (results.mean()*100.0, results.std()*100.0))" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[False True]\n", + "2\n", + "387\n", + "371\n" + ] + } + ], + "source": [ + "\n", + "out= model.predict(Test.values)\n", + "\n", + "Eva = pd.DataFrame(out) #Converting to data frame\n", + "Eva.columns=[\"CLASS\"] #Naming the column\n", + "Eva.index.name=\"Index\" #Creating a column index\n", + "Eva[\"CLASS\"]=Eva[\"CLASS\"].map({0.0:False,1.0:True}) # Chaninging 0 to \"False\" 1 to \"True\"\n", + "\n", + "Eva.to_csv(\"Amber2_csv\") ## Writing a csv file\n", + "print(Eva['CLASS'].unique())\n", + "print(Eva['CLASS'].nunique())\n", + "\n", + "#printing the numbers of False and True\n", + "print(Eva.groupby('CLASS').size()[0].sum()) #\n", + "print(Eva.groupby('CLASS').size()[1].sum())" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precision recall f1-score support\n", + "\n", + " 0.0 0.91 0.92 0.91 521\n", + " 1.0 0.92 0.91 0.92 543\n", + "\n", + " accuracy 0.92 1064\n", + " macro avg 0.92 0.92 0.92 1064\n", + "weighted avg 0.92 0.92 0.92 1064\n", + "\n" + ] + } + ], + "source": [ + "#To check out the classification report \n", + "from sklearn.metrics import classification_report\n", + "\n", + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "scaler = MinMaxScaler(feature_range=(0, 1))\n", + "rescaledA = scaler.fit_transform(A)\n", + "scaler = MinMaxScaler(feature_range=(0, 1))\n", + "rescaledA = scaler.fit_transform(A)\n", + "test_size = 0.35\n", + "seed = 42\n", + "rescaledX_train,rescaledX_test, Y_train, Y_test = train_test_split(rescaledX, Y, test_size=test_size,\n", + "random_state=seed)\n", + "model = LogisticRegression()\n", + "model.fit(rescaledX_train, Y_train)\n", + "predicted = model.predict(rescaledX_test)\n", + "report = classification_report(Y_test, predicted)\n", + "print(report)" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MAE: (-0.26434068269258093, 0.156909136567752)\n" + ] + } + ], + "source": [ + "# we then look at the regression M\n", + "# The Mean Absolute Error(MAE) is the sum of the absolute differences between predictions and actual values.\n", + "# Its aim is to give an idea of how wrong the predictions were. \n", + "from pandas import read_csv\n", + "from sklearn.linear_model import LinearRegression\n", + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "kfold = KFold(n_splits=10, random_state=None)\n", + "model = LinearRegression()\n", + "scoring = 'neg_mean_absolute_error'\n", + "results = cross_val_score(model, rescaledX, Y, cv=kfold, scoring=scoring)\n", + "print(\"MAE:\",(results.mean(), results.std()))" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "R^2: (-1.2197243963358124, 3.6591731890074377)\n" + ] + } + ], + "source": [ + "#The R2 metric provides an indication of the goodness of fit of a set of predictions to the actual values\n", + "#Cross Validation Regression R^2\n", + "array = Train.values\n", + "X = array[:,0:11]\n", + "Y = array[:,11]\n", + "\n", + "kfold = KFold(n_splits=10, random_state=None)\n", + "model = LinearRegression()\n", + "scoring = 'r2'\n", + "results = cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\n", + "print(\"R^2:\",(results.mean(), results.std()))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 8)Spot-Checking Classiffication Algorithms\n", + "##Algorithms Overview\n", + "##looking at six classication algorithms that will help spot-check on your dataset. Starting with two ##linear machine learning algorithms:\n", + "\n", + "8.1.1)Logistic Regression.\n", + "8.1.2)Linear Discriminant Analysis.\n", + "Then looking at four nonlinear machine learning algorithms:\n", + "\n", + "8.2.1)k-Nearest Neighbors.\n", + "8.2.2)Naive Bayes.\n", + "8.2.3)Classication and Regression Trees.\n", + "8.2.4)Support Vector Machines.\n", + "8.2.5)Random Forest\n", + "8.2.6)Gradient Boosting for classification\n", + "8.2.7)An extra-trees classifier.\n", + "8.2.8)Neural Network-MLPC" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " ## 8.1)Linear Machine Language Alogarithms\n", + "### 8.1.1)Logistic Regression\n", + "Logistic regression assumes a Gaussian distribution for the numeric input variables and can model binary classiffication problems.\n", + "****This is done using the Logisticregression class" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "accuracy 91.54051589369463\n", + "MCC: 0.8342865299822478\n" + ] + } + ], + "source": [ + "# Logistic Regression Classification\n", + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.metrics import matthews_corrcoef\n", + "from sklearn.metrics import plot_confusion_matrix\n", + "\n", + "#for model set up\n", + "model = LogisticRegression()\n", + "# For cross validation of data\n", + "num_folds = 10\n", + "seed=42\n", + "kfold = KFold(n_splits=num_folds, random_state=seed,shuffle=True)\n", + "#For accuracy of model\n", + "scoring='accuracy'\n", + "results = cross_val_score(model, X, Y, cv=kfold,scoring=scoring)\n", + "print('accuracy',results.mean()*100)\n", + "#Training the model to make a prediction\n", + "model.fit(X,Y)\n", + "kmodel=model.predict(Test)\n", + "#With Mathews correlation cofficient on the model\n", + "kmcc=matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',kmcc)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[False True]\n", + "2\n", + "383\n", + "375\n" + ] + } + ], + "source": [ + "#Converting the LogisticRegression predicted model first to data frame then a CSV file\n", + "out= model.predict(Test.values)\n", + "\n", + "Eva = pd.DataFrame(out) #Converting to data frame\n", + "Eva.columns=[\"CLASS\"] #Naming the column\n", + "Eva.index.name=\"Index\" #Creating a column index\n", + "Eva[\"CLASS\"]=Eva[\"CLASS\"].map({0.0:False,1.0:True}) # Chaninging 0 to \"False\" 1 to \"True\"\n", + "\n", + "Eva.to_csv(\"Amber3_csv\") ## Writing a csv file\n", + "print(Eva['CLASS'].unique())\n", + "print(Eva['CLASS'].nunique())\n", + "\n", + "#printing the numbers of False and True\n", + "print(Eva.groupby('CLASS').size()[0].sum()) #\n", + "print(Eva.groupby('CLASS').size()[1].sum())" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [], + "source": [ + "# The difference between Accuracy and MCC model is slight but giving the same output pf 383 True values and 375 false values" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 8.1.2)Linear Discriminant Analysis or LDA \n", + "-This a statistical technique for binary and multiclass classiffication. \n", + "-It too assumes a Gaussian distribution for the numerical input variables. \n", + "-You can construct an LDA model using the LinearDiscriminantAnalysis class" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "accuracy 91.70574952232066\n", + "MCC: 0.8377162908048379\n" + ] + } + ], + "source": [ + "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", + "#Model set up\n", + "model = LinearDiscriminantAnalysis()\n", + "# For cross validation of data\n", + "num_folds = 10\n", + "seed=42\n", + "kfold = KFold(n_splits=num_folds, random_state=seed,shuffle=True)\n", + "#For accuracy of model\n", + "scoring='accuracy'\n", + "results = cross_val_score(model, X, Y, cv=kfold,scoring=scoring)\n", + "print('accuracy',results.mean()*100)\n", + "#Training the model to make a prediction\n", + "model.fit(X,Y)\n", + "kmodel=model.predict(Test)\n", + "#With Mathews correlation cofficient on the model\n", + "kmcc=matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',kmcc)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[False True]\n", + "2\n", + "401\n", + "357\n" + ] + } + ], + "source": [ + "#Converting the LinearDiscriminantAnalysis predicted model first to data frame then a CSV file\n", + "out= model.predict(Test.values)\n", + "\n", + "Eva = pd.DataFrame(out) #Converting to data frame\n", + "Eva.columns=[\"CLASS\"] #Naming the column\n", + "Eva.index.name=\"Index\" #Creating a column index\n", + "Eva[\"CLASS\"]=Eva[\"CLASS\"].map({0.0:False,1.0:True}) # Chaninging 0 to \"False\" 1 to \"True\"\n", + "\n", + "Eva.to_csv(\"Amber4_csv\") ## Writing a csv file\n", + "print(Eva['CLASS'].unique())\n", + "print(Eva['CLASS'].nunique())\n", + "\n", + "#printing the numbers of False and True\n", + "print(Eva.groupby('CLASS').size()[0].sum()) #\n", + "print(Eva.groupby('CLASS').size()[1].sum())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 8.2 Nonlinear machine learning algorithms.