diff --git a/Assignment Colab/.ipynb_checkpoints/Kakembo_Fredrick_notebook-checkpoint.ipynb b/Assignment Colab/.ipynb_checkpoints/Kakembo_Fredrick_notebook-checkpoint.ipynb
new file mode 100644
index 0000000..e7bf879
--- /dev/null
+++ b/Assignment Colab/.ipynb_checkpoints/Kakembo_Fredrick_notebook-checkpoint.ipynb	
@@ -0,0 +1,2863 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<div class = 'alert alert-info'>\n",
+    "    Use your markdown better.\n",
+    "    \n",
+    "# Guidance template \n",
+    "\n",
+    "Python Project Template\n",
+    "1. Prepare Problem\n",
+    "\n",
+    "    a). Load libraries\n",
+    "\n",
+    "    b). Load dataset\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "metadata": {},
+   "source": [
+    "#Guidance template \n",
+    "\n",
+    "# Python Project Template\n",
+    "# 1. Prepare Problem\n",
+    "# a) Load libraries\n",
+    "# b) Load dataset\n",
+    "\n",
+    "# 2. Summarize Data\n",
+    "# a) Descriptive statistics\n",
+    "# b) Data visualizations\n",
+    "\n",
+    "# 3. Prepare Data\n",
+    "# a) Data Cleaning\n",
+    "# b) Feature Selection\n",
+    "# c) Data Transforms\n",
+    "\n",
+    "# 4. Evaluate Algorithms\n",
+    "# a) Split-out validation dataset\n",
+    "# b) Test options and evaluation metric\n",
+    "# c) Spot Check Algorithms\n",
+    "# d) Compare Algorithms\n",
+    "\n",
+    "# 5. Improve Accuracy\n",
+    "# a) Algorithm Tuning\n",
+    "# b) Ensembles\n",
+    "\n",
+    "# 6. Finalize Model\n",
+    "# a) Predictions on validation dataset\n",
+    "# b) Create standalone model on entire training dataset\n",
+    "# c) Save model for later use"
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "metadata": {},
+   "source": [
+    "## 1. Preparing my Data Problem\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Python: 3.7.4 (default, Aug 13 2019, 15:17:50) \n",
+      "[Clang 4.0.1 (tags/RELEASE_401/final)]\n",
+      "Scipy: 1.3.1\n",
+      "Pandas:  0.24.2\n",
+      "numpy: 1.17.4\n",
+      "Matplotlib:  3.1.0\n",
+      "Seaborn:  0.9.0\n",
+      "scikit-learn:  0.22.1\n"
+     ]
+    }
+   ],
+   "source": [
+    "#Loading the required libraries and printing the versions used\n",
+    "#Versions are very helpful for reproducibility purposes\n",
+    "\n",
+    "#Ignoring any annoying errors from my cells\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore')\n",
+    "\n",
+    "#Python version\n",
+    "import sys\n",
+    "print('Python: {}'.format(sys.version))\n",
+    "\n",
+    "#Scipy\n",
+    "import scipy\n",
+    "print(\"Scipy: {}\".format(scipy.__version__))\n",
+    "\n",
+    "import pandas as pd #This is for reading and manipulating tabular data \n",
+    "print('Pandas:  {}'.format(pd.__version__))\n",
+    "\n",
+    "import numpy as np  #This is for numerical computing\n",
+    "print('numpy: {}'.format(np.__version__))\n",
+    "\n",
+    "import matplotlib\n",
+    "import matplotlib.pyplot as plt #Generating simple visualizations\n",
+    "print('Matplotlib:  {}'.format(matplotlib.__version__))\n",
+    "\n",
+    "import seaborn as sns  #for generating statistical plots\n",
+    "print('Seaborn:  {}'.format(sns.__version__))\n",
+    "\n",
+    "# scikit-learn\n",
+    "import sklearn\n",
+    "print('scikit-learn:  {}'.format(sklearn.__version__))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>FULL_Charge</th>\n",
+       "      <th>FULL_AcidicMolPerc</th>\n",
+       "      <th>FULL_AURR980107</th>\n",
+       "      <th>FULL_DAYM780201</th>\n",
+       "      <th>FULL_GEOR030101</th>\n",
+       "      <th>FULL_OOBM850104</th>\n",
+       "      <th>NT_EFC195</th>\n",
+       "      <th>AS_MeanAmphiMoment</th>\n",
+       "      <th>AS_DAYM780201</th>\n",
+       "      <th>AS_FUKS010112</th>\n",
+       "      <th>CT_RACS820104</th>\n",
+       "      <th>CLASS</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>5.0</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.951</td>\n",
+       "      <td>74.842</td>\n",
+       "      <td>0.975</td>\n",
+       "      <td>-3.663</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.282</td>\n",
+       "      <td>73.444</td>\n",
+       "      <td>5.661</td>\n",
+       "      <td>1.041</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>4.0</td>\n",
+       "      <td>5.405</td>\n",
+       "      <td>0.931</td>\n",
+       "      <td>71.595</td>\n",
+       "      <td>0.957</td>\n",
+       "      <td>-4.011</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.600</td>\n",
+       "      <td>68.222</td>\n",
+       "      <td>6.537</td>\n",
+       "      <td>1.453</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>5.5</td>\n",
+       "      <td>5.405</td>\n",
+       "      <td>0.873</td>\n",
+       "      <td>73.595</td>\n",
+       "      <td>0.961</td>\n",
+       "      <td>-2.512</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.593</td>\n",
+       "      <td>69.444</td>\n",
+       "      <td>4.934</td>\n",
+       "      <td>1.722</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>5.0</td>\n",
+       "      <td>4.167</td>\n",
+       "      <td>0.895</td>\n",
+       "      <td>66.250</td>\n",
+       "      <td>0.999</td>\n",
+       "      <td>-1.362</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.614</td>\n",
+       "      <td>67.222</td>\n",
+       "      <td>4.316</td>\n",
+       "      <td>1.382</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>7.5</td>\n",
+       "      <td>8.537</td>\n",
+       "      <td>0.932</td>\n",
+       "      <td>64.720</td>\n",
+       "      <td>0.979</td>\n",
+       "      <td>-2.091</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.616</td>\n",
+       "      <td>72.944</td>\n",
+       "      <td>4.540</td>\n",
+       "      <td>1.539</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>5.0</td>\n",
+       "      <td>7.692</td>\n",
+       "      <td>1.030</td>\n",
+       "      <td>78.949</td>\n",
+       "      <td>0.976</td>\n",
+       "      <td>-3.091</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.511</td>\n",
+       "      <td>78.778</td>\n",
+       "      <td>5.992</td>\n",
+       "      <td>1.091</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>3.0</td>\n",
+       "      <td>6.897</td>\n",
+       "      <td>0.930</td>\n",
+       "      <td>78.586</td>\n",
+       "      <td>0.957</td>\n",
+       "      <td>-3.544</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.385</td>\n",
+       "      <td>78.222</td>\n",
+       "      <td>6.284</td>\n",
+       "      <td>1.467</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2.0</td>\n",
+       "      <td>5.882</td>\n",
+       "      <td>0.868</td>\n",
+       "      <td>76.588</td>\n",
+       "      <td>0.949</td>\n",
+       "      <td>-5.832</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.154</td>\n",
+       "      <td>76.588</td>\n",
+       "      <td>6.479</td>\n",
+       "      <td>1.086</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "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",
+       "\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",
+       "\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  "
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "## Loading my datasets\n",
+    "train_data = pd.read_csv(\"../AMP Data Sets/AMP_TrainSet.csv\")\n",
+    "test_data = pd.read_csv(\"../AMP Data Sets/Test.csv\")\n",
+    "\n",
+    "#Viewing a sample of the data\n",
+    "train_data.head(8)  #The first 8 lines of the training dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>FULL_Charge</th>\n",
+       "      <th>FULL_AcidicMolPerc</th>\n",
+       "      <th>FULL_AURR980107</th>\n",
+       "      <th>FULL_DAYM780201</th>\n",
+       "      <th>FULL_GEOR030101</th>\n",
+       "      <th>FULL_OOBM850104</th>\n",
+       "      <th>NT_EFC195</th>\n",
+       "      <th>AS_MeanAmphiMoment</th>\n",
+       "      <th>AS_DAYM780201</th>\n",
+       "      <th>AS_FUKS010112</th>\n",
+       "      <th>CT_RACS820104</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>4.0</td>\n",
+       "      <td>3.704</td>\n",
+       "      <td>0.873</td>\n",
+       "      <td>73.519</td>\n",
+       "      <td>0.987</td>\n",
+       "      <td>-4.833</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.382</td>\n",
+       "      <td>74.556</td>\n",
+       "      <td>7.225</td>\n",
+       "      <td>1.234</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>4.0</td>\n",
+       "      <td>4.444</td>\n",
+       "      <td>0.892</td>\n",
+       "      <td>62.444</td>\n",
+       "      <td>0.931</td>\n",
+       "      <td>-0.584</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.320</td>\n",
+       "      <td>56.056</td>\n",
+       "      <td>4.942</td>\n",
+       "      <td>1.853</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.901</td>\n",
+       "      <td>47.000</td>\n",
+       "      <td>1.039</td>\n",
+       "      <td>-5.664</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.164</td>\n",
+       "      <td>47.000</td>\n",
+       "      <td>5.969</td>\n",
+       "      <td>1.174</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4.5</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.869</td>\n",
+       "      <td>69.222</td>\n",
+       "      <td>0.982</td>\n",
+       "      <td>-5.423</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.010</td>\n",
+       "      <td>69.222</td>\n",
+       "      <td>5.462</td>\n",
+       "      <td>1.138</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>-4.0</td>\n",
+       "      <td>21.591</td>\n",
+       "      <td>1.061</td>\n",
+       "      <td>71.682</td>\n",
+       "      <td>0.976</td>\n",
+       "      <td>-2.002</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.758</td>\n",
+       "      <td>66.000</td>\n",
+       "      <td>5.582</td>\n",
+       "      <td>1.453</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>4.5</td>\n",
+       "      <td>6.977</td>\n",
+       "      <td>0.895</td>\n",
+       "      <td>68.512</td>\n",
+       "      <td>0.950</td>\n",
+       "      <td>-1.878</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3.090</td>\n",
+       "      <td>72.000</td>\n",
+       "      <td>5.779</td>\n",
+       "      <td>1.844</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>12.0</td>\n",
+       "      <td>3.175</td>\n",
+       "      <td>1.022</td>\n",
+       "      <td>74.460</td>\n",
+       "      <td>1.010</td>\n",
+       "      <td>-3.225</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3.172</td>\n",
+       "      <td>76.722</td>\n",
+       "      <td>5.664</td>\n",
+       "      <td>1.215</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>1.5</td>\n",
+       "      <td>3.704</td>\n",
+       "      <td>0.932</td>\n",
+       "      <td>69.519</td>\n",
+       "      <td>0.977</td>\n",
+       "      <td>-2.509</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.543</td>\n",
+       "      <td>72.000</td>\n",
+       "      <td>4.251</td>\n",
+       "      <td>1.560</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "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",
+       "5          4.5               6.977            0.895           68.512   \n",
+       "6         12.0               3.175            1.022           74.460   \n",
+       "7          1.5               3.704            0.932           69.519   \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",
+       "5            0.950           -1.878          0               3.090   \n",
+       "6            1.010           -3.225          0               3.172   \n",
+       "7            0.977           -2.509          0               2.543   \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  \n",
+       "5         72.000          5.779          1.844  \n",
+       "6         76.722          5.664          1.215  \n",
+       "7         72.000          4.251          1.560  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "test_data.head(8) #Viewing the first 8 observations of the test dataset"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2. Summarizing Data\n",
+    "\n",
+    "### Checking Dimensions of my train data\n",
+    "This is to enable me know the number of rows and columns in my data. This gives an idea of the size of the data (number of observations) as well as the number of features i will have to deal with.\n",
+    "This is done using the `shape` function in pandas\n",
+    "\n",
+    "<div class = 'alert alert-success'>\n",
+    "    Good explanation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 149,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(3038, 12)"
+      ]
+     },
+     "execution_count": 149,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_data.shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "From the output above i have 3,038 observations with 12 features. \n",
+    "\n",
+    "Let me list all the features in my data, using the `columns` function of pandas. This "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 150,
+   "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": 150,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_data.columns  #Listing all the columns i have in my dataset"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Datatypes\n",
+    "Now exploring the datatypes of each feature. This is important because different dtypes are treated diffrently. eg strings its better to convert them to categorical values. \n",
+    "The different data types are got using `dtypes` function\n",
+    "\n",
+    "<div class = 'alert alert-success'>\n",
+    "    Good explanation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "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": 75,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_data.dtypes  #Checking the data types for each faeture"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "From this i can see that almost all my features have float values, a few have values indicated as integers which in actual sense are categorical values ie 0 and 1. For this matter i don't have to do anything much with changing the types of the features.\n",
+    "\n",
+    "<div class = 'alert alert-success'>\n",
+    "    Good explanation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Descriptive Statistics\n",
+    "\n",
+    "Lets generate some discriptive statistics on our data. This will give me a more idea of the kind of data i am dealing with as well as some relationships that may be associated with the different features. This will include generating for things such as;\n",
+    "- Mean, counts, sd, min,max, etc\n",
+    "- Description of the outcome\n",
+    "- \n",
+    "\n",
+    "\n",
+    "<div class = 'alert alert-success'>\n",
+    "    Good explanation.\n",
+    "    What did we learn from this?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 151,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>FULL_Charge</th>\n",
+       "      <th>FULL_AcidicMolPerc</th>\n",
+       "      <th>FULL_AURR980107</th>\n",
+       "      <th>FULL_DAYM780201</th>\n",
+       "      <th>FULL_GEOR030101</th>\n",
+       "      <th>FULL_OOBM850104</th>\n",
+       "      <th>NT_EFC195</th>\n",
+       "      <th>AS_MeanAmphiMoment</th>\n",
+       "      <th>AS_DAYM780201</th>\n",
+       "      <th>AS_FUKS010112</th>\n",
+       "      <th>CT_RACS820104</th>\n",
+       "      <th>CLASS</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>count</td>\n",
+       "      <td>3038.000000</td>\n",
+       "      <td>3038.000000</td>\n",
+       "      <td>3038.000000</td>\n",
+       "      <td>3038.000000</td>\n",
+       "      <td>3038.000000</td>\n",
+       "      <td>3038.000000</td>\n",
+       "      <td>3038.000000</td>\n",
+       "      <td>3038.000000</td>\n",
+       "      <td>3038.000000</td>\n",
+       "      <td>3038.000000</td>\n",
+       "      <td>3038.000000</td>\n",
+       "      <td>3038.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>mean</td>\n",
+       "      <td>2.060237</td>\n",
+       "      <td>8.521520</td>\n",
+       "      <td>0.971410</td>\n",
+       "      <td>73.668760</td>\n",
+       "      <td>0.994007</td>\n",
+       "      <td>-2.432927</td>\n",
+       "      <td>0.088545</td>\n",
+       "      <td>15.683233</td>\n",
+       "      <td>73.650828</td>\n",
+       "      <td>5.911361</td>\n",
+       "      <td>1.235255</td>\n",
+       "      <td>0.500000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>std</td>\n",
+       "      <td>3.819929</td>\n",
+       "      <td>7.586652</td>\n",
+       "      <td>0.107413</td>\n",
+       "      <td>8.527489</td>\n",
+       "      <td>0.031333</td>\n",
+       "      <td>1.707223</td>\n",
+       "      <td>0.284133</td>\n",
+       "      <td>11.575665</td>\n",
+       "      <td>9.166092</td>\n",
+       "      <td>0.693689</td>\n",
+       "      <td>0.210012</td>\n",
+       "      <td>0.500082</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>min</td>\n",
+       "      <td>-16.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.684000</td>\n",
+       "      <td>42.750000</td>\n",
+       "      <td>0.866000</td>\n",
+       "      <td>-10.432000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.041000</td>\n",
+       "      <td>42.778000</td>\n",
+       "      <td>3.533000</td>\n",
+       "      <td>0.785000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>25%</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>2.516000</td>\n",
+       "      <td>0.895000</td>\n",
+       "      <td>68.294000</td>\n",
+       "      <td>0.974000</td>\n",
+       "      <td>-3.606000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>5.587500</td>\n",
+       "      <td>67.556000</td>\n",
+       "      <td>5.459250</td>\n",
+       "      <td>1.082000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>50%</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>7.143000</td>\n",
+       "      <td>0.963000</td>\n",
+       "      <td>74.059500</td>\n",
+       "      <td>0.994000</td>\n",
+       "      <td>-2.296500</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>14.988500</td>\n",
+       "      <td>73.697000</td>\n",
+       "      <td>5.925500</td>\n",
+       "      <td>1.184000</td>\n",
+       "      <td>0.500000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>75%</td>\n",
+       "      <td>4.000000</td>\n",
+       "      <td>13.158000</td>\n",
+       "      <td>1.041000</td>\n",
+       "      <td>79.343750</td>\n",
+       "      <td>1.011000</td>\n",
+       "      <td>-1.283250</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>26.807750</td>\n",
+       "      <td>79.778000</td>\n",
+       "      <td>6.382000</td>\n",
+       "      <td>1.351000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>max</td>\n",
+       "      <td>30.000000</td>\n",
+       "      <td>46.667000</td>\n",
+       "      <td>1.451000</td>\n",
+       "      <td>101.682000</td>\n",
+       "      <td>1.196000</td>\n",
+       "      <td>3.576000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>51.280000</td>\n",
+       "      <td>103.167000</td>\n",
+       "      <td>8.662000</td>\n",
+       "      <td>2.192000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "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": 151,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# First i will use the describe to get some descriptive statistics\n",
+    "train_data.describe()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Distribution of the outcome\n",
+    "\n",
+    "Lets first generate a bar chart to see how the predicted values are distributed by counts. Our target is having an outcome that is fairly balanced so as not to bais training process."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 162,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x142ac32d0>"
+      ]
+     },
+     "execution_count": 162,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.countplot(x=\"CLASS\", data=train_data) #Plots the frequency of the 0's and 1's in the class field"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "   A similar graph could be generated using `matplotlib.pyplot` with the code below.   "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x130d60e10>"
+      ]
+     },
+     "execution_count": 77,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX0AAAEDCAYAAADZUdTgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAARCUlEQVR4nO3de4zlZX3H8fenrFAv1eUyIu4uDtX1grZVnCKtTWNFEdS4NJUGYurG0m6bYuulRlH/INGYamxESSzNVlaX1IDWS9hY1G64xDQtyOAFuahMEdlxUcYu0lbqBf32j/NsOB1mZ3bnzJ7Bfd6vZDK/3/f5nt95TjL7Ob99zu+ck6pCktSHX1rtCUiSxsfQl6SOGPqS1BFDX5I6YuhLUkcMfUnqyJrVnsBijjnmmJqcnFztaUjSL5Qbb7zx+1U1sdDYwzr0JycnmZ6eXu1pSNIvlCTf3teYyzuS1BFDX5I6YuhLUkcMfUnqiKEvSR0x9CWpI4a+JHXE0Jekjjys35z1i2Ly/H9e7SkcUu5898tWewqHFP8+V86h8Lfpmb4kdcTQl6SOGPqS1BFDX5I6YuhLUkcMfUnqiKEvSR0x9CWpI4a+JHXE0Jekjhj6ktQRQ1+SOrJk6CfZluSeJDcvMPamJJXkmLafJBclmUlyU5KThno3J7m9/Wxe2YchSdof+3Om/xHg9PnFJBuAFwN3DZXPADa2ny3Axa33KOAC4HnAycAFSY4cZeKSpAO3ZOhX1ReAPQsMXQi8Gaih2ibg0hq4Dlib5DjgJcDOqtpTVfcCO1ngiUSSdHAta00/ySuA71TVV+cNrQN2De3Pttq+6pKkMTrgL1FJ8ijg7cBpCw0vUKtF6gsdfwuDpSGOP/74A52eJGkRyznTfzJwAvDVJHcC64EvJXkCgzP4DUO964Hdi9Qfoqq2VtVUVU1NTEwsY3qSpH054NCvqq9V1eOrarKqJhkE+klV9V1gB/DqdhXPKcB9VXU38HngtCRHthdwT2s1SdIY7c8lm5cB/w48LclsknMXab8SuAOYAf4B+AuAqtoDvBO4of28o9UkSWO05Jp+VZ2zxPjk0HYB5+2jbxuw7QDnJ0laQb4jV5I6YuhLUkcMfUnqiKEvSR0x9CWpI4a+JHXE0Jekjhj6ktQRQ1+SOmLoS1JHDH1J6oihL0kdMfQlqSOGviR1xNCXpI4Y+pLUEUNfkjpi6EtSR/bnO3K3Jbknyc1Dtfcm+XqSm5J8OsnaobG3JplJ8o0kLxmqn95qM0nOX/mHIklayv6c6X8EOH1ebSfwrKr6deCbwFsBkpwInA08s93m75IcluQw4IPAGcCJwDmtV5I0RkuGflV9Adgzr/YvVfVA270OWN+2NwGXV9WPq+pbwAxwcvuZqao7quonwOWtV5I0Riuxpv/HwGfb9jpg19DYbKvtqy5JGqORQj/J24EHgI/uLS3QVovUFzrmliTTSabn5uZGmZ4kaZ5lh36SzcDLgVdV1d4AnwU2DLWtB3YvUn+IqtpaVVNVNTUxMbHc6UmSFrCs0E9yOvAW4BVVdf/Q0A7g7CRHJDkB2Ah8EbgB2JjkhCSHM3ixd8doU5ckHag1SzUkuQx4AXBMklngAgZX6xwB7EwCcF1V/XlV3ZLk48CtDJZ9zquqn7XjvBb4PHAYsK2qbjkIj0eStIglQ7+qzlmgfMki/e8C3rVA/UrgygOanSRpRfmOXEnqiKEvSR0x9CWpI4a+JHXE0Jekjhj6ktQRQ1+SOmLoS1JHDH1J6oihL0kdMfQlqSOGviR1xNCXpI4Y+pLUEUNfkjpi6EtSRwx9SeqIoS9JHVky9JNsS3JPkpuHakcl2Znk9vb7yFZPkouSzCS5KclJQ7fZ3PpvT7L54DwcSdJi9udM/yPA6fNq5wNXVdVG4Kq2D3AGsLH9bAEuhsGTBIMvVH8ecDJwwd4nCknS+CwZ+lX1BWDPvPImYHvb3g6cOVS/tAauA9YmOQ54CbCzqvZU1b3ATh76RCJJOsiWu6Z/bFXdDdB+P77V1wG7hvpmW21fdUnSGK30C7lZoFaL1B96gGRLkukk03Nzcys6OUnq3XJD/3tt2Yb2+55WnwU2DPWtB3YvUn+IqtpaVVNVNTUxMbHM6UmSFrLc0N8B7L0CZzNwxVD91e0qnlOA+9ryz+eB05Ic2V7APa3VJEljtGaphiSXAS8Ajkkyy+AqnHcDH09yLnAXcFZrvxJ4KTAD3A+8BqCq9iR5J3BD63tHVc1/cViSdJAtGfpVdc4+hk5doLeA8/ZxnG3AtgOanSRpRfmOXEnqiKEvSR0x9CWpI4a+JHXE0Jekjhj6ktQRQ1+SOmLoS1JHDH1J6oihL0kdMfQlqSOGviR1xNCXpI4Y+pLUEUNfkjpi6EtSRwx9SeqIoS9JHTH0JakjI4V+kjckuSXJzUkuS/LLSU5Icn2S25N8LMnhrfeItj/TxidX4gFIkvbfskM/yTrgr4CpqnoWcBhwNvAe4MKq2gjcC5zbbnIucG9VPQW4sPVJksZo1OWdNcAjk6wBHgXcDbwQ+EQb3w6c2bY3tX3a+KlJMuL9S5IOwLJDv6q+A/wtcBeDsL8PuBH4QVU90NpmgXVtex2wq932gdZ/9PzjJtmSZDrJ9Nzc3HKnJ0lawCjLO0cyOHs/AXgi8GjgjAVaa+9NFhl7sFC1taqmqmpqYmJiudOTJC1glOWdFwHfqqq5qvop8Cngt4G1bbkHYD2wu23PAhsA2vjjgD0j3L8k6QCNEvp3AackeVRbmz8VuBW4Bnhl69kMXNG2d7R92vjVVfWQM31J0sEzypr+9QxekP0S8LV2rK3AW4A3JplhsGZ/SbvJJcDRrf5G4PwR5i1JWoY1S7fsW1VdAFwwr3wHcPICvT8Czhrl/iRJo/EduZLUEUNfkjpi6EtSRwx9SeqIoS9JHTH0Jakjhr4kdcTQl6SOGPqS1BFDX5I6YuhLUkcMfUnqiKEvSR0x9CWpI4a+JHXE0Jekjhj6ktQRQ1+SOjJS6CdZm+QTSb6e5LYkv5XkqCQ7k9zefh/ZepPkoiQzSW5KctLKPARJ0v4a9Uz/A8DnqurpwG8AtzH4wvOrqmojcBUPfgH6GcDG9rMFuHjE+5YkHaBlh36SxwK/C1wCUFU/qaofAJuA7a1tO3Bm294EXFoD1wFrkxy37JlLkg7YKGf6vwrMAR9O8uUkH0ryaODYqroboP1+fOtfB+wauv1sq0mSxmSU0F8DnARcXFXPAX7Ig0s5C8kCtXpIU7IlyXSS6bm5uRGmJ0mab5TQnwVmq+r6tv8JBk8C39u7bNN+3zPUv2Ho9uuB3fMPWlVbq2qqqqYmJiZGmJ4kab5lh35VfRfYleRprXQqcCuwA9jcapuBK9r2DuDV7SqeU4D79i4DSZLGY82It/9L4KNJDgfuAF7D4Ink40nOBe4Czmq9VwIvBWaA+1uvJGmMRgr9qvoKMLXA0KkL9BZw3ij3J0kaje/IlaSOGPqS1BFDX5I6YuhLUkcMfUnqiKEvSR0x9CWpI4a+JHXE0Jekjhj6ktQRQ1+SOmLoS1JHDH1J6oihL0kdMfQlqSOGviR1xNCXpI4Y+pLUkZFDP8lhSb6c5DNt/4Qk1ye5PcnH2vfnkuSItj/TxidHvW9J0oFZiTP91wG3De2/B7iwqjYC9wLntvq5wL1V9RTgwtYnSRqjkUI/yXrgZcCH2n6AFwKfaC3bgTPb9qa2Txs/tfVLksZk1DP99wNvBn7e9o8GflBVD7T9WWBd214H7AJo4/e1fknSmCw79JO8HLinqm4cLi/QWvsxNnzcLUmmk0zPzc0td3qSpAWMcqb/fOAVSe4ELmewrPN+YG2SNa1nPbC7bc8CGwDa+OOAPfMPWlVbq2qqqqYmJiZGmJ4kab5lh35VvbWq1lfVJHA2cHVVvQq4Bnhla9sMXNG2d7R92vjVVfWQM31J0sFzMK7TfwvwxiQzDNbsL2n1S4CjW/2NwPkH4b4lSYtYs3TL0qrqWuDatn0HcPICPT8CzlqJ+5MkLY/vyJWkjhj6ktQRQ1+SOmLoS1JHDH1J6oihL0kdMfQlqSOGviR1xNCXpI4Y+pLUEUNfkjpi6EtSRwx9SeqIoS9JHTH0Jakjhr4kdcTQl6SOGPqS1JFlh36SDUmuSXJbkluSvK7Vj0qyM8nt7feRrZ4kFyWZSXJTkpNW6kFIkvbPKGf6DwB/XVXPAE4BzktyIoMvPL+qqjYCV/HgF6CfAWxsP1uAi0e4b0nSMiw79Kvq7qr6Utv+b+A2YB2wCdje2rYDZ7btTcClNXAdsDbJccueuSTpgK3Imn6SSeA5wPXAsVV1NwyeGIDHt7Z1wK6hm822miRpTEYO/SSPAT4JvL6q/mux1gVqtcDxtiSZTjI9Nzc36vQkSUNGCv0kj2AQ+B+tqk+18vf2Ltu03/e0+iywYejm64Hd849ZVVuraqqqpiYmJkaZniRpnlGu3glwCXBbVb1vaGgHsLltbwauGKq/ul3Fcwpw395lIEnSeKwZ4bbPB/4I+FqSr7Ta24B3Ax9Pci5wF3BWG7sSeCkwA9wPvGaE+5YkLcOyQ7+q/pWF1+kBTl2gv4Dzlnt/kqTR+Y5cSeqIoS9JHTH0Jakjhr4kdcTQl6SOGPqS1BFDX5I6YuhLUkcMfUnqiKEvSR0x9CWpI4a+JHXE0Jekjhj6ktQRQ1+SOmLoS1JHDH1J6oihL0kdMfQlqSNjD/0kpyf5RpKZJOeP+/4lqWdjDf0khwEfBM4ATgTOSXLiOOcgST0b95n+ycBMVd1RVT8BLgc2jXkOktStNWO+v3XArqH9WeB5ww1JtgBb2u7/JPnGmObWg2OA76/2JJaS96z2DLRKHvZ/n79Af5tP2tfAuEM/C9Tq/+1UbQW2jmc6fUkyXVVTqz0PaSH+fY7HuJd3ZoENQ/vrgd1jnoMkdWvcoX8DsDHJCUkOB84Gdox5DpLUrbEu71TVA0leC3weOAzYVlW3jHMOnXPZTA9n/n2OQapq6S5J0iHBd+RKUkcMfUnqiKEvSR0Z93X6GqMkT2fwjud1DN4PsRvYUVW3rerEJK0az/QPUUnewuBjLgJ8kcHlsgEu84Pu9HCW5DWrPYdDmVfvHKKSfBN4ZlX9dF79cOCWqtq4OjOTFpfkrqo6frXncahyeefQ9XPgicC359WPa2PSqkly076GgGPHOZfeGPqHrtcDVyW5nQc/5O544CnAa1dtVtLAscBLgHvn1QP82/in0w9D/xBVVZ9L8lQGH2e9jsE/plnghqr62apOToLPAI+pqq/MH0hy7fin0w/X9CWpI169I0kdMfQlqSOGvrqW5AlJLk/yH0luTXJlkqcmuXkf/WuSfD/J38yrvzzJl5N8tR3nz1r9aUmuTfKVJLcl8ZMktap8IVfdShLg08D2qjq71Z7N4pcMngZ8A/jDJG+rqkryCAYfC3xyVc0mOQKYbP0XARdW1RXt+L92cB6NtH8801fPfg/4aVX9/d5Cu5pk175vwjnAB4C7gFNa7VcYnED9ZzvGj6tq73c7H8fgqqm9x//ais1eWgZDXz17FnDj/jYneSRwKoPLDS9j8ARAVe1h8A1w305yWZJXJdn7b+tC4Ookn03yhiRrV/QRSAfI0Jf238uBa6rqfuCTwO8nOQygqv6EwRPCF4E3Adta/cPAM4B/Al4AXNeWf6RVYeirZ7cAzz2A/nOAFyW5k8H/EI5msEQEDJZuqupC4MXAHwzVd1fVtqraBDzA4H8Y0qow9NWzq4Ejkvzp3kKS3wSeNL8xyWOB3wGOr6rJqpoEzgPOSfKYJC8Yan827TOPkpzeXuglyRMYPFF85+A8HGlpviNXXUvyROD9DM74fwTcyeBzi24FvjfU+gHguXuv8mm3PYrBlTxPYbDG/2Tgf4EfAq+rqukk7wNe1o4N8N6q+seD+ZikxRj6ktQRl3ckqSOGviR1xNCXpI4Y+pLUEUNfkjpi6EtSRwx9SeqIoS9JHfk/x2lWZgDUYiMAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "train_data.groupby('CLASS').size().plot(kind='bar')  "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "From the outputs above we can see that our data is very balanced hence no need to special treatment with methods like smote.\n",
+    "\n",
+    "<div class = 'alert alert-success'>\n",
+    "    Good explanation\n",
+    "    \n",
+    "   What does it tell us about the metric we are going to use to evaluate our algorithm"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Correlation between the features\n",
+    "\n",
+    "Lets get a correlation of the different variables we have in our data. This will tell whether there are features that are highly dependant on the other, which might affect our model especially if Logistic or Linear regression is used.\n",
+    "\n",
+    "<div class = 'alert alert-info'>\n",
+    "How?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>FULL_Charge</th>\n",
+       "      <th>FULL_AcidicMolPerc</th>\n",
+       "      <th>FULL_AURR980107</th>\n",
+       "      <th>FULL_DAYM780201</th>\n",