\n", + "\n", + "### 8.2.1)k-Nearest Neighbors\n", + "##The k-Nearest Neighbors algorithm (or KNN) uses a distance metric to find the k most similar instances ##In the training data for a new instance and takes the mean outcome of the neighbors as the prediction. #You can construct a KNN model using the KNeighborsClassifier class." + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "accuracy 90.5863066851643\n", + "MCC: 0.8690586462107053\n" + ] + } + ], + "source": [ + "from sklearn.neighbors import KNeighborsClassifier\n", + "#Model set up\n", + "model = KNeighborsClassifier()\n", + "# For cross validation of data\n", + "num_folds = 5\n", + "seed=42\n", + "kfold = KFold(n_splits=num_folds, random_state=seed,shuffle=True)\n", + "#For accuracy of model\n", + "scoring='accuracy'\n", + "results = cross_val_score(model, X, Y, cv=kfold,scoring=scoring)\n", + "print('accuracy',results.mean()*100)\n", + "#Training the model to make a prediction\n", + "model.fit(X,Y)\n", + "kmodel=model.predict(Test)\n", + "#With Mathews correlation cofficient on the model\n", + "kmcc=matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',kmcc)" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[False True]\n", + "2\n", + "402\n", + "356\n" + ] + } + ], + "source": [ + "#Converting the LinearDiscriminantAnalysis predicted model first to data frame then a CSV file\n", + "out= model.predict(Test.values)\n", + "\n", + "Eva = pd.DataFrame(out) #Converting to data frame\n", + "Eva.columns=[\"CLASS\"] #Naming the column\n", + "Eva.index.name=\"Index\" #Creating a column index\n", + "Eva[\"CLASS\"]=Eva[\"CLASS\"].map({0.0:False,1.0:True}) # Chaninging 0 to \"False\" 1 to \"True\"\n", + "\n", + "Eva.to_csv(\"Amber5_csv\") ## Writing a csv file\n", + "print(Eva['CLASS'].unique())\n", + "print(Eva['CLASS'].nunique())\n", + "\n", + "#printing the numbers of False and True\n", + "print(Eva.groupby('CLASS').size()[0].sum()) #\n", + "print(Eva.groupby('CLASS').size()[1].sum())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 8.2.2) Naive Bayes\n", + "-Naive Bayes calculates the probability of each class and the conditional probability of each class given each input value. \n", + "-These probabilities are estimated for new data and multiplied together\n", + "-The Assumption is that they are all independent (a simple or naive assumption).\n", + "-When working with real-valued data, a Gaussian distribution is assumed to easily estimate the probabilities for input variables using the Gaussian Probability Density Function. \n", + "##You can construct a Naive Bayes model using the GaussianNB class4" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "accuracy 91.93622980719125\n", + "MCC: 0.8407203694376205\n", + "0.9193622980719125\n" + ] + } + ], + "source": [ + "from sklearn.naive_bayes import GaussianNB\n", + "# For cross validation of data\n", + "num_folds = 10\n", + "seed=42\n", + "kfold = KFold(n_splits=num_folds, random_state=seed,shuffle=True)\n", + "model = GaussianNB()\n", + "\n", + "#For accuracy of model\n", + "scoring='accuracy'\n", + "results = cross_val_score(model, X, Y, cv=kfold,scoring=scoring)\n", + "print('accuracy',results.mean()*100)\n", + "#Training the model to make a prediction\n", + "model.fit(X,Y)\n", + "kmodel=model.predict(Test)\n", + "#With Mathews correlation cofficient on the model\n", + "kmcc=matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',kmcc)\n", + "\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(results.mean())" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ True False]\n", + "2\n", + "370\n", + "388\n" + ] + } + ], + "source": [ + "#Converting the Naive Bayes predicted model first to data frame then a CSV file\n", + "out= model.predict(Test.values)\n", + "\n", + "Eva = pd.DataFrame(out) #Converting to data frame\n", + "Eva.columns=[\"CLASS\"] #Naming the column\n", + "Eva.index.name=\"Index\" #Creating a column index\n", + "Eva[\"CLASS\"]=Eva[\"CLASS\"].map({0.0:False,1.0:True}) # Chaninging 0 to \"False\" 1 to \"True\"\n", + "\n", + "Eva.to_csv(\"Amber5_csv\") ## Writing a csv file\n", + "print(Eva['CLASS'].unique())\n", + "print(Eva['CLASS'].nunique())\n", + "\n", + "#printing the numbers of False and True\n", + "print(Eva.groupby('CLASS').size()[0].sum()) #\n", + "print(Eva.groupby('CLASS').size()[1].sum())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 8.2.3)Classiffication and Regression Trees\n", + "Classiffication and Regression Trees (CART or just decision trees) construct a binary tree from the training data. Split points are chosen greedily by evaluating each attribute and each value of each attribute in the training data in order to minimize a cost function (like the Gini index). You can construct a CART model using the DecisionTreeClassifier class" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "accuracy 89.20379537953795\n", + "MCC: 1.0\n" + ] + } + ], + "source": [ + "from sklearn.tree import DecisionTreeClassifier\n", + "# For cross validation of data\n", + "num_folds = 10\n", + "seed=42\n", + "kfold = KFold(n_splits=num_folds, random_state=seed,shuffle=True)\n", + "model = DecisionTreeClassifier()\n", + "#For accuracy of model\n", + "scoring='accuracy'\n", + "results = cross_val_score(model, X, Y, cv=kfold,scoring=scoring)\n", + "print('accuracy',results.mean()*100)\n", + "#Training the model to make a prediction\n", + "model.fit(X,Y)\n", + "kmodel=model.predict(Test)\n", + "#With Mathews correlation cofficient on the model\n", + "kmcc=matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',kmcc)\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ True False]\n", + "2\n", + "388\n", + "370\n" + ] + } + ], + "source": [ + "#Converting the DecisionTreeClassifier predicted model first to data frame then a CSV file\n", + "out= model.predict(Test.values)\n", + "\n", + "Eva = pd.DataFrame(out) #Converting to data frame\n", + "Eva.columns=[\"CLASS\"] #Naming the column\n", + "Eva.index.name=\"Index\" #Creating a column index\n", + "Eva[\"CLASS\"]=Eva[\"CLASS\"].map({0.0:False,1.0:True}) # Chaninging 0 to \"False\" 1 to \"True\"\n", + "\n", + "Eva.to_csv(\"Amber6_csv\") ## Writing a csv file\n", + "print(Eva['CLASS'].unique())\n", + "print(Eva['CLASS'].nunique())\n", + "\n", + "#printing the numbers of False and True\n", + "print(Eva.groupby('CLASS').size()[0].sum()) #\n", + "print(Eva.groupby('CLASS').size()[1].sum())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 8.2.4)Support Vector Machines\n", + "Support Vector Machines (or SVM) seek a line that best separates two classes. \n", + "The data instances closest to the line that best separates the classes are called support vectors and \n", + "influence where the line is placed. \n", + "SVM supports multiple classes and that of particular importance is the use of dierent kernel functions via the kernel parameter." + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "accuracy 90.81618030224075\n", + "MCC: 0.8187103751493263\n", + "0.9081618030224075\n" + ] + } + ], + "source": [ + "from sklearn.svm import SVC\n", + "# For cross validation of data\n", + "num_folds = 10\n", + "seed=42\n", + "kfold = KFold(n_splits=num_folds, random_state=seed,shuffle=True)\n", + "model = SVC()\n", + "\n", + "#For accuracy of model\n", + "scoring='accuracy'\n", + "results = cross_val_score(model, X, Y, cv=kfold,scoring=scoring)\n", + "print('accuracy',results.mean()*100)\n", + "#Training the model to make a prediction\n", + "model.fit(X,Y)\n", + "kmodel=model.predict(Test)\n", + "#With Mathews correlation cofficient on the model\n", + "kmcc=matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',kmcc)\n", + "\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(results.mean())\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[False True]\n", + "2\n", + "397\n", + "361\n" + ] + } + ], + "source": [ + "#Converting the SVC predicted model first to data frame then a CSV file\n", + "out= model.predict(Test.values)\n", + "\n", + "Eva = pd.DataFrame(out) #Converting to data frame\n", + "Eva.columns=[\"CLASS\"] #Naming the column\n", + "Eva.index.name=\"Index\" #Creating a column index\n", + "Eva[\"CLASS\"]=Eva[\"CLASS\"].map({0.0:False,1.0:True}) # Chaninging 0 to \"False\" 1 to \"True\"\n", + "\n", + "Eva.to_csv(\"Amber7_csv\") ## Writing a csv file\n", + "print(Eva['CLASS'].unique())\n", + "print(Eva['CLASS'].nunique())\n", + "\n", + "#printing the numbers of False and True\n", + "print(Eva.groupby('CLASS').size()[0].sum()) #\n", + "print(Eva.groupby('CLASS').size()[1].sum())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 8.2.5)Random Forest\n", + "Random forests or random decision forests are an ensemble learning method for classification, regression and other tasks, that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes (classification) or mean prediction (regression) of the individual trees.