+       "      <th>FULL_GEOR030101</th>\n",
+       "      <th>FULL_OOBM850104</th>\n",
+       "      <th>NT_EFC195</th>\n",
+       "      <th>AS_MeanAmphiMoment</th>\n",
+       "      <th>AS_DAYM780201</th>\n",
+       "      <th>AS_FUKS010112</th>\n",
+       "      <th>CT_RACS820104</th>\n",
+       "      <th>CLASS</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>FULL_Charge</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.612996</td>\n",
+       "      <td>-0.490977</td>\n",
+       "      <td>-0.434603</td>\n",
+       "      <td>-0.058725</td>\n",
+       "      <td>-0.283758</td>\n",
+       "      <td>0.088068</td>\n",
+       "      <td>0.355477</td>\n",
+       "      <td>-0.365374</td>\n",
+       "      <td>-0.090570</td>\n",
+       "      <td>0.232929</td>\n",
+       "      <td>0.534602</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>FULL_AcidicMolPerc</td>\n",
+       "      <td>-0.612996</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.794796</td>\n",
+       "      <td>0.541481</td>\n",
+       "      <td>0.115201</td>\n",
+       "      <td>0.513344</td>\n",
+       "      <td>-0.143168</td>\n",
+       "      <td>-0.431590</td>\n",
+       "      <td>0.449621</td>\n",
+       "      <td>0.002334</td>\n",
+       "      <td>-0.213543</td>\n",
+       "      <td>-0.598816</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>FULL_AURR980107</td>\n",
+       "      <td>-0.490977</td>\n",
+       "      <td>0.794796</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.548253</td>\n",
+       "      <td>0.346139</td>\n",
+       "      <td>0.462712</td>\n",
+       "      <td>-0.169540</td>\n",
+       "      <td>-0.426097</td>\n",
+       "      <td>0.456260</td>\n",
+       "      <td>0.032958</td>\n",
+       "      <td>-0.403599</td>\n",
+       "      <td>-0.584111</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>FULL_DAYM780201</td>\n",
+       "      <td>-0.434603</td>\n",
+       "      <td>0.541481</td>\n",
+       "      <td>0.548253</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.010118</td>\n",
+       "      <td>0.334778</td>\n",
+       "      <td>-0.090058</td>\n",
+       "      <td>-0.408793</td>\n",
+       "      <td>0.894191</td>\n",
+       "      <td>0.055915</td>\n",
+       "      <td>-0.326792</td>\n",
+       "      <td>-0.554838</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>FULL_GEOR030101</td>\n",
+       "      <td>-0.058725</td>\n",
+       "      <td>0.115201</td>\n",
+       "      <td>0.346139</td>\n",
+       "      <td>0.010118</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.319157</td>\n",
+       "      <td>-0.230417</td>\n",
+       "      <td>-0.160269</td>\n",
+       "      <td>-0.029085</td>\n",
+       "      <td>0.040480</td>\n",
+       "      <td>-0.151935</td>\n",
+       "      <td>-0.260470</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>FULL_OOBM850104</td>\n",
+       "      <td>-0.283758</td>\n",
+       "      <td>0.513344</td>\n",
+       "      <td>0.462712</td>\n",
+       "      <td>0.334778</td>\n",
+       "      <td>0.319157</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.230561</td>\n",
+       "      <td>-0.336297</td>\n",
+       "      <td>0.275640</td>\n",
+       "      <td>-0.452769</td>\n",
+       "      <td>0.155304</td>\n",
+       "      <td>-0.453287</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>NT_EFC195</td>\n",
+       "      <td>0.088068</td>\n",
+       "      <td>-0.143168</td>\n",
+       "      <td>-0.169540</td>\n",
+       "      <td>-0.090058</td>\n",
+       "      <td>-0.230417</td>\n",
+       "      <td>-0.230561</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.178683</td>\n",
+       "      <td>-0.036844</td>\n",
+       "      <td>0.145924</td>\n",
+       "      <td>0.080898</td>\n",
+       "      <td>0.260702</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>AS_MeanAmphiMoment</td>\n",
+       "      <td>0.355477</td>\n",
+       "      <td>-0.431590</td>\n",
+       "      <td>-0.426097</td>\n",
+       "      <td>-0.408793</td>\n",
+       "      <td>-0.160269</td>\n",
+       "      <td>-0.336297</td>\n",
+       "      <td>0.178683</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.322378</td>\n",
+       "      <td>0.025580</td>\n",
+       "      <td>0.171524</td>\n",
+       "      <td>0.693552</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>AS_DAYM780201</td>\n",
+       "      <td>-0.365374</td>\n",
+       "      <td>0.449621</td>\n",
+       "      <td>0.456260</td>\n",
+       "      <td>0.894191</td>\n",
+       "      <td>-0.029085</td>\n",
+       "      <td>0.275640</td>\n",
+       "      <td>-0.036844</td>\n",
+       "      <td>-0.322378</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.045562</td>\n",
+       "      <td>-0.256060</td>\n",
+       "      <td>-0.437168</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>AS_FUKS010112</td>\n",
+       "      <td>-0.090570</td>\n",
+       "      <td>0.002334</td>\n",
+       "      <td>0.032958</td>\n",
+       "      <td>0.055915</td>\n",
+       "      <td>0.040480</td>\n",
+       "      <td>-0.452769</td>\n",
+       "      <td>0.145924</td>\n",
+       "      <td>0.025580</td>\n",
+       "      <td>0.045562</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.445284</td>\n",
+       "      <td>0.033432</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>CT_RACS820104</td>\n",
+       "      <td>0.232929</td>\n",
+       "      <td>-0.213543</td>\n",
+       "      <td>-0.403599</td>\n",
+       "      <td>-0.326792</td>\n",
+       "      <td>-0.151935</td>\n",
+       "      <td>0.155304</td>\n",
+       "      <td>0.080898</td>\n",
+       "      <td>0.171524</td>\n",
+       "      <td>-0.256060</td>\n",
+       "      <td>-0.445284</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.267652</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>CLASS</td>\n",
+       "      <td>0.534602</td>\n",
+       "      <td>-0.598816</td>\n",
+       "      <td>-0.584111</td>\n",
+       "      <td>-0.554838</td>\n",
+       "      <td>-0.260470</td>\n",
+       "      <td>-0.453287</td>\n",
+       "      <td>0.260702</td>\n",
+       "      <td>0.693552</td>\n",
+       "      <td>-0.437168</td>\n",
+       "      <td>0.033432</td>\n",
+       "      <td>0.267652</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "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": 78,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_data.corr(method='pearson')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "From the output above, we can see that some features have fairly large correlation values of up to 0.7, however none has very strong correlation of close to 1.\n",
+    "\n",
+    "However this output is not the best to interprete. Lets transform this a graphical output."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x135a02c10>"
+      ]
+     },
+     "execution_count": 79,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.heatmap(train_data.corr(method='pearson'))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Lets now check the correlation in relation with the outcome of interest."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "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": 80,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_data.corr(method=\"pearson\")['CLASS']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "From this, **AS_MeanAmphiMoment** has the highest correlation with the outcome of interest. This might be one of the features we shall base on when selecting our features to use.\n",
+    "\n",
+    "<div class = 'alert alert-info'>\n",
+    "The explanation is vague, does this mean this feature is a good predictor or what?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Exploring the data with plots\n",
+    "\n",
+    "Lets generate some plots that will get us a firm understading of our data. This is done with histogram, density plots and box plots\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 12 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "train_data.plot(kind='box', subplots=True, layout=(4,3), sharex=False, sharey=False)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<div class = 'alert alert-info'>\n",
+    "What do you learn from the graphs below?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 111,
+   "metadata": {
+    "code_folding": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<seaborn.axisgrid.PairGrid at 0x140135f10>"
+      ]
+     },
+     "execution_count": 111,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1080x1080 with 42 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plots for 5 selected features as produced by RFE \n",
+    "sns.pairplot(train_data[['FULL_AURR980107', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n",
+    "       'CT_RACS820104','CLASS']]) "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Preparing data for ML\n",
+    "\n",
+    "This helps to prepare our data in a such a way to best expose the problem to the ML algorithm we are going to use.\n",
+    "\n",
+    "Options for Preprocessing include;\n",
+    "- Rescaling using sklearn's MinMaxScaler()\n",
+    "- Standardizing using sklearn's StandardScaler()\n",
+    "- Normalizing the data using sklearn's Normalizer()\n",
+    "- Binarizing the data/feature using sklearn's Binarizer with a threshold."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 83,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[ 5.   ,  0.   ,  0.951, ...,  5.661,  1.041,  1.   ],\n",
+       "       [ 4.   ,  5.405,  0.931, ...,  6.537,  1.453,  1.   ],\n",
+       "       [ 5.5  ,  5.405,  0.873, ...,  4.934,  1.722,  1.   ],\n",
+       "       ...,\n",
+       "       [-1.5  , 12.5  ,  1.091, ...,  5.889,  1.131,  0.   ],\n",
+       "       [ 2.   ,  5.   ,  0.849, ...,  6.055,  1.27 ,  0.   ],\n",
+       "       [-1.   , 15.789,  1.066, ...,  5.853,  1.136,  0.   ]])"
+      ]
+     },
+     "execution_count": 83,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_data.values"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Since the values we have are of different scale, we do rescaling on the data to get it within a single range say 0 - 1.\n",
+    "\n",
+    "This done with sklearn's **MinMaxScaler**.\n",
+    "<div class = 'alert alert-success'>\n",
+    "\n",
+    "Good explanation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([1., 1., 1., ..., 0., 0., 0.])"
+      ]
+     },
+     "execution_count": 84,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_data.shape\n",
+    "array = train_data.values\n",
+    "array[:,11]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "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",
+    "array = train_data.values\n",
+    "# separate array into input and output components\n",
+    "X = array[:,0:11]  #This is the input component\n",
+    "Y = array[:,11]   #This is the output/predicted component\n",
+    "\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,:])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Standardizing the Data\n",
+    "\n",
+    "This involves transforming the data into a Gaussian distribution (ie mean of 0 and standard deviation of 1).  This is especially needed for models that assume a Gaussian distribution such as **Linear Regression, Logistic Regression, LDA**, etc \n",
+    "\n",
+    "<div class = 'alert alert-success'>\n",
+    "Great info"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "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 sklearn.preprocessing import StandardScaler\n",
+    "\n",
+    "array2 = train_data.values\n",
+    "# separate array into input and output components\n",
+    "X = array2[:,0:11]\n",
+    "Y = array2[:,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",
+    "This involves selecting features that are very relevant to our predictions. This is because including features that are irrelevant or partially relevant has a negative impact on the performance our model especially on linear models such as Linear and Logistic Regression.\n",
+    "\n",
+    "Benefits of Feature selection are;\n",
+    "- Improves accuracy\n",
+    "- Reduces Training time\n",
+    "- Reduces overfitting\n",
+    "\n",
+    "Methods for feature selection include;\n",
+    "1. Univariate Selection.\n",
+    "- Recursive Feature Selection\n",
+    "- Principle Component Analysis\n",
+    "- Feature Importance\n",
+    "\n",
+    "<div class = 'alert alert-success'>\n",
+    "Good info"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### a. Univariate selection"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
+   "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<ipython-input-87-0266ee585b8d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[0;31m# feature extraction\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      8\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;36m4\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[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[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     10\u001b[0m \u001b[0;31m# summarize scores\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     11\u001b[0m \u001b[0mset_printoptions\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprecision\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m)\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;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 \u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 349\u001b[0;31m         \u001b[0mscore_func_ret\u001b[0m \u001b[0;34m=\u001b[0m \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": [
+    "from sklearn.feature_selection import SelectKBest\n",
+    "from sklearn.feature_selection import chi2\n",
+    "\n",
+    "array_1 = train_data.values\n",
+    "X = array_1[:,0:11]\n",
+    "Y = array_1[:,11]\n",
+    "# feature extraction\n",
+    "test = SelectKBest(score_func=chi2, k=4)\n",
+    "fit = test.fit(X, Y)\n",
+    "# summarize scores\n",
+    "set_printoptions(precision=3)\n",
+    "print(fit.scores_)\n",
+    "features = fit.transform(X)\n",
+    "# summarize selected features\n",
+    "print(features[0:5,:])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>FULL_Charge</th>\n",
+       "      <th>FULL_AcidicMolPerc</th>\n",
+       "      <th>FULL_AURR980107</th>\n",
+       "      <th>FULL_DAYM780201</th>\n",
+       "      <th>FULL_GEOR030101</th>\n",
+       "      <th>FULL_OOBM850104</th>\n",
+       "      <th>NT_EFC195</th>\n",
+       "      <th>AS_MeanAmphiMoment</th>\n",
+       "      <th>AS_DAYM780201</th>\n",
+       "      <th>AS_FUKS010112</th>\n",
+       "      <th>CT_RACS820104</th>\n",
+       "      <th>CLASS</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>3033</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>5.263</td>\n",
+       "      <td>0.945</td>\n",
+       "      <td>67.947</td>\n",
+       "      <td>1.006</td>\n",
+       "      <td>-2.151</td>\n",
+       "      <td>0</td>\n",
+       "      <td>16.706</td>\n",
+       "      <td>68.611</td>\n",
+       "      <td>5.598</td>\n",
+       "      <td>1.144</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3034</td>\n",
+       "      <td>-6.5</td>\n",
+       "      <td>21.667</td>\n",
+       "      <td>1.133</td>\n",
+       "      <td>75.433</td>\n",
+       "      <td>1.015</td>\n",
+       "      <td>-1.675</td>\n",
+       "      <td>0</td>\n",
+       "      <td>16.897</td>\n",
+       "      <td>73.278</td>\n",
+       "      <td>6.194</td>\n",
+       "      <td>1.639</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3035</td>\n",
+       "      <td>-1.5</td>\n",
+       "      <td>12.500</td>\n",
+       "      <td>1.091</td>\n",
+       "      <td>76.542</td>\n",
+       "      <td>0.991</td>\n",
+       "      <td>-0.918</td>\n",
+       "      <td>0</td>\n",
+       "      <td>16.918</td>\n",
+       "      <td>82.111</td>\n",
+       "      <td>5.889</td>\n",
+       "      <td>1.131</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3036</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>5.000</td>\n",
+       "      <td>0.849</td>\n",
+       "      <td>73.750</td>\n",
+       "      <td>1.017</td>\n",
+       "      <td>-2.722</td>\n",
+       "      <td>0</td>\n",
+       "      <td>17.131</td>\n",
+       "      <td>74.722</td>\n",
+       "      <td>6.055</td>\n",
+       "      <td>1.270</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3037</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>15.789</td>\n",
+       "      <td>1.066</td>\n",
+       "      <td>66.158</td>\n",
+       "      <td>0.998</td>\n",
+       "      <td>-2.080</td>\n",
+       "      <td>0</td>\n",
+       "      <td>17.151</td>\n",
+       "      <td>67.111</td>\n",
+       "      <td>5.853</td>\n",
+       "      <td>1.136</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      FULL_Charge  FULL_AcidicMolPerc  FULL_AURR980107  FULL_DAYM780201  \\\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",
+       "      FULL_GEOR030101  FULL_OOBM850104  NT_EFC195  AS_MeanAmphiMoment  \\\n",
+       "3033            1.006           -2.151          0              16.706   \n",
+       "3034            1.015           -1.675          0              16.897   \n",
+       "3035            0.991           -0.918          0              16.918   \n",
+       "3036            1.017           -2.722          0              17.131   \n",
+       "3037            0.998           -2.080          0              17.151   \n",
+       "\n",
+       "      AS_DAYM780201  AS_FUKS010112  CT_RACS820104  CLASS  \n",
+       "3033         68.611          5.598          1.144      0  \n",
+       "3034         73.278          6.194          1.639      0  \n",
+       "3035         82.111          5.889          1.131      0  \n",
+       "3036         74.722          6.055          1.270      0  \n",
+       "3037         67.111          5.853          1.136      0  "
+      ]
+     },
+     "execution_count": 88,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "array_1 = train_data.values\n",
+    "X = array_1[:,0:11]\n",
+    "train_data.tail()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## b. Recursive Feature Elimination"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 142,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Num Features:  5\n",
+      "Selected Features: [False False  True False  True  True  True False False False  True]\n",
+      "Feature Ranking:  [2 6 1 5 1 1 1 3 7 4 1]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Index(['FULL_AURR980107', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n",
+       "       'CT_RACS820104'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 142,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from sklearn.feature_selection import RFE\n",
+    "from sklearn.linear_model import LogisticRegression\n",
+    "\n",
+    "array_2 = train_data.values\n",
+    "X = array_2[:,0:11]\n",
+    "Y = array_2[:,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_)\n",
+    "\n",
+    "col = train_data.columns[0:11]\n",
+    "#print(col)\n",
+    "col[fit.support_] #Get the best features"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## c. Principal Component Analysis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 90,
+   "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"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.decomposition import PCA\n",
+    "\n",
+    "array_3 = train_data.values\n",
+    "X = array_3[:,0:11]\n",
+    "Y = array_3[:,11]\n",
+    "# feature extraction\n",
+    "pca = PCA(n_components=3)\n",
+    "fit = pca.fit(X)\n",
+    "# summarize components\n",
+    "print(\"Explained Variance: \" , fit.explained_variance_ratio_)\n",
+    "print(fit.components_)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The question is how get the seleced features.\n",
+    "\n",
+    "## d. Feature Importance\n",
+    "This uses Decision Trees to determine the importance of each feature."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[0.082 0.137 0.074 0.095 0.043 0.084 0.032 0.32  0.029 0.03  0.074]\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.ensemble import ExtraTreesClassifier\n",
+    "\n",
+    "array_4 = train_data.values\n",
+    "X = array_4[:,0:11]\n",
+    "Y = array_4[:,11]\n",
+    "# feature extraction\n",
+    "model = ExtraTreesClassifier()\n",
+    "model.fit(X, Y)\n",
+    "print(model.feature_importances_)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<div class = 'alert alert-info'>\n",
+    "Did you use all the above methods to make decisions?\n",
+    "    \n",
+    "Please explain more."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Evaluate 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."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 1. Train and Test"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 92,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy:  91.82452642073778\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.linear_model import LogisticRegression\n",
+    "\n",
+    "array = train_data.values\n",
+    "X = array[:,0:11]\n",
+    "Y = array[:,11]\n",
+    "test_size = 0.33\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))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 113,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy:  92.29534510433388\n",
+      "MCC accuracy is:  0.8347815989560698\n"
+     ]
+    }
+   ],
+   "source": [
+    "#Increasing the testing data set\n",
+    "\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.linear_model import LogisticRegression\n",
+    "\n",
+    "array = train_data.values\n",
+    "X = array[:,0:11]\n",
+    "Y = array[:,11]\n",
+    "test_size1 = 0.41\n",
+    "seed = 7\n",
+    "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size1,\n",
+    "random_state=seed)\n",
+    "model = LogisticRegression()\n",
+    "model.fit(X_train, Y_train)\n",
+    "result = model.score(X_test, Y_test)\n",
+    "\n",
+    "print(\"Accuracy: \",  (result*100.0))\n",
+    "\n",
+    "#model.fit(X,Y)\n",
+    "out = model.predict(test_data)\n",
+    "\n",
+    "mcc = matthews_corrcoef(model.predict(X),Y)\n",
+    "print(\"MCC accuracy is: \", mcc)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 94,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "new = train_data[['FULL_Charge', 'FULL_AURR980107', 'FULL_GEOR030101', 'FULL_OOBM850104',\n",
+    "       'NT_EFC195', 'AS_MeanAmphiMoment', 'AS_FUKS010112', 'CT_RACS820104','CLASS']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 112,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy:  90.54276315789474\n"
+     ]
+    }
+   ],
+   "source": [
+    "#Using selected features\n",
+    "\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.linear_model import LogisticRegression\n",
+    "\n",
+    "array = new.values\n",
+    "X = array[:,0:8]\n",
+    "Y = array[:,8]\n",
+    "test_size = 0.40\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",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 2. K-Fold validation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy: (83.63470557582075, 27.1811965862896)\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.model_selection import KFold\n",
+    "from sklearn.model_selection import cross_val_score\n",
+    "\n",
+    "array = train_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))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 3. Leave out Validation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 96,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.model_selection import LeaveOneOut\n",
+    "from sklearn.model_selection import cross_val_score\n",
+    "\n",
+    "array = train_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)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 97,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy: (91.47465437788019, 27.92584903338453)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Accuracy:\",  (results.mean()*100.0, results.std()*100.0))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 4. Repeated Random Test-Train Splits"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 98,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy:  (91.49551345962112, 0.5257745512835581)\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.model_selection import ShuffleSplit\n",
+    "from sklearn.model_selection import cross_val_score\n",
+    "\n",
+    "array = train_data.values\n",
+    "X = array[:,0:11]\n",
+    "Y = array[:,11]\n",
+    "n_splits = 10\n",
+    "test_size = 0.33\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))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Algorithm Evaluation Metrics\n",
+    "\n",
+    "The following are the common classsification metrics used;\n",
+    "- Classiffication Accuracy.\n",
+    "- Logarithmic Loss.\n",
+    "- Area Under ROC Curve.\n",
+    "- Confusion Matrix.\n",
+    "- Classiffication Report.\n",
+    "\n",
+    "### Classification Accuracy\n",
+    "This is the ratio of the number of correct predictions to the total predictions.\n",
+    "Its more suitably used when there is an equal number of observations in each class.\n",
+    "\n",
+    "<div class = 'alert alert-success'>\n",
+    "Great! Its good to realize this.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 99,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy: (0.8363470557582074, 0.271811965862896)\n"
+     ]
+    }
+   ],
+   "source": [
+    "array = train_data.values\n",
+    "X = array[:,0:11]\n",
+    "Y = array[:,11]\n",
+    "\n",
+    "kfold = KFold(n_splits=10, random_state=7)\n",
+    "\n",
+    "model = LogisticRegression()\n",
+    "\n",
+    "scoring = 'accuracy'\n",
+    "\n",
+    "results = cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\n",
+    "print(\"Accuracy:\", (results.mean(), results.std()))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Logarithmic Loss"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 100,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "ValueError",
+     "evalue": "y_true contains only one label (1.0). Please provide the true labels explicitly through the labels argument.",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-100-bbe6ba28a72a>\u001b[0m in \u001b[0;36m<module>\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[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[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 \u001b[0mcv\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkfold\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mscoring\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mscoring\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      8\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Logloss:\"\u001b[0m\u001b[0;34m,\u001b[0m  \u001b[0;34m(\u001b[0m\u001b[0mresults\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmean\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresults\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstd\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[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/opt/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_validation.py\u001b[0m in \u001b[0;36mcross_val_score\u001b[0;34m(estimator, X, y, groups, scoring, cv, n_jobs, verbose, fit_params, pre_dispatch, error_score)\u001b[0m\n\u001b[1;32m    389\u001b[0m                                 \u001b[0mfit_params\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfit_params\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    390\u001b[0m                                 \u001b[0mpre_dispatch\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpre_dispatch\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 391\u001b[0;31m                                 error_score=error_score)\n\u001b[0m\u001b[1;32m    392\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mcv_results\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'test_score'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    393\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/opt/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_validation.py\u001b[0m in \u001b[0;36mcross_validate\u001b[0;34m(estimator, X, y, groups, scoring, cv, n_jobs, verbose, fit_params, pre_dispatch, return_train_score, return_estimator, error_score)\u001b[0m\n\u001b[1;32m    230\u001b[0m             \u001b[0mreturn_times\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreturn_estimator\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mreturn_estimator\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    231\u001b[0m             error_score=error_score)\n\u001b[0;32m--> 232\u001b[0;31m         for train, test in cv.split(X, y, groups))\n\u001b[0m\u001b[1;32m    233\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    234\u001b[0m     \u001b[0mzipped_scores\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mscores\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~/opt/anaconda3/lib/python3.7/site-packages/joblib/parallel.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, iterable)\u001b[0m\n\u001b[1;32m    919\u001b[0m             \u001b[0;31m# remaining jobs.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    920\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_iterating\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 921\u001b[0;31m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdispatch_one_batch\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0miterator\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    922\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_iterating\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_original_iterator\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    923\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/opt/anaconda3/lib/python3.7/site-packages/joblib/parallel.py\u001b[0m in \u001b[0;36mdispatch_one_batch\u001b[0;34m(self, iterator)\u001b[0m\n\u001b[1;32m    757\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    758\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[0;32m--> 759\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_dispatch\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtasks\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    760\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    761\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/opt/anaconda3/lib/python3.7/site-packages/joblib/parallel.py\u001b[0m in \u001b[0;36m_dispatch\u001b[0;34m(self, batch)\u001b[0m\n\u001b[1;32m    714\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_lock\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    715\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[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 716\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[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    717\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[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    718\u001b[0m             \u001b[0;31m# called before we get here, causing self._jobs to\u001b[0m\u001b[0;34m\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/joblib/_parallel_backends.py\u001b[0m in \u001b[0;36mapply_async\u001b[0;34m(self, func, callback)\u001b[0m\n\u001b[1;32m    180\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mapply_async\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcallback\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\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    181\u001b[0m         \u001b[0;34m\"\"\"Schedule a func to be run\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 182\u001b[0;31m         \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mImmediateResult\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfunc\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    183\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mcallback\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    184\u001b[0m             \u001b[0mcallback\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m)\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/joblib/_parallel_backends.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, batch)\u001b[0m\n\u001b[1;32m    547\u001b[0m         \u001b[0;31m# Don't delay the application, to avoid keeping the input\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    548\u001b[0m         \u001b[0;31m# arguments in memory\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 549\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbatch\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    550\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    551\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mget\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~/opt/anaconda3/lib/python3.7/site-packages/joblib/parallel.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    223\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mparallel_backend\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[0mn_jobs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_n_jobs\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    224\u001b[0m             return [func(*args, **kwargs)\n\u001b[0;32m--> 225\u001b[0;31m                     for func, args, kwargs in self.items]\n\u001b[0m\u001b[1;32m    226\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    227\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__len__\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~/opt/anaconda3/lib/python3.7/site-packages/joblib/parallel.py\u001b[0m in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m    223\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mparallel_backend\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[0mn_jobs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_n_jobs\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    224\u001b[0m             return [func(*args, **kwargs)\n\u001b[0;32m--> 225\u001b[0;31m                     for func, args, kwargs in self.items]\n\u001b[0m\u001b[1;32m    226\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    227\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__len__\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~/opt/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_validation.py\u001b[0m in \u001b[0;36m_fit_and_score\u001b[0;34m(estimator, X, y, scorer, train, test, verbose, parameters, fit_params, return_train_score, return_parameters, return_n_test_samples, return_times, return_estimator, error_score)\u001b[0m\n\u001b[1;32m    554\u001b[0m         \u001b[0mfit_time\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mstart_time\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    555\u001b[0m         \u001b[0;31m# _score will return dict if is_multimetric is True\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 556\u001b[0;31m         \u001b[0mtest_scores\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mestimator\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mX_test\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_test\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mscorer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mis_multimetric\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    557\u001b[0m         \u001b[0mscore_time\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mstart_time\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mfit_time\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    558\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mreturn_train_score\u001b[0m\u001b[0;34m:\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/model_selection/_validation.py\u001b[0m in \u001b[0;36m_score\u001b[0;34m(estimator, X_test, y_test, scorer, is_multimetric)\u001b[0m\n\u001b[1;32m    597\u001b[0m     \"\"\"\n\u001b[1;32m    598\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mis_multimetric\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 599\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0m_multimetric_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mestimator\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mX_test\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_test\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mscorer\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    600\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    601\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0my_test\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\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/model_selection/_validation.py\u001b[0m in \u001b[0;36m_multimetric_score\u001b[0;34m(estimator, X_test, y_test, scorers)\u001b[0m\n\u001b[1;32m    627\u001b[0m             \u001b[0mscore\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mscorer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mestimator\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mX_test\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    628\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[0;32m--> 629\u001b[0;31m             \u001b[0mscore\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mscorer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mestimator\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mX_test\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_test\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    630\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    631\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mhasattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscore\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'item'\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~/opt/anaconda3/lib/python3.7/site-packages/sklearn/metrics/scorer.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, clf, X, y, sample_weight)\u001b[0m\n\u001b[1;32m    138\u001b[0m                                                  **self._kwargs)\n\u001b[1;32m    139\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[0;32m--> 140\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[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    141\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    142\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[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/opt/anaconda3/lib/python3.7/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   2132\u001b[0m             raise ValueError('y_true contains only one label ({0}). Please '\n\u001b[1;32m   2133\u001b[0m                              \u001b[0;34m'provide the true labels explicitly through the '\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2134\u001b[0;31m                              'labels argument.'.format(lb.classes_[0]))\n\u001b[0m\u001b[1;32m   2135\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   2136\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."
+     ]
+    }
+   ],
+   "source": [
+    "array = train_data.values\n",
+    "X = array[:,0:11]\n",
+    "Y = array[:,11]\n",
+    "kfold = KFold(n_splits=10, random_state=7)\n",
+    "model = LogisticRegression()\n",
+    "scoring = 'neg_log_loss'\n",
+    "results = -cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\n",
+    "print(\"Logloss:\",  (results.mean(), results.std()))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Area Under ROC Curve"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 101,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "ValueError",
+     "evalue": "Only one class present in y_true. ROC AUC score is not defined in that case.",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-101-c6be66314cd9>\u001b[0m in \u001b[0;36m<module>\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[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'roc_auc'\u001b[0m\u001b[0;34m\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[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 \u001b[0mcv\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkfold\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mscoring\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mscoring\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      8\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"AUC:\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mresults\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmean\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresults\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstd\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[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/opt/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_validation.py\u001b[0m in \u001b[0;36mcross_val_score\u001b[0;34m(estimator, X, y, groups, scoring, cv, n_jobs, verbose, fit_params, pre_dispatch, error_score)\u001b[0m\n\u001b[1;32m    389\u001b[0m                                 \u001b[0mfit_params\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfit_params\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    390\u001b[0m                                 \u001b[0mpre_dispatch\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpre_dispatch\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 391\u001b[0;31m                                 error_score=error_score)\n\u001b[0m\u001b[1;32m    392\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mcv_results\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'test_score'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    393\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/opt/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_validation.py\u001b[0m in \u001b[0;36mcross_validate\u001b[0;34m(estimator, X, y, groups, scoring, cv, n_jobs, verbose, fit_params, pre_dispatch, return_train_score, return_estimator, error_score)\u001b[0m\n\u001b[1;32m    230\u001b[0m             \u001b[0mreturn_times\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreturn_estimator\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mreturn_estimator\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    231\u001b[0m             error_score=error_score)\n\u001b[0;32m--> 232\u001b[0;31m         for train, test in cv.split(X, y, groups))\n\u001b[0m\u001b[1;32m    233\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    234\u001b[0m     \u001b[0mzipped_scores\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mscores\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~/opt/anaconda3/lib/python3.7/site-packages/joblib/parallel.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, iterable)\u001b[0m\n\u001b[1;32m    919\u001b[0m             \u001b[0;31m# remaining jobs.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    920\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_iterating\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 921\u001b[0;31m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdispatch_one_batch\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0miterator\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    922\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_iterating\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_original_iterator\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    923\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/opt/anaconda3/lib/python3.7/site-packages/joblib/parallel.py\u001b[0m in \u001b[0;36mdispatch_one_batch\u001b[0;34m(self, iterator)\u001b[0m\n\u001b[1;32m    757\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    758\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[0;32m--> 759\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_dispatch\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtasks\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    760\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    761\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/opt/anaconda3/lib/python3.7/site-packages/joblib/parallel.py\u001b[0m in \u001b[0;36m_dispatch\u001b[0;34m(self, batch)\u001b[0m\n\u001b[1;32m    714\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_lock\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    715\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[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 716\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[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    717\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[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    718\u001b[0m             \u001b[0;31m# called before we get here, causing self._jobs to\u001b[0m\u001b[0;34m\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/joblib/_parallel_backends.py\u001b[0m in \u001b[0;36mapply_async\u001b[0;34m(self, func, callback)\u001b[0m\n\u001b[1;32m    180\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mapply_async\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcallback\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\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    181\u001b[0m         \u001b[0;34m\"\"\"Schedule a func to be run\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 182\u001b[0;31m         \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mImmediateResult\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfunc\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    183\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mcallback\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    184\u001b[0m             \u001b[0mcallback\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m)\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/joblib/_parallel_backends.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, batch)\u001b[0m\n\u001b[1;32m    547\u001b[0m         \u001b[0;31m# Don't delay the application, to avoid keeping the input\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    548\u001b[0m         \u001b[0;31m# arguments in memory\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 549\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbatch\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    550\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    551\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mget\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~/opt/anaconda3/lib/python3.7/site-packages/joblib/parallel.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    223\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mparallel_backend\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[0mn_jobs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_n_jobs\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    224\u001b[0m             return [func(*args, **kwargs)\n\u001b[0;32m--> 225\u001b[0;31m                     for func, args, kwargs in self.items]\n\u001b[0m\u001b[1;32m    226\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    227\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__len__\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~/opt/anaconda3/lib/python3.7/site-packages/joblib/parallel.py\u001b[0m in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m    223\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mparallel_backend\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[0mn_jobs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_n_jobs\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    224\u001b[0m             return [func(*args, **kwargs)\n\u001b[0;32m--> 225\u001b[0;31m                     for func, args, kwargs in self.items]\n\u001b[0m\u001b[1;32m    226\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    227\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__len__\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~/opt/anaconda3/lib/python3.7/site-packages/sklearn/model_selection/_validation.py\u001b[0m in \u001b[0;36m_fit_and_score\u001b[0;34m(estimator, X, y, scorer, train, test, verbose, parameters, fit_params, return_train_score, return_parameters, return_n_test_samples, return_times, return_estimator, error_score)\u001b[0m\n\u001b[1;32m    554\u001b[0m         \u001b[0mfit_time\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mstart_time\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    555\u001b[0m         \u001b[0;31m# _score will return dict if is_multimetric is True\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 556\u001b[0;31m         \u001b[0mtest_scores\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mestimator\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mX_test\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_test\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mscorer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mis_multimetric\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    557\u001b[0m         \u001b[0mscore_time\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mstart_time\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mfit_time\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    558\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mreturn_train_score\u001b[0m\u001b[0;34m:\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/model_selection/_validation.py\u001b[0m in \u001b[0;36m_score\u001b[0;34m(estimator, X_test, y_test, scorer, is_multimetric)\u001b[0m\n\u001b[1;32m    597\u001b[0m     \"\"\"\n\u001b[1;32m    598\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mis_multimetric\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 599\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0m_multimetric_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mestimator\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mX_test\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_test\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mscorer\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    600\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    601\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0my_test\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\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/model_selection/_validation.py\u001b[0m in \u001b[0;36m_multimetric_score\u001b[0;34m(estimator, X_test, y_test, scorers)\u001b[0m\n\u001b[1;32m    627\u001b[0m             \u001b[0mscore\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mscorer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mestimator\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mX_test\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    628\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[0;32m--> 629\u001b[0;31m             \u001b[0mscore\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mscorer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mestimator\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mX_test\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_test\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    630\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    631\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mhasattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscore\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'item'\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~/opt/anaconda3/lib/python3.7/site-packages/sklearn/metrics/scorer.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, clf, X, y, sample_weight)\u001b[0m\n\u001b[1;32m    205\u001b[0m                                                  **self._kwargs)\n\u001b[1;32m    206\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[0;32m--> 207\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[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    208\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    209\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[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/opt/anaconda3/lib/python3.7/site-packages/sklearn/metrics/ranking.py\u001b[0m in \u001b[0;36mroc_auc_score\u001b[0;34m(y_true, y_score, average, sample_weight, max_fpr)\u001b[0m\n\u001b[1;32m    353\u001b[0m     return _average_binary_score(\n\u001b[1;32m    354\u001b[0m         \u001b[0m_binary_roc_auc_score\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_true\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_score\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maverage\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 355\u001b[0;31m         sample_weight=sample_weight)\n\u001b[0m\u001b[1;32m    356\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    357\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/opt/anaconda3/lib/python3.7/site-packages/sklearn/metrics/base.py\u001b[0m in \u001b[0;36m_average_binary_score\u001b[0;34m(binary_metric, y_true, y_score, average, sample_weight)\u001b[0m\n\u001b[1;32m     74\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     75\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0my_type\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"binary\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 76\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mbinary_metric\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_true\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_score\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msample_weight\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msample_weight\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     77\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     78\u001b[0m     \u001b[0mcheck_consistent_length\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_true\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_score\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msample_weight\u001b[0m\u001b[0;34m)\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/metrics/ranking.py\u001b[0m in \u001b[0;36m_binary_roc_auc_score\u001b[0;34m(y_true, y_score, sample_weight)\u001b[0m\n\u001b[1;32m    321\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_binary_roc_auc_score\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_true\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_score\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msample_weight\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\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    322\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_true\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 323\u001b[0;31m             raise ValueError(\"Only one class present in y_true. ROC AUC score \"\n\u001b[0m\u001b[1;32m    324\u001b[0m                              \"is not defined in that case.\")\n\u001b[1;32m    325\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mValueError\u001b[0m: Only one class present in y_true. ROC AUC score is not defined in that case."