\n", + "Random decision forests correct for decision trees’ habit of over fitting to their training set." + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "accuracy 93.68030224075041\n", + "MCC: 1.0\n", + "0.9417394042035783\n" + ] + } + ], + "source": [ + "from sklearn.ensemble import RandomForestClassifier\n", + "# For cross validation of data\n", + "num_folds = 10\n", + "seed=42\n", + "kfold = KFold(n_splits=num_folds, random_state=seed,shuffle=True)\n", + "model = RandomForestClassifier(bootstrap = True,\n", + " max_features = None)\n", + "\n", + "#For accuracy of model\n", + "scoring='accuracy'\n", + "results = cross_val_score(model, X, Y, cv=kfold,scoring=scoring)\n", + "print('accuracy',results.mean()*100)\n", + "#Training the model to make a prediction\n", + "model.fit(X,Y)\n", + "kmodel=model.predict(Test)\n", + "#With Mathews correlation cofficient on the model\n", + "kmcc=matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',kmcc)\n", + "\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(results.mean())" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ True False]\n", + "2\n", + "383\n", + "375\n" + ] + } + ], + "source": [ + "#Converting the Randomforest predicted model first to data frame then a CSV file\n", + "out= model.predict(Test.values)\n", + "\n", + "Eva = pd.DataFrame(out) #Converting to data frame\n", + "Eva.columns=[\"CLASS\"] #Naming the column\n", + "Eva.index.name=\"Index\" #Creating a column index\n", + "Eva[\"CLASS\"]=Eva[\"CLASS\"].map({0.0:False,1.0:True}) # Chaninging 0 to \"False\" 1 to \"True\"\n", + "\n", + "Eva.to_csv(\"Amber8_csv\") ## Writing a csv file\n", + "print(Eva['CLASS'].unique())\n", + "print(Eva['CLASS'].nunique())\n", + "\n", + "#printing the numbers of False and True\n", + "print(Eva.groupby('CLASS').size()[0].sum()) #\n", + "print(Eva.groupby('CLASS').size()[1].sum())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 8.2.6)Gradient Boosting for classification.\n", + "GB builds an additive model in a forward stage-wise fashion; it allows for the optimization of arbitrary differentiable loss functions. \n", + "In each stage n_classes_ regression trees are fit on the negative gradient of the binomial or multinomial deviance loss function.\n", + "Binary classification is a special case where only a single regression tree is induced." + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "accuracy 93.15442070522842\n", + "MCC: 0.9092011960769395\n", + "0.9315442070522841\n" + ] + } + ], + "source": [ + "from sklearn.ensemble import GradientBoostingClassifier\n", + "# For cross validation of data\n", + "num_folds = 10\n", + "seed=42\n", + "kfold = KFold(n_splits=num_folds, random_state=seed,shuffle=True)\n", + "model = GradientBoostingClassifier(learning_rate = 1.0,\n", + " max_depth = 1)\n", + "\n", + "#For accuracy of model\n", + "scoring='accuracy'\n", + "results = cross_val_score(model, X, Y, cv=kfold,scoring=scoring)\n", + "print('accuracy',results.mean()*100)\n", + "#Training the model to make a prediction\n", + "model.fit(X,Y)\n", + "kmodel=model.predict(Test)\n", + "#With Mathews correlation cofficient on the model\n", + "kmcc=matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',kmcc)\n", + "\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(results.mean())" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ True False]\n", + "2\n", + "382\n", + "376\n" + ] + } + ], + "source": [ + "#Converting the GradientBoostingClassifier predicted model first to data frame then a CSV file\n", + "out= model.predict(Test.values)\n", + "\n", + "Eva = pd.DataFrame(out) #Converting to data frame\n", + "Eva.columns=[\"CLASS\"] #Naming the column\n", + "Eva.index.name=\"Index\" #Creating a column index\n", + "Eva[\"CLASS\"]=Eva[\"CLASS\"].map({0.0:False,1.0:True}) # Chaninging 0 to \"False\" 1 to \"True\"\n", + "\n", + "Eva.to_csv(\"Amber9_csv\") ## Writing a csv file\n", + "print(Eva['CLASS'].unique())\n", + "print(Eva['CLASS'].nunique())\n", + "\n", + "#printing the numbers of False and True\n", + "print(Eva.groupby('CLASS').size()[0].sum()) #\n", + "print(Eva.groupby('CLASS').size()[1].sum())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 8.2.7)An extra-trees classifier.\n", + "This class implements a meta estimator that fits a number of randomized decision trees (a.k.a. extra-trees) on various sub-samples of the dataset.\n", + "It uses averaging to improve the predictive accuracy and control over-fitting." + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "accuracy 93.77898645127671\n", + "MCC: 1.0\n", + "0.9364751606739621\n" + ] + } + ], + "source": [ + "from sklearn.ensemble import ExtraTreesClassifier\n", + "# For cross validation of data\n", + "num_folds = 10\n", + "seed=42\n", + "kfold = KFold(n_splits=num_folds, random_state=seed,shuffle=True)\n", + "model = ExtraTreesClassifier() \n", + "\n", + "#For accuracy of model\n", + "scoring='accuracy'\n", + "results = cross_val_score(model, X, Y, cv=kfold,scoring=scoring)\n", + "print('accuracy',results.mean()*100)\n", + "#Training the model to make a prediction\n", + "model.fit(X,Y)\n", + "kmodel=model.predict(Test)\n", + "#With Mathews correlation cofficient on the model\n", + "kmcc=matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',kmcc)\n", + "\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(results.mean())" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ True False]\n", + "2\n", + "384\n", + "374\n" + ] + } + ], + "source": [ + "#Converting the ExtratreeClassifier predicted model first to data frame then a CSV file\n", + "out= model.predict(Test.values)\n", + "\n", + "Eva = pd.DataFrame(out) #Converting to data frame\n", + "Eva.columns=[\"CLASS\"] #Naming the column\n", + "Eva.index.name=\"Index\" #Creating a column index\n", + "Eva[\"CLASS\"]=Eva[\"CLASS\"].map({0.0:False,1.0:True}) # Chaninging 0 to \"False\" 1 to \"True\"\n", + "\n", + "Eva.to_csv(\"Amber10_csv\") ## Writing a csv file\n", + "print(Eva['CLASS'].unique())\n", + "print(Eva['CLASS'].nunique())\n", + "\n", + "#printing the numbers of False and True\n", + "print(Eva.groupby('CLASS').size()[0].sum()) #\n", + "print(Eva.groupby('CLASS').size()[1].sum())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 8.2.8)Multi-layer Perceptron classifier.\n", + "This model optimizes the log-loss function using LBFGS or stochastic gradient descent." + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "accuracy 92.39708181344449\n", + "MCC: 0.8470217206261198\n", + "0.9213359822824387\n" + ] + } + ], + "source": [ + "from sklearn.neural_network import MLPClassifier\n", + "# For cross validation of data\n", + "num_folds = 10\n", + "seed=42\n", + "kfold = KFold(n_splits=num_folds, random_state=seed,shuffle=True)\n", + "model = MLPClassifier() \n", + "\n", + "#For accuracy of model\n", + "scoring='accuracy'\n", + "results = cross_val_score(model, X, Y, cv=kfold,scoring=scoring)\n", + "print('accuracy',results.mean()*100)\n", + "#Training the model to make a prediction\n", + "model.fit(X,Y)\n", + "kmodel=model.predict(Test)\n", + "#With Mathews correlation cofficient on the model\n", + "kmcc=matthews_corrcoef(model.predict(X),Y)\n", + "print('MCC:',kmcc)\n", + "\n", + "results = cross_val_score(model, X, Y, cv=kfold)\n", + "print(results.mean())" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ True False]\n", + "2\n", + "356\n", + "402\n" + ] + } + ], + "source": [ + "#Converting the MLPClassifier predicted model first to data frame then a CSV file\n", + "out= model.predict(Test.values)\n", + "\n", + "Eva = pd.DataFrame(out) #Converting to data frame\n", + "Eva.columns=[\"CLASS\"] #Naming the column\n", + "Eva.index.name=\"Index\" #Creating a column index\n", + "Eva[\"CLASS\"]=Eva[\"CLASS\"].map({0.0:False,1.0:True}) # Chaninging 0 to \"False\" 1 to \"True\"\n", + "\n", + "Eva.to_csv(\"Amber11_csv\") ## Writing a csv file\n", + "print(Eva['CLASS'].unique())\n", + "print(Eva['CLASS'].nunique())\n", + "\n", + "#printing the numbers of False and True\n", + "print(Eva.groupby('CLASS').size()[0].sum()) #\n", + "print(Eva.groupby('CLASS').size()[1].sum())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 9)Compare Machine Learning Algorithms\n", + "It is important to compare the performance of multiple different machine learning algorithms consistently. The test harness as a template on your own machine learning problems and add more and different algorithms to compare." + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('LR', 0.8353580423831856, 0.27188952844394665)\n", + "('LDA', 0.8535044293903076, 0.2571395669719574)\n", + "('KNN', 0.8027933385443807, 0.2521136100771112)\n", + "('CART', 0.7345470731283654, 0.2898967460848411)\n", + "('NB', 0.880815746048289, 0.11642272449162755)\n", + "('SVM', 0.8350280093798853, 0.25836507020625044)\n", + "('MLPC', 0.8291112992878235, 0.2688132800232323)\n", + "('EXTC', 0.8370375195414278, 0.25047049509079944)\n", + "('GBC', 0.7899437641132534, 0.2887124941351131)\n", + "('RDF', 0.8093625151988884, 0.2921369545256496)\n" + ] + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Compare Algorithms\n", + "from matplotlib import pyplot\n", + "# prepare models and add them to a list\n", + "models = []\n", + "models.append(('LR', LogisticRegression()))\n", + "models.append(('LDA', LinearDiscriminantAnalysis()))\n", + "models.append(('KNN', KNeighborsClassifier()))\n", + "models.append(('CART', DecisionTreeClassifier()))\n", + "models.append(('NB', GaussianNB()))\n", + "models.append(('SVM', SVC()))\n", + "models.append(('MLPC', MLPClassifier()))\n", + "models.append(('EXTC', ExtraTreesClassifier()))\n", + "models.append(('GBC', GradientBoostingClassifier()))\n", + "models.append(('RDF', RandomForestClassifier()))\n", + "# evaluate each model in turn\n", + "results = []\n", + "names = []\n", + "scoring = 'accuracy'\n", + "for name, model in models:\n", + " kfold = KFold(n_splits=10, random_state=42)\n", + " cv_results = cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\n", + " results.append(cv_results)\n", + " names.append(name)\n", + " msg = (name, cv_results.mean(), cv_results.std())\n", + " print(msg)\n", + "\n", + "# boxplot algorithm comparison\n", + "fig = pyplot.figure()\n", + "fig.suptitle('Algorithm Comparison')\n", + "ax = fig.add_subplot(111)\n", + "pyplot.boxplot(results)\n", + "ax.set_xticklabels(names)\n", + "pyplot.