+     ]
+    }
+   ],
+   "source": [
+    "array = train_data.values\n",
+    "X = array[:,0:11]\n",
+    "Y = array[:,11]\n",
+    "kfold = KFold(n_splits=10, random_state=7)\n",
+    "model = LogisticRegression()\n",
+    "scoring = 'roc_auc'\n",
+    "results = cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\n",
+    "print(\"AUC:\", (results.mean(), results.std()))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Confusion Matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 102,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[458  41]\n",
+      " [ 41 463]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.metrics import confusion_matrix\n",
+    "\n",
+    "array = train_data.values\n",
+    "X = array[:,0:11]\n",
+    "Y = array[:,11]\n",
+    "test_size = 0.33\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",
+    "\n",
+    "model = LogisticRegression()\n",
+    "model.fit(X_train, Y_train)\n",
+    "\n",
+    "predicted = model.predict(X_test)\n",
+    "matrix = confusion_matrix(Y_test, predicted)\n",
+    "print(matrix)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Classiffication Repor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 103,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "         0.0       0.92      0.92      0.92       499\n",
+      "         1.0       0.92      0.92      0.92       504\n",
+      "\n",
+      "    accuracy                           0.92      1003\n",
+      "   macro avg       0.92      0.92      0.92      1003\n",
+      "weighted avg       0.92      0.92      0.92      1003\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.metrics import classification_report\n",
+    "\n",
+    "array = train_data.values\n",
+    "X = array[:,0:11]\n",
+    "Y = array[:,11]\n",
+    "test_size = 0.33\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",
+    "predicted = model.predict(X_test)\n",
+    "report = classification_report(Y_test, predicted)\n",
+    "print(report)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Algorithm Spot-Checking"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 105,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Loading the libraries to be used\n",
+    "import pandas\n",
+    "from pandas.plotting import scatter_matrix\n",
+    "import matplotlib.pyplot as plt\n",
+    "from sklearn import model_selection\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": 146,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "LR: 0.914403 (0.015486)\n",
+      "LDA: 0.919342 (0.014631)\n",
+      "KNN: 0.903704 (0.024910)\n",
+      "CART: 0.894650 (0.023148)\n",
+      "NB: 0.921399 (0.018445)\n",
+      "SVM: 0.890535 (0.019581)\n"
+     ]
+    }
+   ],
+   "source": [
+    "#Building model\n",
+    "#So now we don't know which algorithm will be best to use.   Let's use 6 different algorithms\n",
+    "'''\n",
+    "Logistic Regression\n",
+    "Linear Regression\n",
+    "K-Nearest Neibours\n",
+    "Classification and Regression Trees\n",
+    "Support Vector Machines\n",
+    "Naive bayes\n",
+    "'''\n",
+    "\n",
+    "array = train_data.values  #Having all the values. Returns a numpy object\n",
+    "X = array[:,0:11]  #having all values(rows) and only the begining 4 columns\n",
+    "Y = array[:,11]  #all values(rows ) in the last row\n",
+    "\n",
+    "validation_size = 0.20\n",
+    "seed = np.random.seed(42)  #Helps to keep the same randomness between the train and testing data\n",
+    "X_train, X_test, Y_train, Y_test = model_selection.train_test_split(X, Y, test_size = validation_size, random_state = seed)\n",
+    "\n",
+    "#Lets do a 10-fold cross validation\n",
+    "scoring = 'accuracy'  #ratio of correct in the whole data\n",
+    "\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\n",
+    "results = []\n",
+    "names= []\n",
+    "\n",
+    "for name, model in models:\n",
+    "    kfold = model_selection.KFold(n_splits=10, random_state=seed)\n",
+    "    cv_results = model_selection.cross_val_score(model, X_train, Y_train, cv=kfold, scoring=scoring)\n",
+    "    results.append(cv_results)\n",
+    "    names.append(name)\n",
+    "    msg = \"%s: %f (%f)\" % (name, cv_results.mean(), cv_results.std())\n",
+    "    print(msg)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<div class = 'alert alert-info'>\n",
+    "\n",
+    "## Why do you have less than 10 algos?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "From this we can see that the GaussianNB is giving us the highest accuracy, followed by Linear Discriminant Analysis and Logistic Regression."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Trying Logistic Regression on the prediction Data "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 106,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy is:  91.6065224943547\n",
+      "MCC accuracy is:  0.8316526340707017\n",
+      "       CLASS\n",
+      "Index       \n",
+      "0      False\n",
+      "1      False\n",
+      "2       True\n",
+      "3       True\n",
+      "4      False\n",
+      "[False  True]\n"
+     ]
+    }
+   ],
+   "source": [
+    "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 confusion_matrix\n",
+    "\n",
+    "model = LogisticRegression()\n",
+    "\n",
+    "num_folds = 10\n",
+    "seed = np.random.seed(42)\n",
+    "kfold = KFold(n_splits=num_folds, random_state=seed, shuffle=True)\n",
+    "scoring = \"accuracy\"\n",
+    "results = cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\n",
+    "print(\"Accuracy is: \", results.mean()*100)\n",
+    "\n",
+    "model.fit(X,Y)\n",
+    "out = model.predict(test_data)\n",
+    "\n",
+    "mcc = matthews_corrcoef(model.predict(X),Y)\n",
+    "print(\"MCC accuracy is: \", mcc)\n",
+    "\n",
+    "result = pd.DataFrame(out)\n",
+    "result.columns = [\"CLASS\"]\n",
+    "result.index.name = \"Index\"\n",
+    "\n",
+    "result['CLASS'] = result['CLASS'].map({0.0:False, 1.0:True})\n",
+    "print(result.head())\n",
+    "print(result[\"CLASS\"].unique())\n",
+    "#result.to_csv('/Users/kakembo/Desktop/logistic_out.csv')\n",
+    "#.    This gave me a score of   0.8328"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Doing the Algorithm checking manually"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 130,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.880815746048289\n",
+      "MCC for NB is:  0.8407203694376205\n",
+      "       CLASS\n",
+      "Index       \n",
+      "0       True\n",
+      "1       True\n",
+      "2       True\n",
+      "3       True\n",
+      "4      False\n",
+      "[ True False]\n"
+     ]
+    }
+   ],
+   "source": [
+    "#GaussionNB  ie Naive Bayes\n",
+    "from sklearn.naive_bayes import GaussianNB\n",
+    "array = train_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",
+    "from sklearn.metrics import matthews_corrcoef\n",
+    "model.fit(X,Y)\n",
+    "mcc = matthews_corrcoef(model.predict(X), Y)\n",
+    "print(\"MCC for NB is: \", mcc)\n",
+    "\n",
+    "predNB = model.predict(test_data)\n",
+    "\n",
+    "#Converting the output to a csv file output\n",
+    "resultNB = pd.DataFrame(predNB)\n",
+    "resultNB.columns = [\"CLASS\"]\n",
+    "resultNB.index.name = \"Index\"\n",
+    "\n",
+    "resultNB['CLASS'] = resultNB['CLASS'].map({0.0:False, 1.0:True})\n",
+    "print(resultNB.head())\n",
+    "print(resultNB[\"CLASS\"].unique())\n",
+    "#resultNB.to_csv('/Users/kakembo/Desktop/OutMetrics/GaussionNB_out.csv')\n",
+    "#.    This gave me a score of   0.99559"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The prediction by the GaussianNB gave me a prediction accuracy of 0.99559 on Kaggle using all the features.\n",
+    "\n",
+    "Let's try applying only the 5 features selected during the feature selection using the RFE to see if our performance improves in any way."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 143,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.8075028226506861\n",
+      "MCC for NB is:  0.6505452702192815\n",
+      "       CLASS\n",
+      "Index       \n",
+      "0       True\n",
+      "1       True\n",
+      "2       True\n",
+      "3       True\n",
+      "4      False\n",
+      "[ True False]\n"
+     ]
+    }
+   ],
+   "source": [
+    "#GaussionNB  using a selected features \n",
+    "from sklearn.naive_bayes import GaussianNB\n",
+    "\n",
+    "dataset = train_data[['FULL_AURR980107', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n",
+    "       'CT_RACS820104', 'CLASS']]\n",
+    "array = dataset.values\n",
+    "X = array[:,0:5]\n",
+    "Y = array[:,5]\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",
+    "from sklearn.metrics import matthews_corrcoef\n",
+    "model.fit(X,Y)\n",
+    "mcc = matthews_corrcoef(model.predict(X), Y)\n",
+    "print(\"MCC for NB is: \", mcc)\n",
+    "\n",
+    "predNB = model.predict(test_data[['FULL_AURR980107', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n",
+    "       'CT_RACS820104']])\n",
+    "\n",
+    "#Converting the output to a csv file output\n",
+    "resultNB = pd.DataFrame(predNB)\n",
+    "resultNB.columns = [\"CLASS\"]\n",
+    "resultNB.index.name = \"Index\"\n",
+    "\n",
+    "resultNB['CLASS'] = resultNB['CLASS'].map({0.0:False, 1.0:True})\n",
+    "print(resultNB.head())\n",
+    "print(resultNB[\"CLASS\"].unique())\n",
+    "#resultNB.to_csv('/Users/kakembo/Desktop/OutMetrics/GaussionNB_RFE-5.csv')\n",
+    "#.    This gave me a score of   0.74760"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Reducing my features to 5 best features as determined by RFE method during feature selection greatly reduced the accuracy of my prediction to `0.74760` on Kaggle submission.    \n",
+    "I then increased my features to 8, and then the performance increased to `0.90074` on the kaggle submssion.\n",
+    "\n",
+    "Increasing the features further to 10 improved my prediction accuracy to `0.95593`.\n",
+    "\n",
+    "From this i can conclude that for this dataset its preferred to use the entire dataset without applying any feature selection as removing any feature from the dataset will lead to a drop in the accuracy of my model predictions. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 145,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The Accuracy of LDA is:  0.8535044293903076\n",
+      "MCC accuracy is:  0.8377162908048379\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Trying out the LinearDiscriminantAnalysis\n",
+    "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n",
+    "\n",
+    "\n",
+    "array = train_data.values\n",
+    "X = array[:,0:11]\n",
+    "Y = array[:,11]\n",
+    "\n",
+    "validation_size = 0.20\n",
+    "seed = np.random.seed(42)  #Helps to keep the same randomness between the train and testing data\n",
+    "X_train, X_test, Y_train, Y_test = model_selection.train_test_split(X, Y, test_size = validation_size, random_state = seed)\n",
+    "\n",
+    "\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(\"The Accuracy of LDA is: \",results.mean())\n",
+    "\n",
+    "model.fit(X,Y)\n",
+    "out = model.predict(test_data)\n",
+    "\n",
+    "mcc = matthews_corrcoef(model.predict(X),Y)\n",
+    "print(\"MCC accuracy is: \", mcc)\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": "3.7.4"
+  },
+  "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": 2
+}
diff --git a/Assignment Colab/Kakembo_Fredrick_notebook.ipynb b/Assignment Colab/Kakembo_Fredrick_notebook.ipynb
new file mode 100644
index 0000000..2972864
--- /dev/null
+++ b/Assignment Colab/Kakembo_Fredrick_notebook.ipynb	
@@ -0,0 +1,3538 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<div style=\"text-align: right\">Prepared By:</div>\n",
+    "<div style=\"text-align: right\">Kakembo Fredrick Elishama  </div>\n",
+    "<div style=\"text-align: right\">Reg No:  2019/HD07/24859U  </div>\n",
+    "\n",
+    "## 1. Preparing my Data Problem\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 116,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Python: 3.7.4 (default, Aug 13 2019, 15:17:50) \n",
+      "[Clang 4.0.1 (tags/RELEASE_401/final)]\n",
+      "Scipy: 1.4.1\n",
+      "Pandas:  0.25.1\n",
+      "numpy: 1.17.2\n",
+      "Matplotlib:  3.1.1\n",
+      "Seaborn:  0.9.0\n",
+      "scikit-learn:  0.21.3\n"
+     ]
+    }
+   ],
+   "source": [
+    "#Loading the required libraries and printing the versions used\n",
+    "#Versions are very helpful for reproducibility purposes\n",
+    "\n",
+    "#Ignoring any annoying errors from my cells\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore')\n",
+    "\n",
+    "#Python version\n",
+    "import sys\n",
+    "print('Python: {}'.format(sys.version))\n",
+    "\n",
+    "#Scipy\n",
+    "import scipy\n",
+    "print(\"Scipy: {}\".format(scipy.__version__))\n",
+    "\n",
+    "import pandas as pd #This is for reading and manipulating tabular data \n",
+    "print('Pandas:  {}'.format(pd.__version__))\n",
+    "\n",
+    "import numpy as np  #This is for numerical computing\n",
+    "print('numpy: {}'.format(np.__version__))\n",
+    "\n",
+    "import matplotlib\n",
+    "import matplotlib.pyplot as plt #Generating simple visualizations\n",
+    "print('Matplotlib:  {}'.format(matplotlib.__version__))\n",
+    "\n",
+    "import seaborn as sns  #for generating statistical plots\n",
+    "print('Seaborn:  {}'.format(sns.__version__))\n",
+    "\n",
+    "# scikit-learn\n",
+    "import sklearn\n",
+    "print('scikit-learn:  {}'.format(sklearn.__version__))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>FULL_Charge</th>\n",
+       "      <th>FULL_AcidicMolPerc</th>\n",
+       "      <th>FULL_AURR980107</th>\n",
+       "      <th>FULL_DAYM780201</th>\n",
+       "      <th>FULL_GEOR030101</th>\n",
+       "      <th>FULL_OOBM850104</th>\n",
+       "      <th>NT_EFC195</th>\n",
+       "      <th>AS_MeanAmphiMoment</th>\n",
+       "      <th>AS_DAYM780201</th>\n",
+       "      <th>AS_FUKS010112</th>\n",
+       "      <th>CT_RACS820104</th>\n",
+       "      <th>CLASS</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.951</td>\n",
+       "      <td>74.842</td>\n",
+       "      <td>0.975</td>\n",
+       "      <td>-3.663</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.282</td>\n",
+       "      <td>73.444</td>\n",
+       "      <td>5.661</td>\n",
+       "      <td>1.041</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>5.405</td>\n",
+       "      <td>0.931</td>\n",
+       "      <td>71.595</td>\n",
+       "      <td>0.957</td>\n",
+       "      <td>-4.011</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.600</td>\n",
+       "      <td>68.222</td>\n",
+       "      <td>6.537</td>\n",
+       "      <td>1.453</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>5.5</td>\n",
+       "      <td>5.405</td>\n",
+       "      <td>0.873</td>\n",
+       "      <td>73.595</td>\n",
+       "      <td>0.961</td>\n",
+       "      <td>-2.512</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.593</td>\n",
+       "      <td>69.444</td>\n",
+       "      <td>4.934</td>\n",
+       "      <td>1.722</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>4.167</td>\n",
+       "      <td>0.895</td>\n",
+       "      <td>66.250</td>\n",
+       "      <td>0.999</td>\n",
+       "      <td>-1.362</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.614</td>\n",
+       "      <td>67.222</td>\n",
+       "      <td>4.316</td>\n",
+       "      <td>1.382</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>7.5</td>\n",
+       "      <td>8.537</td>\n",
+       "      <td>0.932</td>\n",
+       "      <td>64.720</td>\n",
+       "      <td>0.979</td>\n",
+       "      <td>-2.091</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.616</td>\n",
+       "      <td>72.944</td>\n",
+       "      <td>4.540</td>\n",
+       "      <td>1.539</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>5</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>7.692</td>\n",
+       "      <td>1.030</td>\n",
+       "      <td>78.949</td>\n",
+       "      <td>0.976</td>\n",
+       "      <td>-3.091</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.511</td>\n",
+       "      <td>78.778</td>\n",
+       "      <td>5.992</td>\n",
+       "      <td>1.091</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>6</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>6.897</td>\n",
+       "      <td>0.930</td>\n",
+       "      <td>78.586</td>\n",
+       "      <td>0.957</td>\n",
+       "      <td>-3.544</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.385</td>\n",
+       "      <td>78.222</td>\n",
+       "      <td>6.284</td>\n",
+       "      <td>1.467</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>7</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>5.882</td>\n",
+       "      <td>0.868</td>\n",
+       "      <td>76.588</td>\n",
+       "      <td>0.949</td>\n",
+       "      <td>-5.832</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.154</td>\n",
+       "      <td>76.588</td>\n",
+       "      <td>6.479</td>\n",
+       "      <td>1.086</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "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",
+       "\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",
+       "\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  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "## Loading my datasets\n",
+    "train_data = pd.read_csv(\"ace-class-assignment/AMP_TrainSet.csv\")\n",
+    "test_data = pd.read_csv(\"ace-class-assignment/Test.csv\")\n",
+    "\n",
+    "#Viewing a sample of the data\n",
+    "train_data.head(8)  #The first 8 lines of the training dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>FULL_Charge</th>\n",
+       "      <th>FULL_AcidicMolPerc</th>\n",
+       "      <th>FULL_AURR980107</th>\n",
+       "      <th>FULL_DAYM780201</th>\n",
+       "      <th>FULL_GEOR030101</th>\n",
+       "      <th>FULL_OOBM850104</th>\n",
+       "      <th>NT_EFC195</th>\n",
+       "      <th>AS_MeanAmphiMoment</th>\n",
+       "      <th>AS_DAYM780201</th>\n",
+       "      <th>AS_FUKS010112</th>\n",
+       "      <th>CT_RACS820104</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>3.704</td>\n",
+       "      <td>0.873</td>\n",
+       "      <td>73.519</td>\n",
+       "      <td>0.987</td>\n",
+       "      <td>-4.833</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.382</td>\n",
+       "      <td>74.556</td>\n",
+       "      <td>7.225</td>\n",
+       "      <td>1.234</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>4.444</td>\n",
+       "      <td>0.892</td>\n",
+       "      <td>62.444</td>\n",
+       "      <td>0.931</td>\n",
+       "      <td>-0.584</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.320</td>\n",
+       "      <td>56.056</td>\n",
+       "      <td>4.942</td>\n",
+       "      <td>1.853</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.901</td>\n",
+       "      <td>47.000</td>\n",
+       "      <td>1.039</td>\n",
+       "      <td>-5.664</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.164</td>\n",
+       "      <td>47.000</td>\n",
+       "      <td>5.969</td>\n",
+       "      <td>1.174</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>4.5</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.869</td>\n",
+       "      <td>69.222</td>\n",
+       "      <td>0.982</td>\n",
+       "      <td>-5.423</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.010</td>\n",
+       "      <td>69.222</td>\n",
+       "      <td>5.462</td>\n",
+       "      <td>1.138</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>-4.0</td>\n",
+       "      <td>21.591</td>\n",
+       "      <td>1.061</td>\n",
+       "      <td>71.682</td>\n",
+       "      <td>0.976</td>\n",
+       "      <td>-2.002</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.758</td>\n",
+       "      <td>66.000</td>\n",
+       "      <td>5.582</td>\n",
+       "      <td>1.453</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>5</td>\n",
+       "      <td>4.5</td>\n",
+       "      <td>6.977</td>\n",
+       "      <td>0.895</td>\n",
+       "      <td>68.512</td>\n",
+       "      <td>0.950</td>\n",
+       "      <td>-1.878</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3.090</td>\n",
+       "      <td>72.000</td>\n",
+       "      <td>5.779</td>\n",
+       "      <td>1.844</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>6</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>3.175</td>\n",
+       "      <td>1.022</td>\n",
+       "      <td>74.460</td>\n",
+       "      <td>1.010</td>\n",
+       "      <td>-3.225</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3.172</td>\n",
+       "      <td>76.722</td>\n",
+       "      <td>5.664</td>\n",
+       "      <td>1.215</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>7</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>3.704</td>\n",
+       "      <td>0.932</td>\n",
+       "      <td>69.519</td>\n",
+       "      <td>0.977</td>\n",
+       "      <td>-2.509</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.543</td>\n",
+       "      <td>72.000</td>\n",
+       "      <td>4.251</td>\n",
+       "      <td>1.560</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "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",
+       "5          4.5               6.977            0.895           68.512   \n",
+       "6         12.0               3.175            1.022           74.460   \n",
+       "7          1.5               3.704            0.932           69.519   \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",
+       "5            0.950           -1.878          0               3.090   \n",
+       "6            1.010           -3.225          0               3.172   \n",
+       "7            0.977           -2.509          0               2.543   \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  \n",
+       "5         72.000          5.779          1.844  \n",
+       "6         76.722          5.664          1.215  \n",
+       "7         72.000          4.251          1.560  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "test_data.head(8) #Viewing the first 8 observations of the test dataset"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2. Summarizing Data\n",
+    "\n",
+    "### Checking Dimensions of my train data\n",
+    "This is to enable me know the number of rows and columns in my data. This gives an idea of the size of the data (number of observations) as well as the number of features i will have to deal with.\n",
+    "This is done using the `shape` function in pandas\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(3038, 12)"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_data.shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "From the output above i have 3,038 observations with 12 features. \n",
+    "\n",
+    "Let me list all the features in my data, using the `columns` function of pandas. This "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "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": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_data.columns  #Listing all the columns i have in my dataset"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Datatypes\n",
+    "Now exploring the datatypes of each feature. This is important because different dtypes are treated diffrently. eg strings its better to convert them to categorical values. \n",
+    "The different data types are got using either `dtypes` or the `info()` function."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\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_data.info()  #Checking the data types for each faeture"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "From this i can see that almost all my features have float values, a few have values indicated as integers which in actual sense are categorical values ie 0 and 1. For this matter i don't have to do anything much with changing the types of the features. \n",
+    "\n",
+    "It seems like the data doesnot as well have any missing values since i have an *equal number of observation* in each feature."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Descriptive Statistics\n",
+    "\n",
+    "Lets generate some discriptive statistics on our data. This will give me a more idea of the kind of data i am dealing with as well as some relationships that may be associated with the different features. This will include generating for things such as;\n",
+    "- Mean, counts, sd, min,max, etc\n",
+    "- Description of the outcome\n",
+    "- Correlation between features\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>FULL_Charge</th>\n",
+       "      <th>FULL_AcidicMolPerc</th>\n",
+       "      <th>FULL_AURR980107</th>\n",
+       "      <th>FULL_DAYM780201</th>\n",
+       "      <th>FULL_GEOR030101</th>\n",
+       "      <th>FULL_OOBM850104</th>\n",
+       "      <th>NT_EFC195</th>\n",
+       "      <th>AS_MeanAmphiMoment</th>\n",
+       "      <th>AS_DAYM780201</th>\n",
+       "      <th>AS_FUKS010112</th>\n",
+       "      <th>CT_RACS820104</th>\n",
+       "      <th>CLASS</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>count</td>\n",
+       "      <td>3038.000000</td>\n",
+       "      <td>3038.000000</td>\n",
+       "      <td>3038.000000</td>\n",
+       "      <td>3038.000000</td>\n",
+       "      <td>3038.000000</td>\n",
+       "      <td>3038.000000</td>\n",
+       "      <td>3038.000000</td>\n",
+       "      <td>3038.000000</td>\n",
+       "      <td>3038.000000</td>\n",
+       "      <td>3038.000000</td>\n",
+       "      <td>3038.000000</td>\n",
+       "      <td>3038.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>mean</td>\n",
+       "      <td>2.060237</td>\n",
+       "      <td>8.521520</td>\n",
+       "      <td>0.971410</td>\n",
+       "      <td>73.668760</td>\n",
+       "      <td>0.994007</td>\n",
+       "      <td>-2.432927</td>\n",
+       "      <td>0.088545</td>\n",
+       "      <td>15.683233</td>\n",
+       "      <td>73.650828</td>\n",
+       "      <td>5.911361</td>\n",
+       "      <td>1.235255</td>\n",
+       "      <td>0.500000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>std</td>\n",
+       "      <td>3.819929</td>\n",
+       "      <td>7.586652</td>\n",
+       "      <td>0.107413</td>\n",
+       "      <td>8.527489</td>\n",
+       "      <td>0.031333</td>\n",
+       "      <td>1.707223</td>\n",
+       "      <td>0.284133</td>\n",
+       "      <td>11.575665</td>\n",
+       "      <td>9.166092</td>\n",
+       "      <td>0.693689</td>\n",
+       "      <td>0.210012</td>\n",
+       "      <td>0.500082</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>min</td>\n",
+       "      <td>-16.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.684000</td>\n",
+       "      <td>42.750000</td>\n",
+       "      <td>0.866000</td>\n",
+       "      <td>-10.432000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.041000</td>\n",
+       "      <td>42.778000</td>\n",
+       "      <td>3.533000</td>\n",
+       "      <td>0.785000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>25%</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>2.516000</td>\n",
+       "      <td>0.895000</td>\n",
+       "      <td>68.294000</td>\n",
+       "      <td>0.974000</td>\n",
+       "      <td>-3.606000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>5.587500</td>\n",
+       "      <td>67.556000</td>\n",
+       "      <td>5.459250</td>\n",
+       "      <td>1.082000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>50%</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>7.143000</td>\n",
+       "      <td>0.963000</td>\n",
+       "      <td>74.059500</td>\n",
+       "      <td>0.994000</td>\n",
+       "      <td>-2.296500</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>14.988500</td>\n",
+       "      <td>73.697000</td>\n",
+       "      <td>5.925500</td>\n",
+       "      <td>1.184000</td>\n",
+       "      <td>0.500000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>75%</td>\n",
+       "      <td>4.000000</td>\n",
+       "      <td>13.158000</td>\n",
+       "      <td>1.041000</td>\n",
+       "      <td>79.343750</td>\n",
+       "      <td>1.011000</td>\n",
+       "      <td>-1.283250</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>26.807750</td>\n",
+       "      <td>79.778000</td>\n",
+       "      <td>6.382000</td>\n",
+       "      <td>1.351000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>max</td>\n",
+       "      <td>30.000000</td>\n",
+       "      <td>46.667000</td>\n",
+       "      <td>1.451000</td>\n",
+       "      <td>101.682000</td>\n",
+       "      <td>1.196000</td>\n",
+       "      <td>3.576000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>51.280000</td>\n",
+       "      <td>103.167000</td>\n",
+       "      <td>8.662000</td>\n",
+       "      <td>2.192000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "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": [
+    "# First i will use the describe to get some descriptive statistics\n",
+    "train_data.describe()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Distribution of the outcome\n",
+    "\n",
+    "Lets first generate a bar chart to see how the predicted values are distributed by counts. Our target is having an outcome that is fairly balanced so as not to bais training process."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x1294b3d10>"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.countplot(x=\"CLASS\", data=train_data) #Plots the frequency of the 0's and 1's in the class field"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "   A similar graph could be generated using `matplotlib.pyplot` with the code below.   "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x129e65990>"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "train_data.groupby('CLASS').size().plot(kind='bar')  "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "From the outputs above we can see that our data is very balanced ie we have an equal number of True's (1) and False (0), hence no need to apply special treatment with methods like smote."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Correlation between the features\n",
+    "\n",
+    "Correlation is one of the most steps in understanding our data, especially when our data is a continous data which is the case with our case. This is can be very helpful especially during feature selection, since it will help us select features that are not very correlated to each other which could lead to an effect known as `MultiCollinearity effect`, where certian faetures have a high positive or negative correlation with the other which will mislead the the algorithm during the testing stage, this can also lead to overfitting our data.\n",
+    "\n",
+    "Correlation refers to the process of understanding the relationship between the multiple features we have in our dataset.\n",
+    "\n",
+    "Lets get a correlation of the different variables we have in our data. This will tell whether there are features that are highly dependant on the other, which might affect our model especially if Logistic or Linear regression is used which are not immune to correlation like Decision Trees. If any of the features is observed exhibiting such a pattern of high correlation, its advisable to remove such features or use Dimensionality Reduction techniques like Principle component Analysis."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>FULL_Charge</th>\n",
+       "      <th>FULL_AcidicMolPerc</th>\n",
+       "      <th>FULL_AURR980107</th>\n",
+       "      <th>FULL_DAYM780201</th>\n",
+       "      <th>FULL_GEOR030101</th>\n",
+       "      <th>FULL_OOBM850104</th>\n",
+       "      <th>NT_EFC195</th>\n",
+       "      <th>AS_MeanAmphiMoment</th>\n",
+       "      <th>AS_DAYM780201</th>\n",
+       "      <th>AS_FUKS010112</th>\n",
+       "      <th>CT_RACS820104</th>\n",
+       "      <th>CLASS</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>FULL_Charge</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.612996</td>\n",
+       "      <td>-0.490977</td>\n",
+       "      <td>-0.434603</td>\n",
+       "      <td>-0.058725</td>\n",
+       "      <td>-0.283758</td>\n",
+       "      <td>0.088068</td>\n",
+       "      <td>0.355477</td>\n",
+       "      <td>-0.365374</td>\n",
+       "      <td>-0.090570</td>\n",
+       "      <td>0.232929</td>\n",
+       "      <td>0.534602</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>FULL_AcidicMolPerc</td>\n",
+       "      <td>-0.612996</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.794796</td>\n",
+       "      <td>0.541481</td>\n",
+       "      <td>0.115201</td>\n",
+       "      <td>0.513344</td>\n",
+       "      <td>-0.143168</td>\n",
+       "      <td>-0.431590</td>\n",
+       "      <td>0.449621</td>\n",
+       "      <td>0.002334</td>\n",
+       "      <td>-0.213543</td>\n",
+       "      <td>-0.598816</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>FULL_AURR980107</td>\n",
+       "      <td>-0.490977</td>\n",
+       "      <td>0.794796</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.548253</td>\n",
+       "      <td>0.346139</td>\n",
+       "      <td>0.462712</td>\n",
+       "      <td>-0.169540</td>\n",
+       "      <td>-0.426097</td>\n",
+       "      <td>0.456260</td>\n",
+       "      <td>0.032958</td>\n",
+       "      <td>-0.403599</td>\n",
+       "      <td>-0.584111</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>FULL_DAYM780201</td>\n",
+       "      <td>-0.434603</td>\n",
+       "      <td>0.541481</td>\n",
+       "      <td>0.548253</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.010118</td>\n",
+       "      <td>0.334778</td>\n",
+       "      <td>-0.090058</td>\n",
+       "      <td>-0.408793</td>\n",
+       "      <td>0.894191</td>\n",
+       "      <td>0.055915</td>\n",
+       "      <td>-0.326792</td>\n",
+       "      <td>-0.554838</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>FULL_GEOR030101</td>\n",
+       "      <td>-0.058725</td>\n",
+       "      <td>0.115201</td>\n",
+       "      <td>0.346139</td>\n",
+       "      <td>0.010118</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.319157</td>\n",
+       "      <td>-0.230417</td>\n",
+       "      <td>-0.160269</td>\n",
+       "      <td>-0.029085</td>\n",
+       "      <td>0.040480</td>\n",
+       "      <td>-0.151935</td>\n",
+       "      <td>-0.260470</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>FULL_OOBM850104</td>\n",
+       "      <td>-0.283758</td>\n",
+       "      <td>0.513344</td>\n",
+       "      <td>0.462712</td>\n",
+       "      <td>0.334778</td>\n",
+       "      <td>0.319157</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.230561</td>\n",
+       "      <td>-0.336297</td>\n",
+       "      <td>0.275640</td>\n",
+       "      <td>-0.452769</td>\n",
+       "      <td>0.155304</td>\n",
+       "      <td>-0.453287</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>NT_EFC195</td>\n",
+       "      <td>0.088068</td>\n",
+       "      <td>-0.143168</td>\n",
+       "      <td>-0.169540</td>\n",
+       "      <td>-0.090058</td>\n",
+       "      <td>-0.230417</td>\n",
+       "      <td>-0.230561</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.178683</td>\n",
+       "      <td>-0.036844</td>\n",
+       "      <td>0.145924</td>\n",
+       "      <td>0.080898</td>\n",
+       "      <td>0.260702</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>AS_MeanAmphiMoment</td>\n",
+       "      <td>0.355477</td>\n",
+       "      <td>-0.431590</td>\n",
+       "      <td>-0.426097</td>\n",
+       "      <td>-0.408793</td>\n",
+       "      <td>-0.160269</td>\n",
+       "      <td>-0.336297</td>\n",
+       "      <td>0.178683</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.322378</td>\n",
+       "      <td>0.025580</td>\n",
+       "      <td>0.171524</td>\n",
+       "      <td>0.693552</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>AS_DAYM780201</td>\n",
+       "      <td>-0.365374</td>\n",
+       "      <td>0.449621</td>\n",
+       "      <td>0.456260</td>\n",
+       "      <td>0.894191</td>\n",
+       "      <td>-0.029085</td>\n",
+       "      <td>0.275640</td>\n",
+       "      <td>-0.036844</td>\n",
+       "      <td>-0.322378</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.045562</td>\n",
+       "      <td>-0.256060</td>\n",
+       "      <td>-0.437168</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>AS_FUKS010112</td>\n",
+       "      <td>-0.090570</td>\n",
+       "      <td>0.002334</td>\n",
+       "      <td>0.032958</td>\n",
+       "      <td>0.055915</td>\n",
+       "      <td>0.040480</td>\n",
+       "      <td>-0.452769</td>\n",
+       "      <td>0.145924</td>\n",
+       "      <td>0.025580</td>\n",
+       "      <td>0.045562</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>-0.445284</td>\n",
+       "      <td>0.033432</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>CT_RACS820104</td>\n",
+       "      <td>0.232929</td>\n",
+       "      <td>-0.213543</td>\n",
+       "      <td>-0.403599</td>\n",
+       "      <td>-0.326792</td>\n",
+       "      <td>-0.151935</td>\n",
+       "      <td>0.155304</td>\n",
+       "      <td>0.080898</td>\n",
+       "      <td>0.171524</td>\n",
+       "      <td>-0.256060</td>\n",
+       "      <td>-0.445284</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.267652</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>CLASS</td>\n",
+       "      <td>0.534602</td>\n",
+       "      <td>-0.598816</td>\n",
+       "      <td>-0.584111</td>\n",
+       "      <td>-0.554838</td>\n",
+       "      <td>-0.260470</td>\n",
+       "      <td>-0.453287</td>\n",
+       "      <td>0.260702</td>\n",
+       "      <td>0.693552</td>\n",
+       "      <td>-0.437168</td>\n",
+       "      <td>0.033432</td>\n",
+       "      <td>0.267652</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "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": [
+    "train_data.corr(method='pearson')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "From the output above, we can see that some features have fairly large correlation values of up to 0.7, however a few have very strong correlation of close to 1.\n",
+    "\n",
+    "However this output is not the best to interprete as we are having alot values. Lets transform this into a graphical output."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1080x1080 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#defining a function to help me with the plotting \n",
+    "def correlation_heatmap(train):   #will be taking the input data as an argument.\n",
+    "    correlations = train.corr(method='pearson') #compute the correlation values using the pearson method and store them to correlations\n",
+    "\n",
+    "    fig, ax = plt.subplots(figsize=(15,15))  #Setting a canvas for the plot\n",
+    "    #Now making the actual plot with annotation set as True to see the actual values in the indivual subplots\n",
+    "    sns.heatmap(correlations, vmax=1.0, center=0, fmt='.2f',  \n",
+    "                square=True, linewidths=.7, annot=True, cbar_kws={\"shrink\": .75})  \n",
+    "    plt.show();  #making the actual plot defined above\n",
+    "    \n",
+    "correlation_heatmap(train_data) #Calling the function above with our train data\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Lets check if we have the same pattern in our testing data set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1080x1080 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#Callling the function defined above on our test data\n",
+    "correlation_heatmap(test_data)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Indeed we can see that both the `train` and `test` datasets have fairly the same patterns of correlation between the features. This is good because the same treatment we apply on the train data will be expected to work fot the testing data and still we won't expect our algorithm performing better on train data and failing on the test data.\n",
+    "\n",
+    "In close observation of the output above, we can see that a few of the feature have a very strong correlation such as **`FULL_DAYM780201`** and **`AS_DAYM780201`** which have a correlation of close of close to `0.9` which is very strong. From this is expect methods such as `Logistic Regression` not to perform to the best as expected unless i apply a PCA dimensionality reduction or removing one of them. \n",
+    "\n",
+    "This wil be more explored below in the Logistic Regression algorithm training and testing step to explore the effects."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Lets now check the correlation in relation with the outcome of interest. This is to check whether there is any feature that is highly correlated with the outcome of interest."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "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": [
+    "train_data.corr(method=\"pearson\")['CLASS']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "From this, **AS_MeanAmphiMoment** has kinda of a strong correlation with the outcome of interest though not too much of a strong association. This might be one of the features we shall use when selecting our features to use, since it shows that the outcome highly depends it on hance might give a stronger score to the prediction accuracy."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Exploring the data with more plots\n",
+    "\n",
+    "Lets generate some plots that will get us a firm understading of our data. This is done with histogram, density plots and box plots\n",
+    "The considered must have plots include;\n",
+    "- Box and Whisker plots\n",
+    "- Line Graphs \n",
+    "- Histogram plots\n",
+    "- Pairwise scatter plots\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### To check Outliers"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 864x4290 with 12 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "l = train_data.columns.values\n",
+    "number_of_columns=12\n",
+    "number_of_rows = len(l)-1/number_of_columns\n",
+    "plt.figure(figsize=(number_of_columns,5*number_of_rows))\n",
+    "for i in range(0,len(l)):\n",
+    "    plt.subplot(number_of_rows + 1,number_of_columns,i+1)\n",
+    "    sns.set_style('whitegrid')\n",
+    "    sns.boxplot(train_data[l[i]],color='green',orient='v')\n",
+    "    plt.tight_layout()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can see from this plot that we do have some outliers in our data. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### To check distribution-Skewness"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1728x6864 with 12 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(2*number_of_columns,8*number_of_rows))\n",
+    "for i in range(0,len(l)):\n",
+    "    plt.subplot(number_of_rows + 1,number_of_columns,i+1)\n",
+    "    sns.distplot(train_data[l[i]],kde=True) \n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "From the graphs above, we can see that most of the features are normally distributed, with exceptions of a few such as `FULL_AcidicMolPerc` and `AS_MeanAmphiMoment`. Skewness means that within our we have some features that are fairly deviating from the mean data points.\n",
+    "\n",
+    "If most of the data is skewed we might need to tranform it to assume a Gaussian distribution."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<seaborn.axisgrid.PairGrid at 0x12986a810>"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 941.625x900 with 30 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plots for 5 selected features as generated by Recursive Feature Elimination method. \n",
+    "sns.pairplot(data=train_data, vars=['FULL_AURR980107', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n",
+    "       'CT_RACS820104'], hue=\"CLASS\") "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Plotting for null values\n",
+    "Lets first confirm if we do not have any null value in our dataset. This will correspond to a missing observation. These if left in will greatly affect the performance of our model. \n",
+    "In case we have any we shall be interested in either removing them or imputing them with anotehr value such as the mode or the mean."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "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": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Counting null values\n",
+    "train_data.isnull().sum()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "According to the output above, we don't have any count for a missing value in our data. Lets confirm this with a plot."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x12ee3a450>"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.heatmap(train_data.isnull(), yticklabels=False, cmap='viridis')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Indeed from this graph output, we can see that we don't have any missing values in our data. This is actually what we wanted, hence no need to impute any values. \n",
+    "\n",
+    "In case we had any missing data or NAs, then we could use the `train_data.dropna(inplace=True)` to remove any observation having a missing values in case thats what we wanted.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Preparing data for ML\n",
+    "This is very important because various algorithms make assumptions of our data being passed into it. It for this reason that we must as well prepare our data in a such a way to best expose the problem to the ML algorithm we are going to use.\n",
+    "\n",
+    "Options for Preprocessing include;\n",
+    "- Rescaling using sklearn's MinMaxScaler()\n",
+    "- Standardizing using sklearn's StandardScaler()\n",
+    "- Normalizing the data using sklearn's Normalizer()\n",
+    "- Binarizing the data/feature using sklearn's Binarizer with a threshold."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### i. Rescaling the data\n",
+    "This is done on the data when values have different scale, rescaling is done on the data to get it within a single range of values say 0 - 1.\n",
+    "\n",
+    "This done with sklearn's **MinMaxScaler**."
+   ]
+  },
+  {
+   "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": [
+    "# Rescale data (between 0 and 1)\n",
+    "import scipy\n",
+    "import numpy as np\n",
+    "from sklearn.preprocessing import MinMaxScaler\n",
+    "\n",
+    "array = train_data.values  #getting only values of the features\n",
+    "X = array[:,0:11]  #extracting out the input data\n",
+    "Y = array[:,11]   #extracting the output feature\n",
+    "scaler = MinMaxScaler(feature_range=(0, 1))  #defining scaler to be used with our range (0-1)\n",
+    "rescaled_X = scaler.fit_transform(X)  #Transforming the data using the scaler\n",
+    "# summarizing the transformed data\n",
+    "np.set_printoptions(precision=3)\n",
+    "print(rescaled_X[0:5,:]) #printing out the output. Its now in a range of 0 - 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The rescaled data printed above is now having values between 0 and 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### ii. Standardizing the Data\n",
+    "\n",
+    "This involves transforming features with a Gaussian distribution and differing means and standard deviations to a standard Gaussian distribution (ie mean of 0 and standard deviation of 1).  This is especially needed for models that assume a Gaussian distribution such as **Linear Regression, Logistic Regression, LDA**, etc \n",
+    "\n",
+    "Standardizing of data is done using scikit-learn's  `StandardScaler` class."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[ 7.697e-01, -1.123e+00, -1.900e-01,  1.376e-01, -6.067e-01,\n",
+       "        -7.206e-01, -3.117e-01, -1.331e+00, -2.257e-02, -3.610e-01,\n",
+       "        -9.251e-01],\n",
+       "       [ 5.079e-01, -4.109e-01, -3.763e-01, -2.432e-01, -1.181e+00,\n",
+       "        -9.245e-01,  3.208e+00, -1.303e+00, -5.924e-01,  9.021e-01,\n",
+       "         1.037e+00],\n",
+       "       [ 9.006e-01, -4.109e-01, -9.163e-01, -8.651e-03, -1.054e+00,\n",
+       "        -4.632e-02, -3.117e-01, -1.304e+00, -4.590e-01, -1.409e+00,\n",
+       "         2.318e+00],\n",
+       "       [ 7.697e-01, -5.741e-01, -7.115e-01, -8.701e-01,  1.594e-01,\n",
+       "         6.274e-01, -3.117e-01, -1.302e+00, -7.015e-01, -2.300e+00,\n",
+       "         6.989e-01],\n",
+       "       [ 1.424e+00,  2.041e-03, -3.670e-01, -1.050e+00, -4.790e-01,\n",
+       "         2.003e-01, -3.117e-01, -1.302e+00, -7.713e-02, -1.977e+00,\n",
+       "         1.447e+00]])"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Standardize data (0 mean, 1 stdev)\n",
+    "from sklearn.preprocessing import StandardScaler\n",
+    "array = train_data.values  #getting only values of the features\n",
+    "X = array[:,0:11]  #extracting out the input data\n",
+    "Y = array[:,11]    #extracting the output feature\n",
+    "\n",
+    "scaler = StandardScaler().fit(X)\n",
+    "rescaledX = scaler.transform(X)\n",
+    "# summarize transformed data\n",
+    "np.set_printoptions(precision=3)\n",
+    "rescaledX[0:5,:]\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### iii. Normalize Data\n",
+    "Normalizing in scikit-learn refers to rescaling each observation (row) to have a length of 1 (called a unit norm in linear algebra).\n",
+    "This is much used when we have data that has alot zeros with attributes of varying scales, especially when its going to be used with an algorithm that weighs input values such as neural networks and algorithms that use K-Nearest Neighbour. \n",
+    "\n",
+    "Normaliizing is done using scikit-learn's `Normalizer` class."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[ 0.048,  0.   ,  0.009,  0.711,  0.009, -0.035,  0.   ,  0.003,\n",
+       "         0.698,  0.054,  0.01 ],\n",
+       "       [ 0.04 ,  0.054,  0.009,  0.72 ,  0.01 , -0.04 ,  0.01 ,  0.006,\n",
+       "         0.686,  0.066,  0.015],\n",
+       "       [ 0.054,  0.053,  0.009,  0.724,  0.009, -0.025,  0.   ,  0.006,\n",
+       "         0.683,  0.049,  0.017],\n",
+       "       [ 0.053,  0.044,  0.009,  0.699,  0.011, -0.014,  0.   ,  0.006,\n",
+       "         0.71 ,  0.046,  0.015],\n",
+       "       [ 0.076,  0.087,  0.009,  0.658,  0.01 , -0.021,  0.   ,  0.006,\n",
+       "         0.742,  0.046,  0.016]])"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from sklearn.preprocessing import Normalizer\n",
+    "array = train_data.values  #getting only values of the features\n",
+    "X = array[:,0:11]  #extracting out the input data\n",
+    "Y = array[:,11]    #extracting the output feature\n",
+    "\n",
+    "scaler = Normalizer().fit(X)  #Defining the normalizer\n",
+    "normalizedX = scaler.transform(X) #Calling the normalizer on our dataset.\n",
+    "# summarizing transformed data\n",
+    "np.set_printoptions(precision=3)\n",
+    "normalizedX[0:5,:]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### iv.Binarizing Data\n",
+    "This refers to converting the data into a binary format where we set a threshold, and any entry above it is assigned a 1 whereas anyvalue below it is asigned a zero.\n",
+    "\n",
+    "This is important especially during feature engeneering, which is the process of using domain knowledge to extract features from raw data via data mining techniques; which features could afterwards be used to improve the accuracy of the model being used.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "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": [
+    "# binarization\n",
+    "from sklearn.preprocessing import Binarizer\n",
+    "array = train_data.values  #getting only values of the features\n",
+    "X = array[:,0:11]  #extracting out the input data\n",
+    "Y = array[:,11]    #extracting the output feature\n",
+    "\n",
+    "binarizer = Binarizer(threshold=0.0).fit(X) #Defining the standardizer \n",
+    "binaryX = binarizer.transform(X)  #Applying the binarizer to transform my data\n",
+    "# summarize transformed data\n",
+    "np.set_printoptions(precision=3)\n",
+    "print(binaryX[0:5,:]) #Output is now a either zero or 1."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**`Note`** Transforming methods of Binarixing, Normalizing, Standardizing were just tried out for learning and practice purposes, but will not be  used any where in my subsquent stages of the pipeline as they are not very really applicable to my current problem to be answered. \n",
+    "\n",
+    "Only Rescaling in this case is applicable as i have negative values in my dataset, hence a need to transform them between 0 and 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Feature Selection\n",
+    "This involves selecting features that are very relevant to our predictions. This is because including features that are irrelevant or partially relevant has a negative impact on the performance of our model especially on linear models such as Linear and Logistic Regression.\n",
+    "\n",
+    "Benefits of Feature selection are;\n",
+    "- Improves accuracy\n",
+    "- Reduces Training time\n",
+    "- Reduces overfitting\n",
+    "\n",
+    "Feature selection algorithms are generally grouped into 3 broad categories ie;   \n",
+    "\n",
+    "i) **Filter methods**    \n",
+    "These often apply statistical scores to the different features, after which features are graded basing on their scores assigned to them. Examples of such methods include `chi-square`, `information gain` and `correlation coeficient scores`.\n",
+    "\n",
+    "ii) **Wrapper Methods**    \n",
+    "These methods usually choose a group of features from the dataset and evaluate the accuracy of the model using the features chosen. A score is given to this group and after a new group is chosen to the evaluated. An example of such a method is `Recursive Feature Elimination`.\n",
+    "    \n",
+    "iii) **Embedded methods**        \n",
+    "Embedded methods learn which features best contribute to the accuracy of the model while the model is being created. The most common type of embedded feature selection methods are `regularization` methods.\n",
+    "\n",
+    "Methods for feature selection i will try out include;\n",
+    "1. Univariate Selection.\n",
+    "- Recursive Feature Selection\n",
+    "- Principle Component Analysis\n",
+    "- Feature Importance"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### a. Univariate selection\n",
+    "This method employs the chi-square goodness of fit to assign scores to each feature. \n",
+    "However running this method on the original dataset returns an error **`ValueError: Input X must be non-negative.`** which ideally means it can be employed on a negative value of which case i have negative values in my original dataset.\n",
+    "\n",
+    "For this case i employed the rescaled version of the dataset from the MinMaxScaler named as `rescaled_X`. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[1.525e+01 1.576e+02 5.423e+01 3.731e+01 4.789e+00 1.623e+01 1.882e+02\n",
+      " 2.442e+02 2.616e+01 1.339e-01 1.515e+01]\n",
+      "[[0.    0.348 0.    0.005]\n",
+      " [0.116 0.322 1.    0.011]\n",
+      " [0.116 0.246 0.    0.011]\n",
+      " [0.089 0.275 0.    0.011]\n",
+      " [0.183 0.323 0.    0.011]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.feature_selection import SelectKBest  #for extracting the best features\n",
+    "from sklearn.feature_selection import chi2  #for scoring the features\n",
+    "\n",
+    "array = train_data.values  #extracting the values only from the dataset\n",
+    "X = array[:,0:11]  #extracting the input data\n",
+    "Y = array[:,11]  #extracting the output data\n",
+    "\n",
+    "# feature extraction\n",
+    "test = SelectKBest(score_func=chi2, k=4) \n",
+    "fit = test.fit(rescaled_X, Y)\n",
+    "\n",
+    "# summarize scores\n",
+    "np.set_printoptions(precision=3)\n",
+    "print(fit.scores_)\n",
+    "features = fit.transform(rescaled_X)\n",
+    "# summary of the selected features\n",
+    "print(features[0:5,:])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## b. Recursive Feature Elimination\n",
+    "This works by removing one feature a time and then evaluate the accuracy of the model using the remaining features. It employs Logistic Regression to compute the accuracy. \n",
+    "A subgroup of the features combination that gives the highest accuracy are selected."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Num Features:  7\n",
+      "Selected Features: [ True False  True False  True  True  True  True False False  True]\n",
+      "Feature Ranking:  [1 4 1 3 1 1 1 1 5 2 1]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Index(['FULL_Charge', 'FULL_AURR980107', 'FULL_GEOR030101', 'FULL_OOBM850104',\n",
+       "       'NT_EFC195', 'AS_MeanAmphiMoment', 'CT_RACS820104'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from sklearn.feature_selection import RFE\n",
+    "from sklearn.linear_model import LogisticRegression\n",
+    "\n",
+    "array_2 = train_data.values  #extracting the values only from the dataset\n",
+    "X = array_2[:,0:11]  #extracting the input data\n",
+    "Y = array_2[:,11]  #extracting the output data\n",
+    "\n",
+    "# feature extraction\n",
+    "model = LogisticRegression()  #defining the model for accuracy detection\n",
+    "rfe = RFE(model, 7)  #Applying the model so as to get the best 7 features \n",
+    "fit = rfe.fit(X, Y)  #assessing the perfomance of the selected features\n",
+    "print(\"Num Features: \",  fit.n_features_)  #print number of features extracting\n",
+    "print(\"Selected Features:\",  fit.support_)  #prints a list of logicals of the best features selected\n",
+    "print(\"Feature Ranking: \",  fit.ranking_)   #A list of the rankings of the different features\n",
+    "\n",
+    "\n",
+    "tr = X[:,fit.support_]\n",
+    "col = train_data.columns[0:11]  #extracting only the column names of the dataset to know the actual names of the selected features\n",
+    "col[fit.support_] #Get the best features by actual names"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "For this assignment i will use features returned by this method. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## c. Principal Component Analysis\n",
+    "This operates by applying a data reduction technique by collapsing/transforming  the data features into a given number of principal components. The best principal compnents that share the lowest reemblance with the original data are returned.    \n",
+    "This is implemented using scikit-learn's `PCA`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "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"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.decomposition import PCA\n",
+    "\n",
+    "#splitting data into input and output\n",
+    "array_3 = train_data.values\n",
+    "X = array_3[:,0:11]\n",
+    "Y = array_3[:,11]\n",
+    "\n",
+    "pca = PCA(n_components=3) #feature extraction with PCA\n",
+    "fit = pca.fit(X)\n",
+    "# summarize components\n",
+    "print(\"Explained Variance: \" , fit.explained_variance_ratio_) \n",
+    "print(fit.components_)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can observe from the above output that 3 Principal Components returned have little resemblance to the source data.\n",
+    "\n",
+    "\n",
+    "## d. Feature Importance\n",
+    "This uses Decision Trees to determine the importance of each feature. A rank of the importance of each feature is returned."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[0.137 0.128 0.047 0.096 0.063 0.072 0.032 0.265 0.063 0.034 0.063]\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.ensemble import ExtraTreesClassifier\n",
+    "\n",
+    "#splitting data into input and output\n",
+    "array_4 = train_data.values\n",
+    "X = array_4[:,0:11]\n",
+    "Y = array_4[:,11]\n",
+    "\n",
+    "# feature extraction\n",
+    "model = ExtraTreesClassifier() #defining my model\n",
+    "model.fit(X, Y)  #fiting the data with the model\n",
+    "print(model.feature_importances_)  #a list of the ranks for each feature"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Evaluating Machine Learning Algorithms\n",
+    "There are 4 metrics that i will try out to assess the accuracy of my algotithm.     \n",
+    "These include;\n",
+    "- Train and Test Sets.\n",
+    "- k-fold Cross Validation.\n",
+    "- Leave One Out Cross Validation.\n",
+    "- Repeated Random Test-Train Splits."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 1. Train and Test\n",
+    "This involved splitting the input data into a training set and testing set, where the algorithm will be first training on the training portion and its performance evaluated on the testing set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy of LR on the data is:  91.52542372881356\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.model_selection import train_test_split  #for splitting the data\n",
+    "from sklearn.linear_model import LogisticRegression  #for making prediction and assessing the accuracy\n",
+    "\n",
+    "#Splitting the data into the input and output component\n",
+    "array = train_data.values\n",
+    "X = array[:,0:11]\n",
+    "Y = array[:,11]\n",
+    "\n",
+    "test_size = 0.33  #split data training portion = 67% and Testing portion = 33%\n",
+    "seed = np.random.seed(42)  #setting seed for reproducibility on other machines\n",
+    "\n",
+    "#Splitting the data\n",
+    "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size, random_state=seed)\n",
+    "\n",
+    "model = LogisticRegression()  #defining the model\n",
+    "\n",
+    "model.fit(X_train, Y_train)  #Fitting the model to the data\n",
+    "result = model.score(X_test, Y_test)  #scoring the performance of the model using known output\n",
+    "print(\"Accuracy of LR on the data is: \",  (result*100.0))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "I would be interested in knowing whether increasing or the size of the training set has an effect on the accuracy of the data. Though a 67 x 33 splitting proportion is usually recommended, in the code below i will be trying a 59 X 41 proportion and see the effect."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy:  91.41252006420547\n",
+      "MCC score is:  0.8316764343349675\n"
+     ]
+    }
+   ],
+   "source": [
+    "#Increasing the testing data set to 0.41\n",
+    "\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.linear_model import LogisticRegression\n",
+    "from sklearn.metrics import matthews_corrcoef  #Adding the mcc as a metric for determining accuracy\n",
+    "\n",
+    "array = train_data.values\n",
+    "X = array[:,0:11]\n",
+    "Y = array[:,11]\n",
+    "test_size1 = 0.41\n",
+    "seed = np.random.seed(42)  #setting seed for reproducibility on other machines\n",
+    "\n",
+    "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size1,\n",
+    "random_state=seed)\n",
+    "model = LogisticRegression()\n",
+    "model.fit(X_train, Y_train)\n",
+    "result = model.score(X_test, Y_test)\n",
+    "\n",
+    "print(\"Accuracy: \",  (result*100.0))\n",
+    "\n",
+    "#model.fit(X,Y)\n",
+    "out = model.predict(test_data)\n",
+    "\n",
+    "mcc = matthews_corrcoef(model.predict(X),Y)\n",
+    "print(\"MCC score is: \", mcc)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It turns out that slightly increasing the testing set to somehting like 41% will slightly increase the performance of an algorithm by like 2%, however reducing the size below 30% or over increasing it beyond 45% will siginificantly drop the performance of the algorithm.\n",
+    "\n",
+    "Next i will be interested in determining whether only using the features returned by the feature selection will improve the performance of the model."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#extracting out only the best 7 features the RFE an dstoring it into new\n",
+    "new = train_data[['FULL_Charge', 'FULL_AURR980107', 'FULL_GEOR030101', 'FULL_OOBM850104',\n",
+    "       'NT_EFC195', 'AS_MeanAmphiMoment', 'CT_RACS820104','CLASS']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy:  89.47368421052632\n"
+     ]
+    }
+   ],
+   "source": [
+    "#Using selected features\n",
+    "\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.linear_model import LogisticRegression\n",
+    "\n",
+    "array = new.values\n",
+    "X = array[:,0:7]\n",
+    "Y = array[:,7]\n",
+    "test_size = 0.40\n",
+    "seed = np.random.seed(42)  #setting seed for reproducibility on other machines\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))\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It turns out that Reducing the number of features will instead drop the accuracy of my model."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 2. K-Fold validation\n",
+    "Here the data the input data is split into k-fold subsets, where the model goes through multiple training and testing stages so that atleast each fold has a chance to be used for testing and training. \n",
+    "\n",
+    "This is considered as more accurate and a standard method than the test_split method as it takes into account the different subportion of the data that could bias the algorithm with a single train and test."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy: (83.63470557582075, 27.1811965862896)\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.model_selection import KFold\n",
+    "from sklearn.model_selection import cross_val_score\n",
+    "\n",
+    "array = train_data.values\n",
+    "X = array[:,0:11]\n",
+    "Y = array[:,11]\n",
+    "\n",
+    "num_folds = 10 #number of folds to use\n",
+    "seed = np.random.seed(42)  #setting seed for reproducibility on other machines\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))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Algorithm Evaluation Metrics\n",
+    "\n",
+    "The following are the common classsification metrics used;\n",
+    "- Classiffication Accuracy.\n",
+    "- Logarithmic Loss.\n",
+    "- Area Under ROC Curve.\n",
+    "- Confusion Matrix.\n",
+    "- Classiffication Report.\n",
+    "\n",
+    "### Classification Accuracy\n",
+    "This is the ratio of the number of correct predictions to the total predictions.\n",
+    "Its more suitably used when there is an equal number of observations in each class.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy: (0.8363470557582074, 0.271811965862896)\n"
+     ]
+    }
+   ],
+   "source": [
+    "array = train_data.values\n",
+    "X = array[:,0:11]\n",
+    "Y = array[:,11]\n",
+    "\n",
+    "kfold = KFold(n_splits=10, random_state=7)\n",
+    "\n",
+    "model = LogisticRegression()\n",
+    "\n",
+    "scoring = 'accuracy'\n",
+    "\n",
+    "results = cross_val_score(model, X, Y, cv=kfold, scoring=scoring)\n",
+    "print(\"Accuracy:\", (results.mean(), results.std()))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Confusion Matrix\n",
+    "This si used to give the a report of the counts of the True positive predictions, True Negative as well as False positive and False Negative."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 110,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[458  41]\n",
+      " [ 41 463]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.metrics import confusion_matrix\n",
+    "\n",
+    "array = train_data.values\n",
+    "X = array[:,0:11]\n",
+    "Y = array[:,11]\n",