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": {}, + "outputs": [], + "source": [ + "# From the alogarithms above the best was the Gausian Naive Bayes with the highest mean value pf 0.88 followed by LDA with 0.85\n", + "# The least fit alogarith was DecisionTreeClassifier(0.73)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.4" + }, + "varInspector": { + "cols": { + "lenName": 16, + "lenType": 16, + "lenVar": 40 + }, + "kernels_config": { + "python": { + "delete_cmd_postfix": "", + "delete_cmd_prefix": "del ", + "library": "var_list.py", + "varRefreshCmd": "print(var_dic_list())" + }, + "r": { + "delete_cmd_postfix": ") ", + "delete_cmd_prefix": "rm(", + "library": "var_list.r", + "varRefreshCmd": "cat(var_dic_list()) " + } + }, + "types_to_exclude": [ + "module", + "function", + "builtin_function_or_method", + "instance", + "_Feature" + ], + "window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/Jupiter Marina.ipynb b/Jupiter Marina.ipynb new file mode 100644 index 0000000..98ca8ae --- /dev/null +++ b/Jupiter Marina.ipynb @@ -0,0 +1 @@ +{"cells":[{"metadata":{},"cell_type":"markdown","source":"KABAHITA JUPITER MARINA\n2019/HD07/24828U\n"},{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nimport sklearn\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n for filename in filenames:\n print(os.path.join(dirname, filename))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Importing data"},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"# Importing data\ntest_data = pd.read_csv(\"/kaggle/input/ace-class-assignment/Test.csv\", header=0, sep=\",\")\namp_train = pd.read_csv(\"/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\", header=0, sep=\",\")\namp_train.head()\n\n\n\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"test_data.head()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## General data attributes and descriptive statistics"},{"metadata":{"trusted":true},"cell_type":"code","source":"#Describing general data attributes\ntrain_dim=amp_train.shape #gets the dimensions of the tranining dataset\ntest_dim= test_data.shape #gets the dimensions of the tesing dataset\nprint(train_dim)\nprint(test_dim)\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"We can see that the test data has one attribute less than the train data set"},{"metadata":{"trusted":true},"cell_type":"code","source":"atr_types=amp_train.dtypes #gets the data type for each column in training dataset\n\natr_types\n\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"amp_train.isnull().sum() # gets the sum of the missing values/observations in each column","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":" All attributes have complete observations"},{"metadata":{"trusted":true},"cell_type":"code","source":"# Descriptive statistics \nstats=amp_train.describe()\nstats","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"From the summary statistics, its visible that some of the attributes like FULL_CHARGE, FULL_AcidicMolPerc and\tFULL_OOBM850104 have outlier values basing on the values of the 75% quartile and maximum values "},{"metadata":{},"cell_type":"markdown","source":"# Class distributions\n\nSometimes, observations from the different classes may not be equal, these may need special handling, so its important to note the class distributions, as if they are uneven, they may bias our model"},{"metadata":{"trusted":true},"cell_type":"code","source":"# CLass distibutions \ncdists= amp_train.groupby('CLASS').size() # groups the observation by the column of class, and counts all the observations including null values\nprint(cdists)\n\n#plots to visualize the class distribution\namp_train.groupby('CLASS').size().plot(kind=\"pie\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"The observations from each class seem8 to be equal"},{"metadata":{},"cell_type":"markdown","source":"# Correlation between the different attributes\nBasically, we need to examine our attributes for correlation as highly correlated attributes present the same data to the algorithm. Removing one may speed learning of the algorithm (less dimensions more speed) and also prevent overfitting of the algorithm"},{"metadata":{"trusted":true},"cell_type":"code","source":"# Correlation between attributes \ncorrelations = amp_train.corr(method=\"pearson\") # calculates pairwaise correlation for the attributes \ncorrelations\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"FULL_AURR980107 and FULL_AcidicMolPerc have a correlation coefficent of 0.79, this might mean these two attributes may be some what correlated. Same goes for AS_DAYM780201 and FULL_DAYM780201 (correlation coefficient is 0.894191)"},{"metadata":{"trusted":true},"cell_type":"code","source":"# Plots to visualize the correlations\nfrom matplotlib import rcParams\nsns.heatmap(correlations, annot=True)\nrcParams['figure.figsize'] = (11.7,8.27)\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Data skewness\n\nMost machine learning algorithms assume that data from the attributes is normally distributed, so identifying attributes with data that has a left or right skew, can be important as this can be easily corrected"},{"metadata":{"trusted":true},"cell_type":"code","source":"sk = amp_train.skew() # calculates the skew for each attribute\nsk","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Negative values like those of FULL_DAYM780201, FULL_OOBM850104,AS_DAYM780201, AS_FUKS010112, indicate that these attributes have values skewed more to the left\nValues closer to zero are indicative of a less or no skew, while positive values would mean that that particular attribute is skewed more to the right"},{"metadata":{},"cell_type":"markdown","source":" # Visualising data distributions with plots"},{"metadata":{"trusted":true},"cell_type":"code","source":"# Plot one, histogram to show the distributions\namp_train.hist(layout=(4,3), figsize=(16,16))\nplt.subplots_adjust(wspace=0.4, hspace=0.5)\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Plot two density plots can show the distributions better\namp_train.plot(kind=\"density\",subplots=True,layout=(4,3),sharex=False,sharey=False, figsize=(16,16))\n#amp_train.plot(kind=\"density\",subplots=False,layout=(4,3),sharex=True,sharey=True)\nplt.show()\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Distributions for AS_MeanAmphiMoment,FULL_AcidicMolPerc and NT_EFC195 dont look so good"},{"metadata":{},"cell_type":"markdown","source":"# Data transformations\nUsing squaring to transform the attributes with negative values into postives"},{"metadata":{"trusted":true},"cell_type":"code","source":"\nneg1=amp_train.iloc[:,0]\ntneg1=neg1**2\ntneg1.plot(kind=\"density\")\n\namp_train.iloc[:,0]=tneg1\n\nneg2=amp_train.iloc[:,5]\ntneg2=neg2**2\ntneg2.plot(kind=\"density\")\namp_train.iloc[:,5]=tneg2\n\n## test\nneg3=test_data.iloc[:,0]\ntneg3=neg3**2\ntneg3.plot(kind=\"density\")\ntest_data.iloc[:,0]=tneg3\n\n\n\nneg4=test_data.iloc[:,5]\ntneg4=neg4**2\ntneg4.plot(kind=\"density\")\ntest_data.iloc[:,5]=tneg4","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Feature selection\n\n\n"},{"metadata":{"trusted":true},"cell_type":"code","source":" #test one selecting out features with low variance\nfrom sklearn.feature_selection import VarianceThreshold\nsel = VarianceThreshold(threshold=(.8 * (1 - .8)))\nk=sel.fit_transform(amp_train)\nnames=amp_train.columns[sel.get_support(indices=True)]\nprint(k.shape)\namp_train2=pd.DataFrame(k,columns=names)\namp_train2.head()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"After selecting out features with low variance, only 8 attribute remained "},{"metadata":{"trusted":true},"cell_type":"code","source":"#test two using sklearn with a chi square test\n\nfrom sklearn.feature_selection import SelectKBest\nfrom sklearn.feature_selection import chi2\n\ntest_array = amp_train2.values\n\ntest_atr = test_array[:,0:7]\nclass_atr = test_array[:,7]\n\n\ntest = SelectKBest(score_func=chi2, k=5)\nfit = test.fit(test_atr, class_atr)\n\n\nprint(fit.scores_)\nfeatures = fit.transform(test_atr)\nnames2=amp_train2.columns[fit.get_support(indices=True)]\namp_train3=pd.DataFrame(features,columns=names2)\namp_train3.iloc[:5,]\nprint(names2)\n\n\n\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Test three Recursive feature elimination\n\nfrom sklearn.feature_selection import RFE\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.ensemble import RandomForestClassifier\n\nmodel1 = LogisticRegression()\nmodel2=RandomForestClassifier()\n\nrfe = RFE(model1, 5)\nfit2 = rfe.fit(test_atr, class_atr)\nfeatures2 = fit2.transform(test_atr)\n\nrfe2= RFE(model2, 5)\nfit3 = rfe2.fit(test_atr, class_atr)\n\n\n\n\nnames3= set(amp_train2.columns[fit2.get_support(indices=True)])\n\nnames4= set(amp_train2.columns[fit3.get_support(indices=True)])\n\nnames2=set(names2)\n\ncomn=names2&names3&names4 ### identifies features common to all the feature selection methods used\ncomn\n\nimport collections\n\ncomn=collections.deque(comn)\ncomn.appendleft(\"FULL_Charge\")\ncomn\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Getting the indices of the chosen attributes"},{"metadata":{"trusted":true},"cell_type":"code","source":"\nindice=[]\n\nfor index,name in enumerate(amp_train.columns):\n for sub_name in comn:\n if name==sub_name:\n indice.append(index)\nindice\n ","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Subsetting the data for the chosen attributes "},{"metadata":{"trusted":true},"cell_type":"code","source":"amp_train = pd.read_csv(\"/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\", header=0, sep=\",\")\n\n\ntest_amp =amp_train.iloc[:,[0,1,3,5,7,11]]\n\ntest_amp.head()\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import train_test_split\nfrom sklearn.model_selection import KFold\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.metrics import confusion_matrix\n\n\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.svm import SVC\nfrom sklearn.neighbors import KNeighborsClassifier\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Logistic regression using cross validation"},{"metadata":{"trusted":true},"cell_type":"code","source":"\nX=test_amp.iloc[:,0:5]\nY=test_amp.iloc[:,5]\nfolds=10\nkfold = KFold(n_splits=folds, random_state=7, shuffle=True,)\nmodel = LogisticRegression()\nresults = cross_val_score(model, X, Y, cv=kfold)\n\nprint((\"Accuracy: %.3f%% (%.3f%%)\") % (results.mean()*100.0, results.std()*100.0))\n\n\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Model one\n ## Logistic regression with a test train split using 5 features\n "},{"metadata":{"trusted":true},"cell_type":"code","source":"test_amp =amp_train.values[:,[0,1,3,5,7,11]]\nfrom sklearn.metrics import matthews_corrcoef\nX=test_amp[:,0:5]\nY=test_amp[:,5]\n\n#Training data spliting \n\ntest_size = 0.4\nseed = 42\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\n\n#model training \n\nmodel1 = LogisticRegression()\nmodel1.fit(X_train, Y_train)\n\n# predicting\n\npredicted = model1.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult1 = model1.score(X_test, Y_test)\n\n# Results accuracy \n\nprint(\"Accuracy: \", (result1*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model1.predict(X_test),Y_test))\nmcc1=matthews_corrcoef(model1.predict(X_test),Y_test)\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":" # Model two\n## Gausian/Naive Bayes using five features "},{"metadata":{"trusted":true},"cell_type":"code","source":"test_amp =amp_train.values[:,[0,1,3,5,7,11]]\nfrom sklearn.metrics import matthews_corrcoef\nX=test_amp[:,0:5]\nY=test_amp[:,5]\n\n#Training data spliting \n\ntest_size = 0.4\nseed = 42\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\n\n#model training \n\nmodel2 = GaussianNB()\nmodel2.fit(X_train, Y_train)\n\n# predicting\n\npredicted = model2.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult2 = model2.score(X_test, Y_test)\n\n# Results accuracy \n\nprint(\"Accuracy: \", (result2*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model2.predict(X_test),Y_test))\nmcc2=matthews_corrcoef(model2.predict(X_test),Y_test)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Model three\n## Linear Discriminant Analysis using five features "},{"metadata":{"trusted":true},"cell_type":"code","source":"test_amp =amp_train.values[:,[0,1,3,5,7,11]]\nfrom sklearn.metrics import matthews_corrcoef\nX=test_amp[:,0:5]\nY=test_amp[:,5]\n\n#Training data spliting \n\ntest_size = 0.4\nseed = 42\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\n\n#model training \n\nmodel3=LinearDiscriminantAnalysis()\nmodel3.fit(X_train, Y_train)\n\n# predicting\n\npredicted = model3.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult3 = model3.score(X_test, Y_test)\n\n# Results accuracy \n\nprint(\"Accuracy: \", (result3*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model3.predict(X_test),Y_test))\n\nmcc3=matthews_corrcoef(model3.predict(X_test),Y_test)\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Model four \n ## Support Vector Machines with five features"},{"metadata":{"trusted":true},"cell_type":"code","source":"test_amp =amp_train.values[:,[0,1,3,5,7,11]]\nfrom sklearn.metrics import matthews_corrcoef\nX=test_amp[:,0:5]\nY=test_amp[:,5]\n\n#Training data spliting \n\ntest_size = 0.4\nseed = 42\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\n\n#model training \n\nmodel4=SVC()\nmodel4.fit(X_train, Y_train)\n\n# predicting\n\npredicted = model4.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult4 = model4.score(X_test, Y_test)\n\n# Results accuracy \n\nprint(\"Accuracy: \", (result4*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model4.predict(X_test),Y_test))\n\n\nmcc4=matthews_corrcoef(model4.predict(X_test),Y_test)\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# model 5\n ## K-Nearest neighbours with five features\n "},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.neighbors import KNeighborsClassifier\nmodel5 = KNeighborsClassifier(n_neighbors=5)\n#Training data spliting \n\ntest_size = 0.4\nseed = 42\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\n\n#model training \n\nmodel5.fit(X_train, Y_train)\n\n# predicting\n\npredicted = model5.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult5 = model5.score(X_test, Y_test)\n\n# Results accuracy \n\nprint(\"Accuracy: \", (result5*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model5.predict(X_test),Y_test))\n\nmcc5=matthews_corrcoef(model5.predict(X_test),Y_test)\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Model six\n ## Centroid clasifier "},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.neighbors import NearestCentroid\nmodel6 = NearestCentroid()\n#Training data spliting \n\ntest_size = 0.4\nseed = 42\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\n\n#model training \n\nmodel6.fit(X_train, Y_train)\n\n# predicting\n\npredicted = model6.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult6 = model6.score(X_test, Y_test)\n\n# Results accuracy \n\nprint(\"Accuracy: \", (result6*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model6.predict(X_test),Y_test))\n\nmcc6=matthews_corrcoef(model6.predict(X_test),Y_test)\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Model seven\n\n## Decision trees with five features \n"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn import tree\n#Training data spliting \n\ntest_size = 0.4\nseed = 42\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\n\n#model training \n\nmodel7=tree.DecisionTreeClassifier()\nmodel7.fit(X_train, Y_train)\n\n# predicting\n\npredicted = model7.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult7 = model7.score(X_test, Y_test)\n\n# Results accuracy \n\nprint(\"Accuracy: \", (result7*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model7.predict(X_test),Y_test))\nmcc7=matthews_corrcoef(model7.predict(X_test),Y_test)\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Model eight \n## Randomised tree"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.ensemble import RandomForestClassifier\nmodel8 =RandomForestClassifier()\n#Training data spliting \n\ntest_size = 0.4\nseed = 42\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\n\n#model training \n\nmodel8.fit(X_train, Y_train)\n\n# predicting\n\npredicted = model8.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult8 = model8.score(X_test, Y_test)\n\n# Results accuracy \n\nprint(\"Accuracy: \", (result8*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model8.predict(X_test),Y_test))\n\n\nmcc8=matthews_corrcoef(model8.predict(X_test),Y_test)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Model nine \n ## Gradient tree boosting\n"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.ensemble import GradientBoostingClassifier\nmodel9 =GradientBoostingClassifier()\n\n#Training data spliting \n\ntest_size = 0.4\nseed = 42\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\n\n#model training \n\nmodel9.fit(X_train, Y_train)\n\n# predicting\n\npredicted = model9.