+    "test_size = 0.33\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",
+    "\n",
+    "model = LogisticRegression()\n",
+    "model.fit(X_train, Y_train)\n",
+    "\n",
+    "predicted = model.predict(X_test)\n",
+    "matrix = confusion_matrix(Y_test, predicted)\n",
+    "print(matrix)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "From the report above, we can see that the alogrithm was able to accurately predict (458 + 463) outcomes however misclassified (41 + 41) outcomes. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Classiffication Report"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "         0.0       0.92      0.92      0.92       499\n",
+      "         1.0       0.92      0.92      0.92       504\n",
+      "\n",
+      "    accuracy                           0.92      1003\n",
+      "   macro avg       0.92      0.92      0.92      1003\n",
+      "weighted avg       0.92      0.92      0.92      1003\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.metrics import classification_report\n",
+    "\n",
+    "array = train_data.values\n",
+    "X = array[:,0:11]\n",
+    "Y = array[:,11]\n",
+    "test_size = 0.33\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",
+    "predicted = model.predict(X_test)\n",
+    "report = classification_report(Y_test, predicted)\n",
+    "print(report)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# PREDICTION OF OUTCOME \n",
+    "\n",
+    "Predictions wil be made using 11 different algorithms for which in every case the accuracy of the different algorithms will be evelauted as well their predictions submitted on kaggle to get thier MCC score.\n",
+    "Since in our case the predicted outcome takes on only 2 values ( ie 1 or 0) this considered as classification problem.\n",
+    "\n",
+    "Algotrithms to be used are;\n",
+    "1. Logistic Regression\n",
+    "- Gaussian Naive Bayes\n",
+    "- LinearDiscriminantAnalysis\n",
+    "- K-Nearest Neigbhour\n",
+    "- Classification And Decision Trees (CART)\n",
+    "- Support Vector Machines\n",
+    "- Random Forests\n",
+    "- AdaBoost\n",
+    "- Stochastic Gradient Boosting \n",
+    "- Stochastic X Gradient Boosting, XGB\n",
+    "- Voting Ensemble"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 1. Logistic Regression\n",
+    "Logistic regression is one the commonest algorithms used to predicting classification problems as it returns a discrete outcome. The accuracy of the predictiion will be assessed using Matthews Correlation Coefficient since the same metrics will be used on kaggle to assess my submission."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 114,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy is: 91.6065224943547 with a standard deviation of 1.3888813627806003\n",
+      "MCC accuracy is:  0.8316526340707017\n",
+      "The confusion matrix is:   \n",
+      " [[463  36]\n",
+      " [ 44 460]]\n",
+      "       CLASS\n",
+      "Index       \n",
+      "0      False\n",
+      "1      False\n",
+      "2       True\n",
+      "3       True\n",
+      "4      False\n"
+     ]
+    }
+   ],
+   "source": [
+    "#Logistic Regression prediction\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 confusion_matrix\n",
+    "\n",
+    "array_2 = train_data.values  #extracting the values only from the dataset\n",
+    "X = array_2[:,0:11]  #extracting the input data\n",
+    "Y = array_2[:,11]  #extracting the output data\n",
+    "\n",
+    "model = LogisticRegression() #defining the used model\n",
+    "\n",
+    "num_folds = 10  #numbers of folds used\n",
+    "seed = np.random.seed(42)  #setting a seed for reproducibility\n",
+    "kfold = KFold(n_splits=num_folds, random_state=seed, shuffle=True)  #Splitting the data into 10 folds\n",
+    "scoring = \"accuracy\"  #defining my scoring metric as accuracy\n",
+    "results = cross_val_score(model, X, Y, cv=kfold, scoring=scoring) #. storing results from each validation round into results\n",
+    "print(\"Accuracy is: %s with a standard deviation of %s\" % (results.mean()*100,results.std()*100)) \n",
+    "\n",
+    "model.fit(X,Y)  #fitting input data with outcome\n",
+    "\n",
+    "mcc = matthews_corrcoef(model.predict(X),Y) #computing MCC for the model\n",
+    "print(\"MCC accuracy is: \", mcc)\n",
+    "\n",
+    "#A confussion Matrix \n",
+    "predicted = model.predict(X_test)\n",
+    "matrix = confusion_matrix(Y_test, predicted)\n",
+    "print('The confusion matrix is:   \\n',matrix)\n",
+    "\n",
+    "out = model.predict(test_data)  #predicting outcome on the test_data and storing it into out\n",
+    "\n",
+    "#Storing output to a csv file \n",
+    "result = pd.DataFrame(out)  #convert the numpy object to a pandas DataFrame\n",
+    "result.columns = [\"CLASS\"]  #Adding columns names\n",
+    "result.index.name = \"Index\"\n",
+    "\n",
+    "result['CLASS'] = result['CLASS'].map({0.0:False, 1.0:True}) #converting 0 False and 1 as True as the required output\n",
+    "print(result.head())  #sample output\n",
+    "result.to_csv('/Users/kakembo/Desktop/OutMetrics/logistic_out.csv') #saving output to a csv file.\n",
+    "\n",
+    "#.    This gave me an mcc score on kaggle of   0.8328 "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Logistic Regression has an accuracy 91.61 and an MCC of 0.832, and on viewing this performance with a confusion matrix, i see that (463 + 460) were correctly predicted, while (44 + 36) were falsely predicted.\n",
+    "\n",
+    "Logistic Regression on the actual prediction gave me an MCC score of 0.832."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2. Gaussian Naive Bayes\n",
+    "This is also another algorithm reported to perform very well on classification problems.\n",
+    "It employs a Bayesian approach in learning patterns in the data as well as making predictions."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 118,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy is: 91.93622980719125 with a standard deviation of 1.6401530202739358\n",
+      "MCC accuracy is:  0.8407203694376205\n",
+      "       CLASS\n",
+      "Index       \n",
+      "0       True\n",
+      "1       True\n",
+      "2       True\n",
+      "3       True\n",
+      "4      False\n"
+     ]
+    }
+   ],
+   "source": [
+    "#GaussionNB  ie Naive Bayes\n",
+    "from sklearn.naive_bayes import GaussianNB\n",
+    "from sklearn.metrics import matthews_corrcoef\n",
+    "\n",
+    "array_2 = train_data.values  #extracting the values only from the dataset\n",
+    "X = array_2[:,0:11]  #extracting the input data\n",
+    "Y = array_2[:,11]  #extracting the output data\n",
+    "\n",
+    "model = GaussianNB() #defining the used model\n",
+    "\n",
+    "num_folds = 10  #numbers of folds used\n",
+    "seed = np.random.seed(42)  #setting a seed for reproducibility\n",
+    "kfold = KFold(n_splits=num_folds, random_state=seed, shuffle=True)  #Splitting the data into 10 folds\n",
+    "scoring = \"accuracy\"  #defining my scoring metric as accuracy\n",
+    "results = cross_val_score(model, X, Y, cv=kfold, scoring=scoring) #. storing results from each validation round into results\n",
+    "print(\"Accuracy is: %s with a standard deviation of %s\" % (results.mean()*100,results.std()*100)) \n",
+    "\n",
+    "model.fit(X,Y)  #fitting input data with outcome\n",
+    "\n",
+    "mcc = matthews_corrcoef(model.predict(X),Y) #computing MCC for the model\n",
+    "print(\"MCC accuracy is: \", mcc)\n",
+    "\n",
+    "predNB = model.predict(test_data)  #predicting outcome on the test_data and storing it into out\n",
+    "\n",
+    "#Storing output to a csv file \n",
+    "resultNB = pd.DataFrame(predNB)  #convert the numpy object to a pandas DataFrame\n",
+    "resultNB.columns = [\"CLASS\"]  #Adding columns names\n",
+    "resultNB.index.name = \"Index\"\n",
+    "\n",
+    "resultNB['CLASS'] = resultNB['CLASS'].map({0.0:False, 1.0:True})  #converting 0 False and 1 as True as the required output\n",
+    "print(resultNB.head())  #sample output\n",
+    "#  resultNB.to_csv('/Users/kakembo/Desktop/OutMetrics/GaussionNB_out.csv')   #saving output to a csv file.\n",
+    "\n",
+    "#.    This gave me a score of   0.99559"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The prediction by the GaussianNB gave me a prediction accuracy of 0.99559 on Kaggle using all the features. This is very high compared to the output i had from the Logistic Regression.\n",
+    "\n",
+    "Let me try applying only the 5 features selected during the feature selection using the RFE to see if our performance improves in any way."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.8075028226506861\n",
+      "MCC for NB is:  0.6505452702192815\n",
+      "       CLASS\n",
+      "Index       \n",
+      "0       True\n",
+      "1       True\n",
+      "2       True\n",
+      "3       True\n",
+      "4      False\n",
+      "[ True False]\n"
+     ]
+    }
+   ],
+   "source": [
+    "#GaussionNB  using a selected features \n",
+    "from sklearn.naive_bayes import GaussianNB\n",
+    "\n",
+    "dataset = train_data[['FULL_AURR980107', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n",
+    "       'CT_RACS820104', 'CLASS']]\n",
+    "array = dataset.values\n",
+    "X = array[:,0:5]\n",
+    "Y = array[:,5]\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",
+    "from sklearn.metrics import matthews_corrcoef\n",
+    "model.fit(X,Y)\n",
+    "mcc = matthews_corrcoef(model.predict(X), Y)\n",
+    "print(\"MCC for NB is: \", mcc)\n",
+    "\n",
+    "predNB = model.predict(test_data[['FULL_AURR980107', 'FULL_GEOR030101', 'FULL_OOBM850104', 'NT_EFC195',\n",
+    "       'CT_RACS820104']])\n",
+    "\n",
+    "#Converting the output to a csv file output\n",
+    "resultNB = pd.DataFrame(predNB)\n",
+    "resultNB.columns = [\"CLASS\"]\n",
+    "resultNB.index.name = \"Index\"\n",
+    "\n",
+    "resultNB['CLASS'] = resultNB['CLASS'].map({0.0:False, 1.0:True})\n",
+    "print(resultNB.head())\n",
+    "print(resultNB[\"CLASS\"].unique())\n",
+    "#resultNB.to_csv('/Users/kakembo/Desktop/OutMetrics/GaussionNB_RFE-5.csv')\n",
+    "#.    This gave me a score of   0.74760"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It turns out that Reducing my features to 5 best features as determined by RFE method during feature selection greatly reduced the accuracy of my prediction to `0.74760` on Kaggle submission.    \n",
+    "I then increased my features to 8, and then the performance increased to `0.90074` on the kaggle submssion.\n",
+    "\n",
+    "Increasing the features further to 10 improved my prediction accuracy to `0.95593`.\n",
+    "\n",
+    "From this i can conclude that for this dataset its preferred to use the entire dataset without applying any feature selection as removing any feature from the dataset will lead to a drop in the accuracy of my model predictions. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 3. LinearDiscriminantAnalysis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy is: 90.45498957790518 with a standard deviation of 1.3436057312261347\n",
+      "MCC accuracy is:  0.8377162908048379\n",
+      "       CLASS\n",
+      "Index       \n",
+      "0      False\n",
+      "1       True\n",
+      "2       True\n",
+      "3      False\n",
+      "4      False\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Trying out LinearDiscriminantAnalysis\n",
+    "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n",
+    "from sklearn.metrics import matthews_corrcoef\n",
+    "\n",
+    "array_2 = train_data.values  #extracting the values only from the dataset\n",
+    "X = array_2[:,0:11]  #extracting the input data\n",
+    "Y = array_2[:,11]  #extracting the output data\n",
+    "\n",
+    "model = LinearDiscriminantAnalysis() #defining the used model\n",
+    "\n",
+    "num_folds = 10  #numbers of folds used\n",
+    "seed = np.random.seed(42)  #setting a seed for reproducibility\n",
+    "kfold = KFold(n_splits=num_folds, random_state=seed, shuffle=True)  #Splitting the data into 10 folds\n",
+    "scoring = \"accuracy\"  #defining my scoring metric as accuracy\n",
+    "results = cross_val_score(model, tr, Y, cv=kfold, scoring=scoring) # storing results from each validation round into results\n",
+    "print(\"Accuracy is: %s with a standard deviation of %s\" % (results.mean()*100,results.std()*100)) \n",
+    "\n",
+    "model.fit(X,Y)  #fitting input data with outcome\n",
+    "\n",
+    "mcc = matthews_corrcoef(model.predict(X),Y) #computing MCC for the model\n",
+    "print(\"MCC accuracy is: \", mcc)\n",
+    "\n",
+    "predLDA = model.predict(test_data)  #predicting outcome on the test_data and storing it into out\n",
+    "\n",
+    "#Storing output to a csv file \n",
+    "resultLDA = pd.DataFrame(predLDA)  #convert the numpy object to a pandas DataFrame\n",
+    "resultLDA.columns = [\"CLASS\"]  #Adding columns names\n",
+    "resultLDA.index.name = \"Index\"\n",
+    "\n",
+    "resultLDA['CLASS'] = resultLDA['CLASS'].map({0.0:False, 1.0:True})  #converting 0 False and 1 as True as the required output\n",
+    "print(resultLDA.head())  #sample output\n",
+    "#resultLDA.to_csv('/Users/kakembo/Desktop/OutMetrics/LDA_out.csv')   #saving output to a csv file.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 4. K-Nearest Neighbour\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy is: 90.68449279138441 with a standard deviation of 1.7300074011300002\n",
+      "MCC accuracy is:  0.8690586462107053\n",
+      "       CLASS\n",
+      "Index       \n",
+      "0      False\n",
+      "1       True\n",
+      "2       True\n",
+      "3       True\n",
+      "4      False\n"
+     ]
+    }
+   ],
+   "source": [
+    "#  KNN\n",
+    "from sklearn.neighbors import KNeighborsClassifier\n",
+    "from sklearn.metrics import matthews_corrcoef\n",
+    "\n",
+    "array = train_data.values  #extracting the values only from the dataset\n",
+    "X = array[:,0:11]  #extracting the input data\n",
+    "Y = array[:,11]  #extracting the output data\n",
+    "\n",
+    "model = KNeighborsClassifier() #defining the used model\n",
+    "\n",
+    "num_folds = 10  #numbers of folds used\n",
+    "seed = np.random.seed(42)  #setting a seed for reproducibility\n",
+    "kfold = KFold(n_splits=num_folds, random_state=seed, shuffle=True)  #Splitting the data into 10 folds\n",
+    "scoring = \"accuracy\"  #defining my scoring metric as accuracy\n",
+    "results = cross_val_score(model, tr, Y, cv=kfold, scoring=scoring) # storing results from each validation round into results\n",
+    "print(\"Accuracy is: %s with a standard deviation of %s\" % (results.mean()*100,results.std()*100)) \n",
+    "\n",
+    "model.fit(X,Y)  #fitting input data with outcome\n",
+    "\n",
+    "mcc = matthews_corrcoef(model.predict(X),Y) #computing MCC for the model using known results\n",
+    "print(\"MCC accuracy is: \", mcc)\n",
+    "\n",
+    "predKNN = model.predict(test_data)  #predicting outcome on the test_data and storing it into out\n",
+    "\n",
+    "#Storing output to a csv file \n",
+    "resultKNN = pd.DataFrame(predKNN)  #convert the numpy object to a pandas DataFrame\n",
+    "resultKNN.columns = [\"CLASS\"]  #Adding columns names\n",
+    "resultKNN.index.name = \"Index\"\n",
+    "\n",
+    "resultKNN['CLASS'] = resultKNN['CLASS'].map({0.0:False, 1.0:True})  #converting 0 False and 1 as True as the required output\n",
+    "print(resultKNN.head())  #sample output\n",
+    "resultKNN.to_csv('/Users/kakembo/Desktop/OutMetrics/KNN_out.csv')   #saving output to a csv file.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 5. Decision Trees (CART)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy is: 88.90687424005559 with a standard deviation of 1.640701962492025\n",
+      "MCC accuracy is:  1.0\n",
+      "       CLASS\n",
+      "Index       \n",
+      "0       True\n",
+      "1       True\n",
+      "2      False\n",
+      "3      False\n",
+      "4      False\n"
+     ]
+    }
+   ],
+   "source": [
+    "#Classifiction And Regression Trees. (CART)\n",
+    "from sklearn.tree import DecisionTreeClassifier\n",
+    "from sklearn.metrics import matthews_corrcoef\n",
+    "\n",
+    "array_2 = train_data.values  #extracting the values only from the dataset\n",
+    "X = array_2[:,0:11]  #extracting the input data\n",
+    "Y = array_2[:,11]  #extracting the output data\n",
+    "\n",
+    "model = DecisionTreeClassifier() #defining the used model\n",
+    "\n",
+    "num_folds = 10  #numbers of folds used\n",
+    "seed = np.random.seed(42)  #setting a seed for reproducibility\n",
+    "kfold = KFold(n_splits=num_folds, random_state=seed, shuffle=True)  #Splitting the data into 10 folds\n",
+    "scoring = \"accuracy\"  #defining my scoring metric as accuracy\n",
+    "results = cross_val_score(model, tr, Y, cv=kfold, scoring=scoring) # storing results from each validation round into results\n",
+    "print(\"Accuracy is: %s with a standard deviation of %s\" % (results.mean()*100,results.std()*100)) \n",
+    "\n",
+    "model.fit(X,Y)  #fitting input data with outcome\n",
+    "\n",
+    "mcc = matthews_corrcoef(model.predict(X),Y) #computing MCC for the model\n",
+    "print(\"MCC accuracy is: \", mcc)\n",
+    "\n",
+    "predCART = model.predict(test_data)  #predicting outcome on the test_data and storing it into out\n",
+    "\n",
+    "#Storing output to a csv file \n",
+    "resultCART = pd.DataFrame(predCART)  #convert the numpy object to a pandas DataFrame\n",
+    "resultCART.columns = [\"CLASS\"]  #Adding columns names\n",
+    "resultCART.index.name = \"Index\"\n",
+    "\n",
+    "resultCART['CLASS'] = resultCART['CLASS'].map({0.0:False, 1.0:True})  #converting 0 False and 1 as True as the required output\n",
+    "print(resultCART.head())  #sample output\n",
+    "resultCART.to_csv('/Users/kakembo/Desktop/OutMetrics/CART_out.csv')   #saving output to a csv file.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 6. Extra Trees\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 105,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy is: 93.87799635226679 with a standard deviation of 1.2323341253760978\n",
+      "MCC accuracy is:  1.0\n",
+      "       CLASS\n",
+      "Index       \n",
+      "0       True\n",
+      "1       True\n",
+      "2       True\n",
+      "3       True\n",
+      "4      False\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.ensemble import ExtraTreesClassifier\n",
+    "\n",
+    "array_2 = train_data.values  #extracting the values only from the dataset\n",
+    "X = array_2[:,0:11]  #extracting the input data\n",
+    "Y = array_2[:,11]  #extracting the output data\n",
+    "\n",
+    "max_features = 3\n",
+    "num_trees = 1000\n",
+    "model = ExtraTreesClassifier(n_estimators=num_trees, max_features=max_features) #defining the used model\n",
+    "\n",
+    "num_folds = 10  #numbers of folds used\n",
+    "seed = np.random.seed(42)  #setting a seed for reproducibility\n",
+    "kfold = KFold(n_splits=num_folds, random_state=seed, shuffle=True)  #Splitting the data into 10 folds\n",
+    "scoring = \"accuracy\"  #defining my scoring metric as accuracy\n",
+    "results = cross_val_score(model, X, Y, cv=kfold, scoring=scoring) #. storing results from each validation round into results\n",
+    "print(\"Accuracy is: %s with a standard deviation of %s\" % (results.mean()*100,results.std()*100)) \n",
+    "\n",
+    "model.fit(X,Y)  #fitting input data with outcome\n",
+    "\n",
+    "mcc = matthews_corrcoef(model.predict(X),Y) #computing MCC for the model\n",
+    "print(\"MCC accuracy is: \", mcc)\n",
+    "\n",
+    "predET = model.predict(test_data)  #predicting outcome on the test_data and storing it into out\n",
+    "\n",
+    "#Storing output to a csv file \n",
+    "resultET = pd.DataFrame(predET)  #convert the numpy object to a pandas DataFrame\n",
+    "resultET.columns = [\"CLASS\"]  #Adding columns names\n",
+    "resultET.index.name = \"Index\"\n",
+    "\n",
+    "resultET['CLASS'] = resultET['CLASS'].map({0.0:False, 1.0:True})  #converting 0 False and 1 as True as the required output\n",
+    "print(resultET.head())  #sample output\n",
+    "resultET.to_csv('/Users/kakembo/Desktop/OutMetrics/Extra_Tree_out.csv')   #saving output to a csv file.\n",
+    "\n",
+    "#.    This gave me a score of   0.99559"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 7. Support Vector Machine, SVM"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy is: 91.57373632100052 with a standard deviation of 1.9906988239840162\n",
+      "MCC accuracy is:  0.9704865031499489\n",
+      "       CLASS\n",
+      "Index       \n",
+      "0       True\n",
+      "1       True\n",
+      "2       True\n",
+      "3       True\n",
+      "4      False\n"
+     ]
+    }
+   ],
+   "source": [
+    "#Support Vector Machine,  SVM\n",
+    "from sklearn.tree import DecisionTreeClassifier\n",
+    "from sklearn.metrics import matthews_corrcoef\n",
+    "\n",
+    "array_2 = train_data.values  #extracting the values only from the dataset\n",
+    "X = array_2[:,0:11]  #extracting the input data\n",
+    "Y = array_2[:,11]  #extracting the output data\n",
+    "\n",
+    "model = SVC() #defining the used model\n",
+    "\n",
+    "num_folds = 10  #numbers of folds used\n",
+    "seed = np.random.seed(42)  #setting a seed for reproducibility\n",