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult9 = model9.score(X_test, Y_test)\n\n# Results accuracy \n\nprint(\"Accuracy: \", (result9*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model9.predict(X_test),Y_test))\n\nmcc9=matthews_corrcoef(model9.predict(X_test),Y_test)\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Model ten\n## Stochastic Gradient Descent "},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.linear_model import SGDClassifier\nmodel10 = SGDClassifier()\n\n#Training data spliting \n\ntest_size = 0.4\nseed = 42\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,random_state=seed, shuffle=True)\n\n#model training \n\nmodel10.fit(X_train, Y_train)\n\n# predicting\n\npredicted = model10.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult10 = model10.score(X_test, Y_test)\n\n# Results accuracy \n\nprint(\"Accuracy: \", (result10*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model10.predict(X_test),Y_test))\n\n\nmcc10=matthews_corrcoef(model10.predict(X_test),Y_test)\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"compare=[result1,result2,result3,result4,result5,result6,result7,result8,result9,result10]\n\ncompare=pd.DataFrame(compare).T\n\ncompare=compare.rename(columns={0:\"LGR\", 1:\"GNB\", 2:\"LDN\", 3:\"SVM\", 4:\"KNN\", 5:\"CCL\", 6:\"DCS\", 7:\"RDT\", 8:\"GBT\", 9:\"SGD\"})\n\ncompareMCC=[mcc1,mcc2,mcc3,mcc4,mcc5,mcc6,mcc7,mcc8,mcc9,mcc10]\ncompareMCC=pd.DataFrame(compareMCC).T\ncompareMCC=compareMCC.rename(columns={0:\"LGR\", 1:\"GNB\", 2:\"LDN\", 3:\"SVM\", 4:\"KNN\", 5:\"CCL\", 6:\"DCS\", 7:\"RDT\", 8:\"GBT\", 9:\"SGD\"})\n\ncompare=compare.append(compareMCC)\n#compare.plot(kind=\"box\")\n#plt.plot(\"Mean of MCC and Accuracy\",\"Different models\", data=compare)\n\n\ncompare=compare.values\n\nfig = plt.figure()\nax = fig.add_subplot(111)\nax.boxplot(compare)\nplt.xticks([1, 2, 3,4,5,6,7,8,9,10], [\"LGR\",\"GNB\",\"LDN\",\"SVM\",\"KNN\",\"CCL\",\"DCS\",\"RDT\",\"GBT\",\"SGD\"])\n\n\n\nax.set_title('A comparison of the different Accuracies and MCC from the different Models')\nax.set_xlabel('The different Models')\nax.set_ylabel('Mean of Accuracy and MCC')\nplt.show()\n\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Predicting from the test data"},{"metadata":{"trusted":true},"cell_type":"code","source":"\ntest_data = pd.read_csv(\"/kaggle/input/ace-class-assignment/Test.csv\", header=0, sep=\",\")\ntest_data2=test_data.values[:,[0,1,3,5,7]]","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### Predictions from logistic Regression"},{"metadata":{"trusted":true},"cell_type":"code","source":"model1.fit(X,Y) ## retrains the algorithm again on the entire train data set\nkj_results=model1.predict(test_data2)\n\ndf = pd.DataFrame(kj_results)\ndf.columns = ['CLASS']\ndf.index.name = 'Index'\ndf['CLASS']=df['CLASS'].map({0.0:False,1.0:True})\ndf.to_csv(\"kjLGR.csv\")\ndf[\"CLASS\"].unique()\nprint(df.groupby(\"CLASS\").size()[0].sum())\nprint(df.groupby(\"CLASS\").size()[1].sum())\ndf['CLASS'].value_counts()\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Score from the leader board using this prediction is 0.82503"},{"metadata":{},"cell_type":"markdown","source":"## Predicting using Gausssian"},{"metadata":{"trusted":true},"cell_type":"code","source":"model2.fit(X,Y) ## retrains the algorithm again on the entire train data set\nkj_results=model2.predict(test_data2)\n\ndf = pd.DataFrame(kj_results)\ndf.columns = ['CLASS']\ndf.index.name = 'Index'\ndf['CLASS']=df['CLASS'].map({0.0:False,1.0:True})\ndf.to_csv(\"kjGNB.csv\")\ndf[\"CLASS\"].unique()\nprint(df.groupby(\"CLASS\").size()[0].sum())\nprint(df.groupby(\"CLASS\").size()[1].sum())\ndf['CLASS'].value_counts()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Score on leader board using this prediction was 0.84591"},{"metadata":{},"cell_type":"markdown","source":"# Predicting using Support Vector Machines "},{"metadata":{"trusted":true},"cell_type":"code","source":"model4.fit(X,Y) ## retrains the algorithm again on the entire train data set\nkj_results=model4.predict(test_data2)\n\ndf = pd.DataFrame(kj_results)\ndf.columns = ['CLASS']\ndf.index.name = 'Index'\ndf['CLASS']=df['CLASS'].map({0.0:False,1.0:True})\ndf.to_csv(\"kjSVM.csv\")\ndf[\"CLASS\"].unique()\nprint(df.groupby(\"CLASS\").size()[0].sum())\nprint(df.groupby(\"CLASS\").size()[1].sum())\ndf['CLASS'].value_counts()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Score on leader board using this prediction was 0.82136"},{"metadata":{},"cell_type":"markdown","source":"## Predicting using the randomised tree classifier"},{"metadata":{"trusted":true},"cell_type":"code","source":"model8.fit(X,Y) ## retrains the algorithm again on the entire train data set\nkj_results=model8.predict(test_data2)\n\ndf = pd.DataFrame(kj_results)\ndf.columns = ['CLASS']\ndf.index.name = 'Index'\ndf['CLASS']=df['CLASS'].map({0.0:False,1.0:True})\ndf.to_csv(\"kjRDT.csv\")\ndf[\"CLASS\"].unique()\nprint(df.groupby(\"CLASS\").size()[0].sum())\nprint(df.groupby(\"CLASS\").size()[1].sum())\ndf['CLASS'].value_counts()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Score on leader board using this prediction was 0.80561"},{"metadata":{},"cell_type":"markdown","source":"## Predicting using the Gradient tree boosting classifier "},{"metadata":{"trusted":true},"cell_type":"code","source":"model9.fit(X,Y) ## retrains the algorithm again on the entire train data set\nkj_results=model9.predict(test_data2)\n\ndf = pd.DataFrame(kj_results)\ndf.columns = ['CLASS']\ndf.index.name = 'Index'\ndf['CLASS']=df['CLASS'].map({0.0:False,1.0:True})\ndf.to_csv(\"kjGBT.csv\")\ndf[\"CLASS\"].unique()\nprint(df.groupby(\"CLASS\").size()[0].sum())\nprint(df.groupby(\"CLASS\").size()[1].sum())\ndf['CLASS'].value_counts()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Score on leader board using this prediction was 0.79678"},{"metadata":{},"cell_type":"markdown","source":"Random forest and Gradient boosting classifiers had the highest accuracies during training but gave the least scores on the leader board\n\nGausian gave the highest score"},{"metadata":{},"cell_type":"markdown","source":"# More with the gausian "},{"metadata":{},"cell_type":"markdown","source":"## Using gausian with more features"},{"metadata":{},"cell_type":"markdown","source":"## Using gausian with eight features "},{"metadata":{"trusted":true},"cell_type":"code","source":"amp_train = pd.read_csv(\"/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\", header=0, sep=\",\")\ntest_data = pd.read_csv(\"/kaggle/input/ace-class-assignment/Test.csv\", header=0, sep=\",\")\n\n#selecting out features with low variance\nfrom sklearn.feature_selection import VarianceThreshold\nsel = VarianceThreshold(threshold=(.8 * (1 - .8)))\nk=sel.fit_transform(amp_train)\nnames=amp_train.columns[sel.get_support(indices=True)]\nprint(k.shape)\namp_train2=pd.DataFrame(k,columns=names)\n#print(amp_train2)\n\nn=sel.fit_transform(test_data)\nnames2=test_data.columns[sel.get_support(indices=True)]\ntest_data=pd.DataFrame(n,columns=names2)\ntest_data2=test_data.values\n\n#print(test_data)\n\n### data \ntest_amp =amp_train2.values\nX=test_amp[:,0:7]\nY=test_amp[:,7]\n\n\n\n\n#model\nmodel=GaussianNB()\nfrom sklearn.metrics import matthews_corrcoef\ntest_size = 0.4\nseed = 42\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\nrandom_state=seed, shuffle=\"True\")\nmodel.fit(X_train, Y_train)\npredicted = model.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult = model.score(X_test, Y_test)\nprint(\"Accuracy: \", (result*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model.predict(X_test),Y_test)) \nmodel.fit(X,Y)\nkj_resultsg8=model.predict(test_data)\n\n\n#### results \n\ndf = pd.DataFrame(kj_resultsg8)\ndf.columns = ['CLASS']\ndf.index.name = 'Index'\ndf['CLASS']=df['CLASS'].map({0.0:False,1.0:True})\n\ndf.to_csv(\"kjGNB8.csv\")\ndf[\"CLASS\"].unique()\nprint(df.groupby(\"CLASS\").size()[0].sum())\nprint(df.groupby(\"CLASS\").size()[1].sum())\ndf['CLASS'].value_counts()\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"MCC value for the Gaussian with 8 features and that with 5 features are almost the same, but the leaderboard score using the gausian with 8 features was 0.86379, which is an improvement over the 0.84 score from the five features"},{"metadata":{},"cell_type":"markdown","source":"## Using gaussian with all attributes "},{"metadata":{"trusted":true},"cell_type":"code","source":"amp_train = pd.read_csv(\"/kaggle/input/ace-class-assignment/AMP_TrainSet.csv\", header=0, sep=\",\")\ntest_data = pd.read_csv(\"/kaggle/input/ace-class-assignment/Test.csv\", header=0, sep=\",\")\n\n\n### data \ntest_amp =amp_train.values\nX=test_amp[:,0:11]\nY=test_amp[:,11]\n\n\n#model\nmodel=GaussianNB()\nfrom sklearn.metrics import matthews_corrcoef\ntest_size = 0.4\nseed = 