+    "kfold = KFold(n_splits=num_folds, random_state=seed, shuffle=True)  #Splitting the data into 10 folds\n",
+    "scoring = \"accuracy\"  #defining my scoring metric as accuracy\n",
+    "results = cross_val_score(model, tr, Y, cv=kfold, scoring=scoring) # storing results from each validation round into results\n",
+    "print(\"Accuracy is: %s with a standard deviation of %s\" % (results.mean()*100,results.std()*100)) \n",
+    "\n",
+    "model.fit(X,Y)  #fitting input data with outcome\n",
+    "\n",
+    "mcc = matthews_corrcoef(model.predict(X),Y) #computing MCC for the model\n",
+    "print(\"MCC accuracy is: \", mcc)\n",
+    "\n",
+    "predSVM = model.predict(test_data)  #predicting outcome on the test_data and storing it into out\n",
+    "\n",
+    "#Storing output to a csv file \n",
+    "resultSVM = pd.DataFrame(predSVM)  #convert the numpy object to a pandas DataFrame\n",
+    "resultSVM.columns = [\"CLASS\"]  #Adding columns names\n",
+    "resultSVM.index.name = \"Index\"\n",
+    "\n",
+    "resultSVM['CLASS'] = resultSVM['CLASS'].map({0.0:False, 1.0:True})  #converting 0 False and 1 as True as the required output\n",
+    "print(resultSVM.head())  #sample output\n",
+    "resultSVM.to_csv('/Users/kakembo/Desktop/OutMetrics/SVM_out.csv')   #saving output to a csv file.\n",
+    "\n",
+    "# This gave a score of 0.74461 on a kaggle submsion"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 8. Random Forests"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy is: 92.26517717561231 with a standard deviation of 0.8309722046784965\n",
+      "MCC accuracy is:  0.9894881966653224\n",
+      "       CLASS\n",
+      "Index       \n",
+      "0       True\n",
+      "1       True\n",
+      "2       True\n",
+      "3       True\n",
+      "4      False\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Random Forest\n",
+    "from sklearn.ensemble import RandomForestClassifier\n",
+    "\n",
+    "array = train_data.values  #extracting the values only from the dataset\n",
+    "X = array[:,0:11]  #extracting the input data\n",
+    "Y = array[:,11]  #extracting the output data\n",
+    "\n",
+    "model = RandomForestClassifier() #defining the used model\n",
+    "\n",
+    "num_folds = 10  #numbers of folds used\n",
+    "seed = np.random.seed(42)  #setting a seed for reproducibility\n",
+    "kfold = KFold(n_splits=num_folds, random_state=seed, shuffle=True)  #Splitting the data into 10 folds\n",
+    "scoring = \"accuracy\"  #defining my scoring metric as accuracy\n",
+    "results = cross_val_score(model, tr, Y, cv=kfold, scoring=scoring) # storing results from each validation round into results\n",
+    "print(\"Accuracy is: %s with a standard deviation of %s\" % (results.mean()*100,results.std()*100)) \n",
+    "\n",
+    "model.fit(X,Y)  #fitting input data with outcome\n",
+    "\n",
+    "mcc = matthews_corrcoef(model.predict(X),Y) #computing MCC for the model\n",
+    "print(\"MCC accuracy is: \", mcc)\n",
+    "\n",
+    "pred_RForest = model.predict(test_data)  #predicting outcome on the test_data and storing it into out\n",
+    "\n",
+    "#Storing output to a csv file \n",
+    "result_RForest = pd.DataFrame(pred_RForest)  #convert the numpy object to a pandas DataFrame\n",
+    "result_RForest.columns = [\"CLASS\"]  #Adding columns names\n",
+    "result_RForest.index.name = \"Index\"\n",
+    "\n",
+    "result_RForest['CLASS'] = result_RForest['CLASS'].map({0.0:False, 1.0:True})  #converting 0 False and 1 as True as the required output\n",
+    "print(result_RForest.head())  #sample output\n",
+    "result_RForest.to_csv('/Users/kakembo/Desktop/OutMetrics/RForest_out.csv')   #saving output to a csv file.\n",
+    "\n",
+    "# This gave a score of 0.80492 on a kaggle submsion"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 9. AdaBoost\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy is: 77.01895518499218 with a standard deviation of 29.02061682872751\n",
+      "MCC accuracy is:  0.8730261590913062\n",
+      "       CLASS\n",
+      "Index       \n",
+      "0       True\n",
+      "1       True\n",
+      "2      False\n",
+      "3       True\n",
+      "4      False\n"
+     ]
+    }
+   ],
+   "source": [
+    "# AdaBoost Classification\n",
+    "from sklearn.model_selection import KFold\n",
+    "from sklearn.model_selection import cross_val_score\n",
+    "from sklearn.ensemble import AdaBoostClassifier\n",
+    "\n",
+    "array_2 = train_data.values  #extracting the values only from the dataset\n",
+    "X = array_2[:,0:11]  #extracting the input data\n",
+    "Y = array_2[:,11]  #extracting the output data\n",
+    "\n",
+    "num_folds = 10  #numbers of folds used\n",
+    "seed = np.random.seed(42)  #setting a seed for reproducibility\n",
+    "num_trees = 30\n",
+    "\n",
+    "kfold = KFold(n_splits=num_folds, random_state=seed)\n",
+    "model = AdaBoostClassifier(n_estimators=num_trees, random_state=seed)\n",
+    "\n",
+    "results = cross_val_score(model, X, Y, cv=kfold)\n",
+    "\n",
+    "print(\"Accuracy is: %s with a standard deviation of %s\" % (results.mean()*100,results.std()*100)) \n",
+    "\n",
+    "model.fit(X,Y)  #fitting input data with outcome\n",
+    "\n",
+    "mcc = matthews_corrcoef(model.predict(X),Y) #computing MCC for the model\n",
+    "print(\"MCC accuracy is: \", mcc)\n",
+    "\n",
+    "predAda = model.predict(test_data)  #predicting outcome on the test_data and storing it into out\n",
+    "\n",
+    "#Storing output to a csv file \n",
+    "resultAda = pd.DataFrame(predAda)  #convert the numpy object to a pandas DataFrame\n",
+    "resultAda.columns = [\"CLASS\"]  #Adding columns names\n",
+    "resultAda.index.name = \"Index\"\n",
+    "\n",
+    "resultAda['CLASS'] = resultAda['CLASS'].map({0.0:False, 1.0:True})  #converting 0 False and 1 as True as the required output\n",
+    "print(resultAda.head())  #sample output\n",
+    "resultAda.to_csv('/Users/kakembo/Desktop/OutMetrics/Ada_out.csv')   #saving output to a csv file.\n",
+    "\n",
+    "# This gave a score of 0.79958 on a kaggle submsion"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 10. Stochastic Gradient Boosting"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy is: 79.02737971165537 with a standard deviation of 28.849018693832996\n",
+      "MCC accuracy is:  0.9355236060852458\n",
+      "       CLASS\n",
+      "Index       \n",
+      "0       True\n",
+      "1      False\n",
+      "2       True\n",
+      "3       True\n",
+      "4      False\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Stochastic Gradient Boosting Classification\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_data.values  #extracting the values only from the dataset\n",
+    "X = array[:,0:11]  #extracting the input data\n",
+    "Y = array[:,11]  #extracting the output data\n",
+    "\n",
+    "num_trees = 100  #Number of trees to use\n",
+    "seed = np.random.seed(42)\n",
+    "\n",
+    "kfold = KFold(n_splits=10, random_state=seed)\n",
+    "model = GradientBoostingClassifier(n_estimators=num_trees, random_state=seed)\n",
+    "\n",
+    "results = cross_val_score(model, X, Y, cv=kfold)\n",
+    "print(\"Accuracy is: %s with a standard deviation of %s\" % (results.mean()*100,results.std()*100)) \n",
+    "\n",
+    "model.fit(X,Y)  #fitting input data with outcome\n",
+    "\n",
+    "mcc = matthews_corrcoef(model.predict(X),Y) #computing MCC for the model\n",
+    "print(\"MCC accuracy is: \", mcc)\n",
+    "\n",
+    "predSGboost = model.predict(test_data)  #predicting outcome on the test_data and storing it into out\n",
+    "\n",
+    "#Storing output to a csv file \n",
+    "resultSGboost = pd.DataFrame(predSGboost)  #convert the numpy object to a pandas DataFrame\n",
+    "resultSGboost.columns = [\"CLASS\"]  #Adding columns names\n",
+    "resultSGboost.index.name = \"Index\"\n",
+    "\n",
+    "resultSGboost['CLASS'] = resultSGboost['CLASS'].map({0.0:False, 1.0:True})  #converting 0 False and 1 as True as the required output\n",
+    "print(resultSGboost.head())  #sample output\n",
+    "resultSGboost.to_csv('/Users/kakembo/Desktop/OutMetrics/SGboost_out.csv')   #saving output to a csv file.\n",
+    "\n",
+    "# This gave a score of 0.82551 on a kaggle submsion\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 11. XGBoost"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy is: 93.8123154420705 with a standard deviation of 1.11564218145759\n",
+      "MCC accuracy is:  0.9269836637327226\n",
+      "       CLASS\n",
+      "Index       \n",
+      "0       True\n",
+      "1       True\n",
+      "2       True\n",
+      "3       True\n",
+      "4      False\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Stochastic X Gradient Boosting Classification\n",
+    "from sklearn.model_selection import KFold\n",
+    "from sklearn.model_selection import cross_val_score\n",
+    "from xgboost import XGBClassifier\n",
+    "import numpy as np\n",
+    "\n",
+    "array = train_data.values  #extracting the values only from the dataset\n",
+    "X = array[:,0:11]  #extracting the input data\n",
+    "Y = array[:,11]  #extracting the output data\n",
+    "\n",
+    "num_trees = 100\n",
+    "seed = np.random.seed(42)  #setting a seed for reproducibility\n",
+    "kfold = KFold(n_splits=10, random_state=9, shuffle=True)\n",
+    "\n",
+    "model = XGBClassifier(n_estimators=num_trees, random_state=9)\n",
+    "results = cross_val_score(model, X, Y, cv=kfold)\n",
+    "\n",
+    "print(\"Accuracy is: %s with a standard deviation of %s\" % (results.mean()*100,results.std()*100)) \n",
+    "\n",
+    "model.fit(X,Y)  #fitting input data with outcome\n",
+    "\n",
+    "mcc = matthews_corrcoef(model.predict(X),Y) #computing MCC for the model\n",
+    "print(\"MCC accuracy is: \", mcc)\n",
+    "\n",
+    "predXGB = model.predict(test_data.values)  #predicting outcome on the test_data and storing it into out\n",
+    "\n",
+    "#Storing output to a csv file \n",
+    "resultXGB = pd.DataFrame(predXGB)  #convert the numpy object to a pandas DataFrame\n",
+    "resultXGB.columns = [\"CLASS\"]  #Adding columns names\n",
+    "resultXGB.index.name = \"Index\"\n",
+    "\n",
+    "resultXGB['CLASS'] = resultXGB['CLASS'].map({0.0:False, 1.0:True})  #converting 0 False and 1 as True as the required output\n",
+    "print(resultXGB.head())  #sample output\n",
+    "resultXGB.to_csv('/Users/kakembo/Desktop/OutMetrics/XGB_out.csv')   #saving output to a csv file.\n",
+    "\n",
+    "# This gave a score of 0.82922 on a kaggle submsion\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 12. Voting Ensembles\n",
+    "Now i will try using Ensembles to improve the prediction accuracy of my algorithms.\n",
+    "These work by combing predictions from different classiffiers, and the averaging their prediction results on the new dataset to give a more accurate prediction to the dataset.\n",
+    "\n",
+    "This is based on the fact that each model has its own weakness and strength, hence Ensembles strive at hiding the algorithms' weakness and harness the strength of each for a better prediction.    \n",
+    "They are implemented using the `VotingClassifier` function from sklearn's ensemble module.\n",
+    "\n",
+    "For this assignment i will work with, 5 models that have so far given the a good MCC score."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.9348336807364946\n",
+      "Accuracy is: 93.48336807364946 with a standard deviation of 1.2348494460266053\n",
+      "MCC accuracy is:  0.9590244476323128\n",
+      "       CLASS\n",
+      "Index       \n",
+      "0       True\n",
+      "1       True\n",
+      "2       True\n",
+      "3       True\n",
+      "4      False\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Voting Ensemble for 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",
+    "from sklearn.tree import DecisionTreeClassifier\n",
+    "from xgboost import XGBClassifier\n",
+    "from sklearn.ensemble import RandomForestClassifier\n",
+    "from sklearn.svm import SVC\n",
+    "from sklearn.ensemble import VotingClassifier\n",
+    "\n",
+    "array_2 = train_data.values  #extracting the values only from the dataset\n",
+    "X = array_2[:,0:11]  #extracting the input data\n",
+    "Y = array_2[:,11]  #extracting the output data\n",
+    "\n",
+    "num_folds = 10  #numbers of folds used\n",
+    "seed = np.random.seed(42)  #setting a seed for reproducibility\n",
+    "kfold = KFold(n_splits=num_folds, random_state=seed, shuffle=True)  #Splitting the data into 10 folds\n",
+    "scoring = \"accuracy\"  #defining my scoring metric as accuracy\n",
+    "\n",
+    "# creating  the sub models\n",
+    "estimators = []\n",
+    "model1 = LogisticRegression()\n",
+    "estimators.append(('logistic', model1))\n",
+    "\n",
+    "model2 = GaussianNB()\n",
+    "estimators.append(('NB', model2))\n",
+    "\n",
+    "model3 = DecisionTreeClassifier()\n",
+    "estimators.append(('cart', model3))\n",
+    "\n",
+    "model3 = SVC()\n",
+    "estimators.append(('svm', model3))\n",
+    "\n",
+    "model4 = XGBClassifier()\n",
+    "estimators.append(('xgb', model4))\n",
+    "\n",
+    "model5 = RandomForestClassifier()\n",
+    "estimators.append(('rfc', model5))\n",
+    "\n",
+    "# create the ensemble model\n",
+    "ensemble = VotingClassifier(estimators)\n",
+    "results = cross_val_score(ensemble, X, Y, cv=kfold)\n",
+    "print(results.mean())\n",
+    "\n",
+    "\n",
+    "print(\"Accuracy is: %s with a standard deviation of %s\" % (results.mean()*100,results.std()*100)) \n",
+    "\n",
+    "ensemble.fit(X,Y)  #fitting input data with outcome\n",
+    "\n",
+    "mcc = matthews_corrcoef(ensemble.predict(X),Y) #computing MCC for the model\n",
+    "print(\"MCC accuracy is: \", mcc)\n",
+    "\n",
+    "pred_ensemble = ensemble.predict(test_data.values)  #predicting outcome on the test_data and storing it into out\n",
+    "\n",
+    "#Storing output to a csv file \n",
+    "result_ensemble = pd.DataFrame(pred_ensemble)  #convert the numpy object to a pandas DataFrame\n",
+    "result_ensemble.columns = [\"CLASS\"]  #Adding columns names\n",
+    "result_ensemble.index.name = \"Index\"\n",
+    "\n",
+    "result_ensemble['CLASS'] = result_ensemble['CLASS'].map({0.0:False, 1.0:True})  #converting 0 False and 1 as True as the required output\n",
+    "print(result_ensemble.head())  #sample output\n",
+    "result_ensemble.to_csv('/Users/kakembo/Desktop/OutMetrics/ensemble_out.csv')   #saving output to a csv file.\n",
+    "\n",
+    "# This gave a score of 0.85148 on a kaggle submsion"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Summary of the Algorithms used\n",
+    "\n",
+    "Upto now, i have used a total of 12 algorithms to make my predictions.    \n",
+    "The purpose of this section will be to give a summary of the accuracy of each of the algorithms to give a better comparison between the algorithms.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 125,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Model  Mean_Score  Std_Deviation  MCC\n",
+      "LR:   0.914403    (0.015486)    MCC: 0.822529\n",
+      "LDA:   0.919342    (0.014631)    MCC: 0.837499\n",
+      "KNN:   0.903704    (0.024910)    MCC: 0.813543\n",
+      "CART:   0.897531    (0.023886)    MCC: 0.808861\n",
+      "NB:   0.921399    (0.018445)    MCC: 0.825922\n",
+      "SVM:   0.890535    (0.019581)    MCC: 0.792345\n",
+      "RF:   0.931276    (0.015944)    MCC: 0.849080\n",
+      "Ada:   0.917695    (0.014374)    MCC: 0.838748\n",
+      "SGB:   0.938272    (0.015832)    MCC: 0.878831\n",
+      "XGB:   0.937860    (0.016812)    MCC: 0.891446\n",
+      "ET:   0.938683    (0.017600)    MCC: 0.858510\n"
+     ]
+    }
+   ],
+   "source": [
+    "#Summarizig the algorithms used.\n",
+    "array_2 = train_data.values  #extracting the values only from the dataset\n",
+    "X = array_2[:,0:11]  #extracting the input data\n",
+    "Y = array_2[:,11]  #extracting the output data\n",
+    "\n",
+    "validation_size = 0.20\n",
+    "seed = np.random.seed(42)  #Helps to keep the same randomness between the train and testing data\n",
+    "X_train, X_test, Y_train, Y_test = model_selection.train_test_split(X, Y, test_size = validation_size, random_state = seed)\n",
+    "\n",
+    "#Lets do a 10-fold cross validation\n",
+    "scoring = 'accuracy'  #ratio of correct in the whole data\n",
+    "\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(('RF', RandomForestClassifier()))\n",
+    "models.append(('Ada', AdaBoostClassifier(n_estimators=num_trees, random_state=seed)))\n",
+    "models.append(('SGB', GradientBoostingClassifier(n_estimators=num_trees, random_state=seed)))\n",
+    "models.append(('XGB', XGBClassifier(n_estimators=num_trees, random_state=9)))\n",
+    "models.append(('ET', ExtraTreesClassifier(n_estimators=1000, max_features=3)))\n",
+    "\n",
+    "#evaluating each model and will store indivual output the list\n",
+    "results = []\n",
+    "names= []\n",
+    "\n",
+    "print(\"Model \", \"Mean_Score\", \" Std_Deviation\", \" MCC\") #Headers for the output results\n",
+    "\n",
+    "for name, model in models:\n",
+    "    kfold = model_selection.KFold(n_splits=10, random_state=seed)\n",
+    "    cv_results = model_selection.cross_val_score(model, X_train, Y_train, cv=kfold, scoring=scoring)\n",
+    "    results.append(cv_results)\n",
+    "    names.append(name)\n",
+    "    \n",
+    "    model.fit(X_train,Y_train)\n",
+    "    mcc = matthews_corrcoef(model.predict(X_test),Y_test)\n",
+    "    \n",
+    "    msg = \"%s:   %f    (%f)    MCC: %f\" % (name, cv_results.mean(), cv_results.std(), mcc)\n",
+    "    print(msg)\n",
+    "    \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 136,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#A Box Plot Summarizing the comparison in Performance of the models\n",
+    "\n",
+    "import matplotlib.pyplot as plt  #For Generating the plots\n",
+    "\n",
+    "fig = plt.figure()\n",
+    "fig.suptitle('Algorithm Comparison')\n",
+    "ax = fig.add_subplot(111)\n",
+    "plt.boxplot(results, widths = 0.8, patch_artist = True)  #Changing teh width of the bars using the width attribute\n",
+    "ax.set_xticklabels(names)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "From this i can see that `Random Forests, RF`, `Stochastic Gradient Boosting, SGB`, `XG-boost, XGB` and `Extra Trees, ET` have the highest accuracy with XG-boost having the highest MCC score. \n",
+    "\n",
+    "However in my predictions submitted on kaggle, `Gaussian Naive Bayes, NB` gave the highest prediction accuracy (MCC) of 0.99559 that was not comparable to any other algorithms, using all the features. Its worthy to conclude in this prediction problem that reducing the number of features by even one, the accuracy of the prediction will decrease much further implying we did not have any redundant feature in the dataset.    \n",
+    "\n",
+    "This is however not the case with every prediction problem, as to some (especially those with multiple features) perorming a feature selection with greatly imporove the prediction accuracy."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Finalizing my Model\n",
+    "\n",
+    "Since the Gaussian Naive Bayes gave me the highest prediction score i will be interested in saving it to a file, so that next time when i need to reuse it to make a prediction, i can simply reload it.\n",
+    "For this i will use **`joblib`**'s <u>dump</u> function."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 122,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['/Users/kakembo/Desktop/OutMetrics/finalized_GaussianNB_model.sav']"
+      ]
+     },
+     "execution_count": 122,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Saving the GaussianNB Model Using joblib\n",
+    "\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.naive_bayes import GaussianNB\n",
+    "from sklearn.externals.joblib import dump\n",
+    "from sklearn.externals.joblib import load\n",
+    "\n",
+    "array = train_data.values\n",
+    "X = array[:,0:11]\n",
+    "Y = array[:,11]\n",
+    "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.33, random_state=7)\n",
+    "\n",
+    "# Fit the model on 33%\n",
+    "model = GaussianNB()\n",
+    "model.fit(X_train, Y_train)\n",
+    "\n",
+    "# save the model to disk\n",
+    "filename = '/Users/kakembo/Desktop/OutMetrics/finalized_GaussianNB_model.sav'\n",
+    "dump(model, filename)\n",
+    "\n",
+    "\n",
+    "\n",
+    "# To load it later from disk for use:\n",
+    "#   loaded_model = load(filename)\n",
+    "#   result = loaded_model.score(X_test, Y_test)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    " \n",
+    " \n",
+    " \n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# References\n",
+    "\n",
+    "- https://towardsdatascience.com/exploratory-data-analysis-8fc1cb20fd15  - Exploratoty Data analysis article on `towardsdatascience.com` by `Prasad Patil`\n",
+    "\n",
+    "- https://medium.com/@ODSC/transforming-skewed-data-for-machine-learning-90e6cc364b0 - Skewness in data and. how transform skewed data.\n",
+    "\n",
+    "- https://machinelearningmastery.com/prepare-data-machine-learning-python-scikit-learn/  - preparing Data for machine Learning by Jason Brownlee on May 18, 2016 in Python Machine Learning\n",
+    "\n",