42\nX_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size,\nrandom_state=seed)\nmodel.fit(X_train, Y_train)\npredicted = model.predict(X_test)\nmatrix = confusion_matrix(Y_test, predicted)\nresult = model.score(X_test, Y_test)\nprint(\"Accuracy: \", (result*100.0))\nprint(matrix)\nprint('MCC: ', matthews_corrcoef(model.predict(X_test),Y_test)) \nmodel.fit(X,Y)\n\nkj_resultsg12=model.predict(test_data)\n\n\n#### results \n\ndf = pd.DataFrame(kj_resultsg12)\ndf.columns = ['CLASS']\ndf.index.name = 'Index'\ndf['CLASS']=df['CLASS'].map({0.0:False,1.0:True})\n\ndf.to_csv(\"kjGNB11.csv\")\ndf[\"CLASS\"].unique()\nprint(df.groupby(\"CLASS\").size()[0].sum())\nprint(df.groupby(\"CLASS\").size()[1].sum())\ndf['CLASS'].value_counts()\n\n","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Score from the leaderboard using all features was 0.99559"},{"metadata":{},"cell_type":"markdown","source":"References\n\n\n1. https://realpython.com/logistic-regression-python/\n2. https://www.tutorialspoint.com/machine_learning_with_python/machine_learning_with_python_extra_trees.htm\n3. https://stackabuse.com/gradient-boosting-classifiers-in-python-with-scikit-learn/\n4. https://machinelearningmastery.com/stochastic-gradient-boosting-xgboost-scikit-learn-python/\n5. https://machinelearningmastery.com/stochastic-gradient-boosting-xgboost-scikit-learn-python/\n6. https://machinelearningmastery.com/compare-machine-learning-algorithms-python-scikit-learn/\n7. https://machinelearningmastery.com/master-machine-learning-algorithms/\n8. https://machinelearningmastery.com/compare-machine-learning-algorithms-python-scikit-learn/\n9. https://github.com/search?q=data-analysis-and-visualization-with-python&type=Repositories\n10. https://stackabuse.com/applying-filter-methods-in-python-for-feature-selection/\n11. https://towardsdatascience.com/decision-tree-in-machine-learning-e380942a4c96\n12. https://machinelearningmastery.com/master-machine-learning-algorithms/\n13. https://machinelearningmastery.com/compare-machine-learning-algorithms-python-scikit-learn/\n\n"}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4} \ No newline at end of file From e9a1d188ffc833f183be7bd723b3fef4b370f6ed Mon Sep 17 00:00:00 2001 From: Mugume Twinamatsiko Atwine Date: Tue, 21 Apr 2020 20:28:14 +0300 Subject: [PATCH 29/29] Created using Colaboratory --- Dimensionality_Reduction_DataCamp.ipynb | 1103 +++++++++++++++++++++++ 1 file changed, 1103 insertions(+) create mode 100644 Dimensionality_Reduction_DataCamp.ipynb diff --git a/Dimensionality_Reduction_DataCamp.ipynb b/Dimensionality_Reduction_DataCamp.ipynb new file mode 100644 index 0000000..7a2245f --- /dev/null +++ b/Dimensionality_Reduction_DataCamp.ipynb @@ -0,0 +1,1103 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "name": "Dimensionality Reduction DataCamp", + "provenance": [], + "authorship_tag": "ABX9TyOpbxCKdT5L31c28gvonWQ/", + "include_colab_link": true + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + } + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "view-in-github", + "colab_type": "text" + }, + "source": [ + "\"Open" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Q8DGq2UXFmtZ", + "colab_type": "text" + }, + "source": [ + "## When you want to visually explore the patterns in a high dimensional dataset.\n" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "lSEn6j5J9_sp", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 71 + }, + "outputId": "c293a1bf-47bf-4979-8832-3393bbbab272" + }, + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns" + ], + "execution_count": 1, + "outputs": [ + { + "output_type": "stream", + "text": [ + "/usr/local/lib/python3.6/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n", + " import pandas.util.testing as tm\n" + ], + "name": "stderr" + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "hHvkBmNd-eDf", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#read in the data\n", + "data = pd.read_csv(\"https://assets.datacamp.com/production/repositories/3515/datasets/802fc5cdbe3a29248483e496a966627ea9629e7a/ANSUR_II_FEMALE.csv\")" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "aKVH0pf7-ivt", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 276 + }, + "outputId": "cc307b73-1383-43c0-bff9-19864910f457" + }, + "source": [ + "#look at the head\n", + "data.head(3)" + ], + "execution_count": 3, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
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BranchComponentGenderabdominalextensiondepthsittingacromialheightacromionradialelengthanklecircumferenceaxillaheightballoffootcircumferenceballoffootlengthbiacromialbreadthbicepscircumferenceflexedbicristalbreadthbideltoidbreadthbimalleolarbreadthbitragionchinarcbitragionsubmandibulararcbizygomaticbreadthbuttockcircumferencebuttockdepthbuttockheightbuttockkneelengthbuttockpopliteallengthcalfcircumferencecervicaleheightchestbreadthchestcircumferencechestdepthchestheightcrotchheightcrotchlengthomphalioncrotchlengthposterioromphalionearbreadthearlengthearprotrusionelbowrestheighteyeheightsittingfootbreadthhorizontalfootlengthforearmcenterofgriplength...kneeheightsittinglateralfemoralepicondyleheightlateralmalleolusheightlowerthighcircumferencementonsellionlengthneckcircumferenceneckcircumferencebaseoverheadfingertipreachsittingpalmlengthpoplitealheightradialestylionlengthshouldercircumferenceshoulderelbowlengthshoulderlengthsittingheightsleevelengthspinewristsleeveoutseamspansuprasternaleheighttenthribheightthighcircumferencethighclearancethumbtipreachtibialheighttragiontopofheadtrochanterionheightverticaltrunkcircumferenceusawaistbacklengthwaistbreadthwaistcircumferencewaistdepthwaistfrontlengthsittingwaistheightomphalionwristcircumferencewristheightweight_kgstature_mBMIBMI_classHeight_class
0Combat SupportRegular ArmyFemale231128230120411802221773733152634666533830114110112238365874763601336274922245109575955731035651622071391246316...4964475540411833536812681133622351062327148803809513164712801013622174736430110844148840629585021734594215275665.71.56026.997041OverweightNormal
1Combat Service SupportRegular ArmyFemale19413793202071292225178372272250430642942701268931869005834833501440261839206123483554932932602320872691249341...53249269334115302345138911042625910143461428358105751751137211075241527714751259011470422254708168329103215581553.41.66519.262506NormalNormal
2Combat Service SupportRegular ArmyFemale183136932923312712371963973002764506930927012898720486158346638414512878742231226821643374366526204790100265343...53046964401135325369141412239825810493621649048555681779138310895771648144581298821542419269727159367103516279966.31.71122.647148NormalTall
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3 rows × 99 columns

\n", + "
" + ], + "text/plain": [ + " Branch Component ... BMI_class Height_class\n", + "0 Combat Support Regular Army ... Overweight Normal\n", + "1 Combat Service Support Regular Army ... Normal Normal\n", + "2 Combat Service Support Regular Army ... Normal Tall\n", + "\n", + "[3 rows x 99 columns]" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 3 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "b0tgs_d2-kSL", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "outputId": "25e1854a-adf0-42f4-8059-de774ed8d161" + }, + "source": [ + "#shape of the data\n", + "data.shape" + ], + "execution_count": 4, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(1986, 99)" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 4 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "cSFn6Dy5-osm", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#lets take only the numeric data\n", + "dt = data.select_dtypes(exclude='object')" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "RKy8oymF_FHb", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "outputId": "02874db7-8fab-4caa-9bcd-98c7e3274115" + }, + "source": [ + "#new shape\n", + "dt.shape" + ], + "execution_count": 6, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(1986, 94)" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 6 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "Lq8CyCvX_RFJ", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#get t-SNE\n", + "from sklearn.manifold import TSNE\n", + "\n", + "m = TSNE(learning_rate=50)\n", + "\n", + "tsne_features = m.fit_transform(dt)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "nTOXOr_EA9qq", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 68 + }, + "outputId": "0a74ac0c-922c-4f36-e7db-27feb549c1c7" + }, + "source": [ + "#it reduces the features into a two dimensional one.\n", + "tsne_features[1:4,:]" + ], + "execution_count": 8, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "array([[ -4.6460032, -40.48791 ],\n", + " [-19.894072 , -27.56942 ],\n", + " [-24.738132 , 7.966632 ]], dtype=float32)" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 8 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "6d57vuFdGnHX", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 500 + }, + "outputId": "7c7ff86f-6e42-4f93-9920-f2c361b11c2a" + }, + "source": [ + "plt.figure(figsize=(12,8))\n", + "plt.scatter(x=tsne_features[:,0],y=tsne_features[:,1])\n", + "\n", + "#I have to find a way to put these results in the dt dataframe and work with them there\n", + "#I would want to visualize how heigh affects the distribution e.t.c" + ], + "execution_count": 10, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 10 + }, + { + "output_type": "display_data", + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "U6pFJduuG1DY", + "colab_type": "code", + "colab": {} + }, + "source": [ + "" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "OndV7f7ILZUY", + "colab_type": "code", + "colab": {} + }, + "source": [ + "" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3-H1pSkrLaHX", + "colab_type": "text" + }, + "source": [ + "# Removing Features\n", + "\n", + "1 -Variance Threshold\n", + "\n", + "2 -High number of missing values." + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "_EtuAT8LLgcY", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1000 + }, + "outputId": "d7448d8f-5086-46e5-c70b-d484589fd870" + }, + "source": [ + "#let's draw the boxplot to show variance\n", + "#variance is affected by different scales of data so we normalize the data by dividing by the mean\n", + "dt_norm = dt/dt.mean()\n", + "plt.figure(figsize = (18,14))\n", + "dt_norm.boxplot()\n", + "plt.xticks(rotation='vertical')\n", + "#we can see the variance normalized at 10" + ], + "execution_count": 46, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,\n", + " 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34,\n", + " 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51,\n", + " 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68,\n", + " 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85,\n", + " 86, 87, 88, 89, 90, 91, 92, 93, 94]),\n", + " )" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 46 + }, + { + "output_type": "display_data", + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "qYIMp9BtMNf6", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 357 + }, + "outputId": "2669168e-5abf-458c-f353-cc74e1d90c51" + }, + "source": [ + "#let's see the variances of all the features\n", + "list(dt_norm.var().sort_values(ascending=False))[:20]" + ], + "execution_count": 34, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "[0.026281388190225897,\n", + " 0.021689614994511382,\n", + " 0.01877197853310506,\n", + " 0.01875529617208825,\n", + " 0.016963347661495994,\n", + " 0.013473994470864599,\n", + " 0.012755787812620725,\n", + " 0.01221022494210274,\n", + " 0.012078548319412467,\n", + " 0.010909104241888172,\n", + " 0.010130786183765356,\n", + " 0.008204608384362806,\n", + " 0.007700789927583826,\n", + " 0.007628374548528208,\n", + " 0.007014264997366014,\n", + " 0.0070079680463572885,\n", + " 0.00695285389983951,\n", + " 0.006869515365066108,\n", + " 0.006738086346872471,\n", + " 0.006634223006816111]" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 34 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "foeUF8AcRHGj", + "colab_type": "code", + "colab": {} + }, + "source": [ + "from sklearn.feature_selection import VarianceThreshold\n", + "\n", + "# Create a VarianceThreshold feature selector\n", + "sel = VarianceThreshold(threshold=0.01)\n", + "\n", + "# Fit the selector to normalized head_df\n", + "sel.fit(dt / dt.mean())\n", + "\n", + "# Create a boolean mask\n", + "mask = sel.get_support()" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "BcTGX-ukSc0V", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#let's take these values that qualify from the dataset\n", + "#having a high variance means the feature spread touches different subcategories.\n", + "data = dt.loc[:,mask]" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "1nmdXHB1Spp-", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 656 + }, + "outputId": "ccc123cf-5e8d-4fcf-ba8a-e55897e1b7e7" + }, + "source": [ + "#let's visualize this in a heatmap\n", + "plt.figure(figsize = (10,8))\n", + "sns.heatmap(data.corr(), center=0, linewidths=1, annot=True, fmt=\".2f\")" + ], + "execution_count": 39, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 39 + }, + { + "output_type": "display_data", + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "Eryh7wciVtuJ", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# Create the correlation matrix\n", + "corr = data.corr()\n", + "\n", + "# Generate a mask for the upper triangle \n", + "mask = np.triu(np.ones_like(corr, dtype=bool))" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "z8SQ2YDgXL3p", + "colab_type": "text" + }, + "source": [ + "# Notes:\n", + "Features that are perfects correlated: positive or negative bring no new information to the model but increase the complexity of the model we have to drop one.\n", + "\n", + "Strong correlation does not imply causation.\n", + "\n", + "Make sure you visually look at the diagrams of the scatter plots to see the relationship in the variables because sometimes its non linear and still the correlation is high, e.g in the image.\n", + "\n", + "---\n", + "\n", + "We can drop highly correlated features like this:\n", + "\n", + "\n", + "\n", + "```\n", + "# Calculate the correlation matrix and take the absolute value\n", + "corr_matrix = ansur_df.corr().abs()\n", + "\n", + "# Create a True/False mask and apply it\n", + "mask = np.triu(np.ones_like(corr_matrix, dtype=bool))\n", + "tri_df = corr_matrix.mask(mask)\n", + "\n", + "# List column names of highly correlated features (r > 0.95)\n", + "to_drop = [c for c in tri_df.columns if any(tri_df[c] > 0.95)]\n", + "\n", + "# Drop the features in the to_drop list\n", + "reduced_df = ansur_df.drop(to_drop, axis=1)\n", + "\n", + "print(\"The reduced_df dataframe has {} columns\".format(reduced_df.shape[1]))\n", + "\n", + "```\n", + "\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "1FobyjoRWAum", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 639 + }, + "outputId": "ac4b12f4-d579-41ff-98a1-c9a47d3e4b6d" + }, + "source": [ + "# Add the mask to the heatmap\n", + "plt.figure(figsize = (12,8))\n", + "sns.heatmap(corr, mask=mask, center=0, linewidths=1, annot=True, fmt=\".2f\")\n", + "plt.show()" + ], + "execution_count": 42, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "SVFa58q3WIR7", + "colab_type": "code", + "colab": {} + }, + "source": [ + "" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "MS8nE2xic_PG", + "colab_type": "text" + }, + "source": [ + "#Select Features based on Importance.\n", + "\n", + "## RFE:-\n", + "\n", + "How does it work?\n", + "\n", + "It is applied on linear algorithms that have feature coefficients as we shall see below.\n", + "\n", + "It then removes each feature that has tending to 0 coefficient one by one.\n", + "\n", + "```\n", + "from sklearn.preprocessing import StandardScaler\n", + "\n", + "scaler = StandardScaler()\n", + "\n", + "# Fit the scaler on the training features and transform these in one go\n", + "X_train_std = scaler.fit_transform(X_train)\n", + "\n", + "# Fit the logistic regression model on the scaled training data\n", + "lr.fit(X_train_std, y_train)\n", + "\n", + "# Scale the test features\n", + "X_test_std = scaler.transform(X_test)\n", + "\n", + "# Predict diabetes presence on the scaled test set\n", + "y_pred = lr.predict(X_test_std)\n", + "\n", + "# Prints accuracy metrics and feature coefficients\n", + "print(\"{0:.1%} accuracy on test set.\".format(accuracy_score(y_test, y_pred))) \n", + "print(dict(zip(X.columns, abs(lr.coef_[0]).round(2))))\n", + "\n", + "```" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "PWXlZoYGe9EO", + "colab_type": "code", + "colab": {} + }, + "source": [ + "" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "-wyn0PnqjdjA", + "colab_type": "text" + }, + "source": [ + "\n", + "\n", + "```\n", + "# Set the feature eliminator to remove 2 features on each step\n", + "rfe = RFE(estimator=RandomForestClassifier(), n_features_to_select=2, step=2, verbose=1)\n", + "\n", + "# Fit the model to the training data\n", + "rfe.fit(X_train, y_train)\n", + "\n", + "# Create a mask\n", + "mask = rfe.support_\n", + "\n", + "# Apply the mask to the feature dataset X and print the result\n", + "reduced_X = X.loc[:, mask]\n", + "print(reduced_X.columns)\n", + "```\n", + "\n" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "bwThjfxbjhiH", + "colab_type": "code", + "colab": {} + }, + "source": [ + "" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "qnV8zH1Uo2gQ", + "colab_type": "text" + }, + "source": [ + "# Feature Extraction\n", + "\n", + "Calculating New features from the old" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "bdHhkPgQo8SK", + "colab_type": "code", + "colab": {} + }, + "source": [ + "" + ], + "execution_count": 0, + "outputs": [] + } + ] +} \ No newline at end of file