+    "- https://www.dataquest.io/blog/machine-learning-preparing-data/ - Data Cleaning and Preparation for Machine Learning\n",
+    "\n",
+    "- https://machinelearningmastery.com/an-introduction-to-feature-selection/ - Introduction to feature selelction, By Jason Brownlee on October 6, 2014 in Machine Learning Process\n",
+    "\n",
+    "- https://www.tutorialspoint.com/machine_learning_with_python/machine_learning_with_python_data_feature_selection.htm - Machine learning with Python from Tutorialspoint.com \n",
+    "\n",
+    "- https://medium.com/@Mandysidana/machine-learning-types-of-classification-9497bd4f2e14 - Machine Learning Classification algorithms on medium.com by Mandy Sidana\n",
+    "\n",
+    "- https://towardsdatascience.com/why-feature-correlation-matters-a-lot-847e8ba439c4\n",
+    "\n",
+    "- https://towardsdatascience.com/decision-tree-in-machine-learning-e380942a4c96\n",
+    "\n",
+    "- https://machinelearningmastery.com/understand-problem-get-better-results-using-exploratory-data-analysis/\n",
+    "\n",
+    "- https://towardsdatascience.com/decision-tree-in-machine-learning-e380942a4c96 - Implementing a decision tree in Python\n",
+    "\n",
+    "- https://machinelearningmastery.com/logistic-regression-for-machine-learning/ - Logistic Regression for Machine Learning By Jason Brownlee on April 1, 2016 in Machine Learning Algorithms \n",
+    "\n",
+    "- https://towardsdatascience.com/logistic-regression-using-python-sklearn-numpy-mnist-handwriting-recognition-matplotlib-a6b31e2b166a - Logistic Regression using Python (scikit-learn) by Michael Galarnyk\n",
+    "\n",
+    "- https://machinelearningmastery.com/naive-bayes-for-machine-learning/ - Naive Bayes for Machine Learning By Jason Brownlee on April 11, 2016 in Machine Learning Algorithms \n",
+    "\n",
+    "- https://medium.com/@LSchultebraucks/gaussian-naive-bayes-19156306079b - Gaussian Naive Bayes  by Lasse Schultebraucks\n",
+    "\n",
+    "- https://towardsdatascience.com/how-to-impliment-a-gaussian-naive-bayes-classifier-in-python-from-scratch-11e0b80faf5a - How to implement a Gaussian Naive Bayes Classifier in Python from scratch? by Vasile Păpăluță on towardsdatascience.com\n",
+    "\n",
+    "- https://scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.GaussianNB.html - Implementing GaussianNB in sklearn\n",
+    "\n",
+    "- https://scikit-learn.org/stable/modules/generated/sklearn.discriminant_analysis.LinearDiscriminantAnalysis.html - Implementing LinearDiscriminantAnalysis in sklearn\n",
+    "\n",
+    "- https://towardsdatascience.com/linear-discriminant-analysis-in-python-76b8b17817c2 - Linear Discriminant Analysis In Python by Cory Maklin on towardsdatascience.com\n",
+    "\n",
+    "- https://towardsdatascience.com/ensemble-learning-using-scikit-learn-85c4531ff86a - Building an Ensemble Learning Model Using Scikit-learn by Eijaz Allibhai\n",
+    "\n",
+    "\n",
+    "---\n",
+    "*Special credits and thanks*  to the [Github notebook](https://github.com/atwine/ace-class-notes/blob/master/Thur%2020%20Feb/ACE_ClassML%20Pipeline_edit.ipynb) prepared by `Mr.Atwine Mugume Twinamatsiko`  that was a very handful template for me to come up with my final notebook\n",
+    "\n",
+    "---\n",
+    "---\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": "3.7.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/Thur 20 Feb/ACE_ClassML Pipeline.ipynb b/Thur 20 Feb/ACE_ClassML Pipeline.ipynb
index e55fe6d..2958e73 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": 2,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -41,14 +41,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "/Users/drjamesmugume/Desktop/ACE CLASS NOTES/Thur 20 Feb\r\n"
+      "/Users/kakembo/Desktop/MSBT/BigData/ace-class-notes/Thur 20 Feb\r\n"
      ]
     }
    ],
@@ -58,15 +58,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "ACE_ClassML Pipeline.ipynb \u001b[31mhousing.csv\u001b[m\u001b[m\r\n",
-      "\u001b[31mdiabetes.csv\u001b[m\u001b[m\r\n"
+      "ACE_ClassML Pipeline.ipynb \u001b[1m\u001b[31mhousing.csv\u001b[m\u001b[m\r\n",
+      "\u001b[1m\u001b[31mdiabetes.csv\u001b[m\u001b[m\r\n"
      ]
     }
    ],
@@ -77,16 +77,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
-    "pd.read"
+    "#pd.read"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -123,7 +123,7 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>0</th>\n",
+       "      <td>0</td>\n",
        "      <td>6</td>\n",
        "      <td>148</td>\n",
        "      <td>72</td>\n",
@@ -135,7 +135,7 @@
        "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1</th>\n",
+       "      <td>1</td>\n",
        "      <td>1</td>\n",
        "      <td>85</td>\n",
        "      <td>66</td>\n",
@@ -147,7 +147,7 @@
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2</th>\n",
+       "      <td>2</td>\n",
        "      <td>8</td>\n",
        "      <td>183</td>\n",
        "      <td>64</td>\n",
@@ -159,7 +159,7 @@
        "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>3</th>\n",
+       "      <td>3</td>\n",
        "      <td>1</td>\n",
        "      <td>89</td>\n",
        "      <td>66</td>\n",
@@ -171,7 +171,7 @@
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>4</th>\n",
+       "      <td>4</td>\n",
        "      <td>0</td>\n",
        "      <td>137</td>\n",
        "      <td>40</td>\n",
@@ -202,7 +202,7 @@
        "4                     2.288   33        1  "
       ]
      },
-     "execution_count": 6,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -228,7 +228,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -237,7 +237,7 @@
        "(768, 9)"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -252,7 +252,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -263,7 +263,7 @@
        "      dtype='object')"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -286,7 +286,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -304,7 +304,7 @@
        "dtype: object"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -336,7 +336,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -373,7 +373,7 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>count</th>\n",
+       "      <td>count</td>\n",
        "      <td>768.000000</td>\n",
        "      <td>768.000000</td>\n",
        "      <td>768.000000</td>\n",
@@ -385,7 +385,7 @@
        "      <td>768.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>mean</th>\n",
+       "      <td>mean</td>\n",
        "      <td>3.845052</td>\n",
        "      <td>120.894531</td>\n",
        "      <td>69.105469</td>\n",
@@ -397,7 +397,7 @@
        "      <td>0.348958</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>std</th>\n",
+       "      <td>std</td>\n",
        "      <td>3.369578</td>\n",
        "      <td>31.972618</td>\n",
        "      <td>19.355807</td>\n",
@@ -409,7 +409,7 @@
        "      <td>0.476951</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>min</th>\n",
+       "      <td>min</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
@@ -421,7 +421,7 @@
        "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>25%</th>\n",
+       "      <td>25%</td>\n",
        "      <td>1.000000</td>\n",
        "      <td>99.000000</td>\n",
        "      <td>62.000000</td>\n",
@@ -433,7 +433,7 @@
        "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>50%</th>\n",
+       "      <td>50%</td>\n",
        "      <td>3.000000</td>\n",
        "      <td>117.000000</td>\n",
        "      <td>72.000000</td>\n",
@@ -445,7 +445,7 @@
        "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>75%</th>\n",
+       "      <td>75%</td>\n",
        "      <td>6.000000</td>\n",
        "      <td>140.250000</td>\n",
        "      <td>80.000000</td>\n",
@@ -457,7 +457,7 @@
        "      <td>1.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>max</th>\n",
+       "      <td>max</td>\n",
        "      <td>17.000000</td>\n",
        "      <td>199.000000</td>\n",
        "      <td>122.000000</td>\n",
@@ -494,7 +494,7 @@
        "max     67.100000                  2.420000   81.000000    1.000000  "
       ]
      },
-     "execution_count": 10,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -514,22 +514,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1e9b4c50>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x122f3bf10>"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAAEDCAYAAADOc0QpAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjAsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+17YcXAAAOIElEQVR4nO3df6zd9V3H8edrdGxz6Ph1bbAtXhK6EIjCyA1C8I8JOgcYiwYIZBkVm/QPmWFi4upiYkxcAiYOhxpiI5OOsDE2N1sZmZLC/LENxoVBGeDGHcJoA/Ru/JgLMgd7+8f5NBy6tve099x76YfnI7k53+/n+znnfA5pnj18+z3npqqQJPXlTUu9AEnS+Bl3SeqQcZekDhl3SeqQcZekDhl3SerQsqVeAMDRRx9dk5OTS70MSTqo3Hvvvd+tqok9HXtdxH1ycpLp6emlXoYkHVSSPLG3Y56WkaQOGXdJ6pBxl6QOGXdJ6pBxl6QOjRT3JI8neTDJ/Umm29iRSW5P8mi7PaKNJ8m1SWaSbEty6kK+AEnST9qfd+6/UlWnVNVU298AbK2q1cDWtg9wDrC6/awHrhvXYiVJo5nPaZk1wKa2vQk4f2j8EzVwF3B4kmPm8TySpP006oeYCvjXJAX8XVVtBJZX1VPt+NPA8ra9Anhy6L7b29hTQ2MkWc/gnT3HHnvsga1+kU1u+MJSL6Erj1913lIvQerWqHH/5arakeRngduT/NfwwaqqFv6Rtb8gNgJMTU3566AkaYxGOi1TVTva7U7g88BpwDO7Tre0251t+g5g1dDdV7YxSdIimTPuSd6e5Kd3bQPvAb4BbAHWtmlrgc1tewtwabtq5nTghaHTN5KkRTDKaZnlwOeT7Jr/yar6YpJ7gFuSrAOeAC5q828DzgVmgBeBy8a+aknSPs0Z96p6DDh5D+PfA87ew3gBl49ldZKkA+InVCWpQ8Zdkjpk3CWpQ8Zdkjpk3CWpQ8Zdkjpk3CWpQ8Zdkjpk3CWpQ8Zdkjpk3CWpQ8Zdkjpk3CWpQ8Zdkjpk3CWpQ8Zdkjpk3CWpQ8Zdkjpk3CWpQ8Zdkjpk3CWpQ8Zdkjpk3CWpQ8Zdkjpk3CWpQ8Zdkjpk3CWpQ8Zdkjpk3CWpQ8Zdkjpk3CWpQ8Zdkjo0ctyTHJLk60lubfvHJbk7yUySTyc5tI2/pe3PtOOTC7N0SdLe7M879yuAR4b2rwauqarjgeeAdW18HfBcG7+mzZMkLaKR4p5kJXAe8PdtP8BZwGfblE3A+W17TdunHT+7zZckLZJR37n/FfBHwI/b/lHA81X1ctvfDqxo2yuAJwHa8RfafEnSIpkz7kl+A9hZVfeO84mTrE8ynWR6dnZ2nA8tSW94o7xzPxP4zSSPAzczOB3zMeDwJMvanJXAjra9A1gF0I6/A/je7g9aVRuraqqqpiYmJub1IiRJrzVn3Kvqj6tqZVVNAhcDd1TV+4A7gQvatLXA5ra9pe3Tjt9RVTXWVUuS9mk+17l/CLgyyQyDc+rXt/HrgaPa+JXAhvktUZK0v5bNPeVVVfUl4Ett+zHgtD3MeQm4cAxrkyQdID+hKkkdMu6S1CHjLkkdMu6S1CHjLkkdMu6S1CHjLkkdMu6S1CHjLkkdMu6S1CHjLkkdMu6S1CHjLkkdMu6S1CHjLkkdMu6S1CHjLkkdMu6S1CHjLkkdMu6S1CHjLkkdMu6S1CHjLkkdMu6S1CHjLkkdMu6S1CHjLkkdMu6S1CHjLkkdMu6S1CHjLkkdMu6S1KE5457krUm+luSBJA8l+bM2flySu5PMJPl0kkPb+Fva/kw7PrmwL0GStLtR3rn/EDirqk4GTgHem+R04Grgmqo6HngOWNfmrwOea+PXtHmSpEU0Z9xr4Adt983tp4CzgM+28U3A+W17TdunHT87Sca2YknSnEY6557kkCT3AzuB24FvA89X1cttynZgRdteATwJ0I6/ABw1zkVLkvZtpLhX1StVdQqwEjgNOGG+T5xkfZLpJNOzs7PzfThJ0pD9ulqmqp4H7gTOAA5PsqwdWgnsaNs7gFUA7fg7gO/t4bE2VtVUVU1NTEwc4PIlSXsyytUyE0kOb9tvA34NeIRB5C9o09YCm9v2lrZPO35HVdU4Fy1J2rdlc0/hGGBTkkMY/GVwS1XdmuRh4OYkfw58Hbi+zb8euDHJDPAscPECrFuStA9zxr2qtgHv2sP4YwzOv+8+/hJw4VhWJ0k6IH5CVZI6ZNwlqUPGXZI6ZNwlqUPGXZI6ZNwlqUPGXZI6ZNwlqUOjfEJV0uvc5IYvLPUSuvL4Vect9RLmzXfuktQh4y5JHTLuktQh4y5JHTLuktQh4y5JHTLuktQh4y5JHTLuktQh4y5JHTLuktQh4y5JHTLuktQh4y5JHTLuktQh4y5JHTLuktQh4y5JHTLuktQh4y5JHTLuktQh4y5JHTLuktQh4y5JHZoz7klWJbkzycNJHkpyRRs/MsntSR5tt0e08SS5NslMkm1JTl3oFyFJeq1R3rm/DPxhVZ0InA5cnuREYAOwtapWA1vbPsA5wOr2sx64buyrliTt05xxr6qnquq+tv0/wCPACmANsKlN2wSc37bXAJ+ogbuAw5McM/aVS5L2ar/OuSeZBN4F3A0sr6qn2qGngeVtewXw5NDdtrcxSdIiGTnuSQ4D/hH4YFV9f/hYVRVQ+/PESdYnmU4yPTs7uz93lSTNYaS4J3kzg7DfVFWfa8PP7Drd0m53tvEdwKqhu69sY69RVRuraqqqpiYmJg50/ZKkPRjlapkA1wOPVNVHhw5tAda27bXA5qHxS9tVM6cDLwydvpEkLYJlI8w5E3g/8GCS+9vYh4GrgFuSrAOeAC5qx24DzgVmgBeBy8a6YknSnOaMe1X9J5C9HD57D/MLuHye65IkzYOfUJWkDhl3SeqQcZekDhl3SeqQcZekDhl3SeqQcZekDhl3SeqQcZekDhl3SeqQcZekDhl3SeqQcZekDhl3SeqQcZekDhl3SeqQcZekDhl3SeqQcZekDhl3SeqQcZekDhl3SeqQcZekDhl3SeqQcZekDhl3SeqQcZekDhl3SeqQcZekDhl3SeqQcZekDhl3SerQnHFP8vEkO5N8Y2jsyCS3J3m03R7RxpPk2iQzSbYlOXUhFy9J2rNR3rnfALx3t7ENwNaqWg1sbfsA5wCr28964LrxLFOStD/mjHtV/Tvw7G7Da4BNbXsTcP7Q+Cdq4C7g8CTHjGuxkqTRHOg59+VV9VTbfhpY3rZXAE8OzdvexiRJi2je/6BaVQXU/t4vyfok00mmZ2dn57sMSdKQA437M7tOt7TbnW18B7BqaN7KNvYTqmpjVU1V1dTExMQBLkOStCcHGvctwNq2vRbYPDR+abtq5nTghaHTN5KkRbJsrglJPgW8Gzg6yXbgT4GrgFuSrAOeAC5q028DzgVmgBeByxZgzZKkOcwZ96q6ZC+Hzt7D3AIun++iJEnz4ydUJalDxl2SOmTcJalDxl2SOmTcJalDxl2SOmTcJalDxl2SOmTcJalDxl2SOmTcJalDxl2SOmTcJalDxl2SOmTcJalDxl2SOmTcJalDxl2SOmTcJalDxl2SOmTcJalDxl2SOmTcJalDxl2SOmTcJalDxl2SOmTcJalDxl2SOmTcJalDxl2SOmTcJalDxl2SOmTcJalDCxL3JO9N8s0kM0k2LMRzSJL2buxxT3II8LfAOcCJwCVJThz380iS9m4h3rmfBsxU1WNV9X/AzcCaBXgeSdJeLFuAx1wBPDm0vx34pd0nJVkPrG+7P0jyzQVYyxvV0cB3l3oRc8nVS70CLQH/bI7Xz+/twELEfSRVtRHYuFTP37Mk01U1tdTrkHbnn83FsxCnZXYAq4b2V7YxSdIiWYi43wOsTnJckkOBi4EtC/A8kqS9GPtpmap6OckHgH8BDgE+XlUPjft5tE+e7tLrlX82F0mqaqnXIEkaMz+hKkkdMu6S1CHjLkkdWrLr3DUeSU5g8AngFW1oB7Clqh5ZulVJWmq+cz+IJfkQg693CPC19hPgU35hm17Pkly21GvonVfLHMSSfAs4qap+tNv4ocBDVbV6aVYm7VuS71TVsUu9jp55Wubg9mPg54Andhs/ph2TlkySbXs7BCxfzLW8ERn3g9sHga1JHuXVL2s7Fjge+MCSrUoaWA78OvDcbuMBvrL4y3ljMe4Hsar6YpJ3Mvia5eF/UL2nql5ZupVJANwKHFZV9+9+IMmXFn85byyec5ekDnm1jCR1yLhLUoeMu7qRZGWSzUkeTfLtJB9rl4Xu6z4fXqz1SYvJuKsLSQJ8Dvindn3/O4HDgI/McVfjri4Zd/XiLOClqvoHgHa10B8Av5vk95L8za6JSW5N8u4kVwFvS3J/kpvasUuTbEvyQJIb29hkkjva+NYkx7bxG5Jcl+SuJI+1x/x4kkeS3DD0fO9J8tUk9yX5TJLDFu2/it6wjLt6cRJw7/BAVX0f+A57ueS3qjYA/1tVp1TV+5KcBPwJcFZVnQxc0ab+NbCpqn4RuAm4duhhjgDOYPAXyRbgmraWX0hySpKj22P+alWdCkwDV47jBUv74nXu0qvOAj5TVd8FqKpn2/gZwG+37RuBvxi6zz9XVSV5EHimqh4ESPIQMMngdwifCHx5cOaIQ4GvLvDrkIy7uvEwcMHwQJKfYfCJ3ed57f+lvnWMz/vDdvvjoe1d+8uAV4Dbq+qSMT6nNCdPy6gXW4GfSnIpQJJDgL8EbgAeA05J8qYkqxh8oneXHyV5c9u+A7gwyVHtMY5s419h8IveAd4H/Md+rOsu4Mwkx7fHfHv7VLG0oIy7ulCDj1r/FoM4Pwp8C3iJwdUwXwb+m8G7+2uB+4buuhHYluSm9ovcPwL8W5IHgI+2Ob8PXNa+COv9vHoufpR1zQK/w+BrmLcxOCVzwoG+TmlUfv2AJHXId+6S1CHjLkkdMu6S1CHjLkkdMu6S1CHjLkkdMu6S1CHjLkkd+n/0hCwwEIJ7xAAAAABJRU5ErkJggg==\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -561,7 +561,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 11,
    "metadata": {
     "scrolled": true
    },
@@ -600,7 +600,7 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>Pregnancies</th>\n",
+       "      <td>Pregnancies</td>\n",
        "      <td>1.000000</td>\n",
        "      <td>0.129459</td>\n",
        "      <td>0.141282</td>\n",
@@ -612,7 +612,7 @@
        "      <td>0.221898</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>Glucose</th>\n",
+       "      <td>Glucose</td>\n",
        "      <td>0.129459</td>\n",
        "      <td>1.000000</td>\n",
        "      <td>0.152590</td>\n",
@@ -624,7 +624,7 @@
        "      <td>0.466581</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>BloodPressure</th>\n",
+       "      <td>BloodPressure</td>\n",
        "      <td>0.141282</td>\n",
        "      <td>0.152590</td>\n",
        "      <td>1.000000</td>\n",
@@ -636,7 +636,7 @@
        "      <td>0.065068</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>SkinThickness</th>\n",
+       "      <td>SkinThickness</td>\n",
        "      <td>-0.081672</td>\n",
        "      <td>0.057328</td>\n",
        "      <td>0.207371</td>\n",
@@ -648,7 +648,7 @@
        "      <td>0.074752</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>Insulin</th>\n",
+       "      <td>Insulin</td>\n",
        "      <td>-0.073535</td>\n",
        "      <td>0.331357</td>\n",
        "      <td>0.088933</td>\n",
@@ -660,7 +660,7 @@
        "      <td>0.130548</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>BMI</th>\n",
+       "      <td>BMI</td>\n",
        "      <td>0.017683</td>\n",
        "      <td>0.221071</td>\n",
        "      <td>0.281805</td>\n",
@@ -672,7 +672,7 @@
        "      <td>0.292695</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>DiabetesPedigreeFunction</th>\n",
+       "      <td>DiabetesPedigreeFunction</td>\n",
        "      <td>-0.033523</td>\n",
        "      <td>0.137337</td>\n",
        "      <td>0.041265</td>\n",
@@ -684,7 +684,7 @@
        "      <td>0.173844</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>Age</th>\n",
+       "      <td>Age</td>\n",
        "      <td>0.544341</td>\n",
        "      <td>0.263514</td>\n",
        "      <td>0.239528</td>\n",
@@ -696,7 +696,7 @@
        "      <td>0.238356</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>Outcome</th>\n",
+       "      <td>Outcome</td>\n",
        "      <td>0.221898</td>\n",
        "      <td>0.466581</td>\n",
        "      <td>0.065068</td>\n",
@@ -746,7 +746,7 @@
        "Outcome                   0.238356  1.000000  "
       ]
      },
-     "execution_count": 8,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -757,7 +757,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -767,7 +767,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 13,
    "metadata": {
     "scrolled": false
    },
@@ -775,16 +775,16 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x10d76e750>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x12315bc90>"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 432x432 with 2 Axes>"
       ]
@@ -802,7 +802,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -820,7 +820,7 @@
        "Name: Outcome, dtype: float64"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -867,22 +867,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1ae0e0d0>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x1232e5a90>"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXIAAAFyCAYAAADoJFEJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAgAElEQVR4nO3de5RkVX328e8zDPcAEhjwggNKAB0VvAwCgddEFCMxr/ECAoIaNRKjMaAxiaCJJhokxpiseOEVAwSJwXjDS0wQRJQQQTKDIOCAFwRFjQ6gQhBE8Hn/2Kema3p6eqqnq2rXnn4+a/WaPqe66/xW9/RTu/bZF9kmIiLatah2ARERMT8J8oiIxiXIIyIalyCPiGhcgjwionEJ8oiIxi2ucdGdd97Ze+yxR41LR0Q0a+XKlbfaXjL9fJUg32OPPVixYkWNS0dENEvSzTOdT9dKRETjEuQREY1LkEdENC5BHhHRuAR5RETjEuQREY1LkEdENC5BHhHRuCoTgiJq2ON1nx7ac9106jOG9lwR85UWeURE4xLkERGNS5BHRDQuQR4R0bgEeURE4xLkERGNS5BHRDQuQR4R0bh5B7mkh0q6WNIqSddJOmEYhUVExGCGMbPzPuCPbF8paTtgpaQLbX91CM8dEREbMO8Wue3v276y+/xOYBXwkPk+b0REDGaofeSS9gAeB3xpmM8bERHrN7Qgl/RLwEeBE23fMcPjx0taIWnF6tWrh3XZiIgFbyhBLmlzSoh/wPbHZvoa26fbXm57+ZIlS4Zx2YiIYDijVgScAayy/Y75lxQREXMxjBb5wcALgEMlXdV9/OYQnjciIgYw7+GHti8FNIRaImICZAOO9mRmZ0RE4xLkERGNS5BHRDQuQR4R0bgEeURE4xLkERGNS5BHRDQuQR4R0bgEeURE4xLkERGNS5BHRDQuQR4R0bgEeURE4xLkERGNS5BHRDQuQR4R0bgEeURE4xLkERGNS5BHRDQuQR4R0bgEeURE4xLkERGNS5BHRDQuQR4R0bgEeURE4xLkERGNS5BHRDQuQR4R0bgEeURE4xLkERGNS5BHRDQuQR4R0bgEeURE4xLkERGNS5BHRDQuQR4R0bjFtQuIiBjEHq/79FCe56ZTnzGU55kkaZFHRDQuQR4R0bihBLmkMyX9UNK1w3i+iIgY3LBa5P8EPH1IzxUREXMwlCC3fQlw+zCeKyIi5iZ95BERjRtbkEs6XtIKSStWr149rstGRGzyxhbktk+3vdz28iVLlozrshERm7x0rURENG5Yww/PBS4D9pF0i6SXDuN5IyJiw4YyRd/2McN4nn7Dmo4Lm+aU3IiInnStREQ0LkEeEdG4BHlEROMS5BERjUuQR0Q0LkEeEdG4BHlEROMS5BERjUuQR0Q0LkEeEdG4BHlEROMS5BERjRvKolkREQvRsBb3m+/CfmmRR0Q0LkEeEdG4BHlEROMS5BERjUuQR0Q0LkEeEdG4BHlEROMS5BERjUuQR0Q0LkEeEdG4BHlEROMS5BERjUuQR0Q0LkEeEdG4BHlEROMS5BERjUuQR0Q0LkEeEdG4BHlEROMS5BERjUuQR0Q0bnHtAloyrB2zYf67ZkdE9KRFHhHRuAR5RETj0rUSIzGsbqh0QUVsWFrkERGNG0qQS3q6pBskfUPS64bxnBERMZh5B7mkzYB3A4cDy4BjJC2b7/NGRMRghtEifyLwDds32r4X+CDw20N43oiIGMAwgvwhwHf6jm/pzkVExBjI9vyeQDoS+A3bv9sdvwB4ou1XTfu644HjAZYuXfqEm2++eV7XjSkZIdKuTDKLuZC00vby6eeH0SK/BXho3/FuwPemf5Ht020vt718yZIlQ7hsRETAcIL8v4G9JD1M0hbA0cAnh/C8ERExgHlPCLJ9n6Q/AD4DbAacafu6eVcWEREDGcrMTtv/Dvz7MJ4rIiLmJjM7IyIalyCPiGhcgjwionEJ8oiIxiXIIyIalyCPiGhcgjwionEJ8oiIxiXIIyIalyCPiGhcgjwionEJ8oiIxiXIIyIalyCPiGhcgjwionFDWY88IjZO9tmMYUiLPCKicQnyiIjGJcgjIhqXII+IaFyCPCKicQnyiIjGJcgjIhqXII+IaFyCPCKicQnyiIjGJcgjIhqXII+IaFyCPCKicQnyiIjGJcgjIhqXII+IaFyCPCKicQnyiIjGJcgjIhqXII+IaFyCPCKicQnyiIjGJcgjIho3ryCXdKSk6yT9QtLyYRUVERGDm2+L/FrgOcAlQ6glIiI2wuL5fLPtVQCShlNNRETMWfrIIyIat8EWuaTPAg+c4aHX2/7EoBeSdDxwPMDSpUsHLjAiIma3wSC3/dRhXMj26cDpAMuXL/cwnjMiItK1EhHRvPkOP3y2pFuAg4BPS/rMcMqKiIhBzXfUynnAeUOqJSIiNkK6ViIiGpcgj4hoXII8IqJxCfKIiMYlyCMiGpcgj4hoXII8IqJxCfKIiMYlyCMiGpcgj4hoXII8IqJxCfKIiMYlyCMiGpcgj4hoXII8IqJxCfKIiMYlyCMiGpcgj4hoXII8IqJxCfKIiMYlyCMiGpcgj4hoXII8IqJxCfKIiMYlyCMiGpcgj4hoXII8IqJxCfKIiMYlyCMiGpcgj4hoXII8IqJxCfKIiMYlyCMiGpcgj4hoXII8IqJxi2sXEPN306nPqF1CRFSUFnlEROMS5BERjUuQR0Q0bl5BLulvJF0v6SuSzpP0gGEVFhERg5lvi/xC4NG29wW+Bpw0/5IiImIu5hXkti+wfV93eDmw2/xLioiIuRhmH/lLgP8Y4vNFRMQANjiOXNJngQfO8NDrbX+i+5rXA/cBH5jleY4HjgdYunTpRhUbERHr2mCQ237qbI9LehHwW8BTbHuW5zkdOB1g+fLl6/26iIiYG82SvRv+ZunpwDuAX7O9eg7ftxq4eaMvvLadgVuH9FzDkpoGk5oGN4l1pabBDLOm3W0vmX5yvkH+DWBL4Lbu1OW2X77RT7hxNaywvXyc19yQ1DSY1DS4SawrNQ1mHDXNa60V278yrEIiImLjZGZnRETjNoUgP712ATNITYNJTYObxLpS02BGXtO8+sgjIqK+TaFFHhGxoCXIIyIalyCPiGhcgjyqkbSjpH1r1xHRuiZvdko6Ejjf9p2S3gA8HniL7Ssr1rQ7sJftz0raGlhs+85a9XQ17Q2cBuxq+9FdaD7T9lsq1vR54JmUOQxXAauBL9h+Ta2auro2A3alb26F7W9XqmXWn4Xtd4yrlum6/1N/DOzO2j+rQyvVsytwCvBg24dLWgYcZPuMGvX01bUN8EfAUtsvk7QXsI/tfxvF9Vptkf9ZF+KHAL8BnE0JrCokvQz4CPDe7tRuwMdr1dPnfZQ14n8OYPsrwNFVK4IdbN8BPAc4y/YTgFnX8xk1Sa8CfkBZX//T3cdI/uAGtN0GPmr6MHAl8AZKoPc+avkn4DPAg7vjrwEnVqtmylnAz4CDuuNbgJE1oOY1s7Oi+7t/nwGcZvsTkt5UsZ5XAk8EvgRg++uSdqlYT882tq+Q1H/uvvV98ZgslvQg4HnA6yvX0nMCpbV02wa/cgxs/0XtGmZxn+1qjaYZ7Gz7Q5JOArB9n6T7N/RNY7Cn7aMkHQNg+25N+0McplaD/LuS3ktpyf21pC2p++7iZ7bv7f2eJC0GJqHP6lZJe9LVIukI4Pt1S+IvKS2oS23/t6SHA1+vXNN3gJ9UrmENSf8w2+O2/3BctczgU5JeAZxHaXECYPv2SvXcJWknpv6PH8hk/C7v7bpYe3XtSd/Pa9ha7SPfBng6cE3X+n0Q8BjbF1Sq523Aj4EXAq8CXgF81XbVFmcXkqcDvwr8CPgWcKztYa08uUmQdAawD6VLpT+cqvRFS7oXuBb4EPA9YK2WnO2za9QFIOlbM5y27YePvRhA0uOBdwKPpvzMlgBHdN2I1Ug6jNL9tAy4ADgY+B3bnx/J9VoMcoCuf3wv22dJWgL8ku2Z/pONo5ZFwEuBp1H+6D4D/ONs67OPqaYjured2wKLat987ep6G6Wv8G7gfGA/4ETb/1yxpjfOdL5WF0fXwjwSOIrSFfavwEdt/6hGPZOuewe8D+Vv7wbbP69cErDm93ggpa7LbY9sed0mg7z7w1tO6dfcW9KDgQ/bPrhyaUj6ZWC32i2CrpZLbD+pdh39JF1l+7GSng08C3g1cLHt/SqXNpEkPQQ4BngN8Ke2z6lcz+bA7wO9/1efB95bKzwlPWeG0z+hvFv/4bjr6deNEtuDtUf3fGwU12q1j/zZwOMod8+x/T1J1e7mzzSkTlL1IXXAhZJeS2nR3dU7WbE/E2Dz7t/fBM61ffsI7wHNStLf2z5R0qeY4Z6G7WdWKGuNrtvgGOAwyn64K2vW0zmN8jt8T3f8gu7c71aq56WUkSEXd8e/TtkIfm9Jf1nrhU/SmcC+wHXAL7rTBhLkfe61bUm9GwnbVq5nB9t3SPpdypC6N0qq3iKnbIgNZVRNj4Eq/ZmdT0m6ntK18oquW+yeSrX0/sjfXun6M5L0F5TtE1cBHwROsl17tFHP/tPePX1O0tXVqikh+UjbP4A148pPAw4ALmHqdzxuB9peNq6LtRrkH+pGrTygG8P9EsqY6VomcUgdth9Wu4bpbL9O0l8Dd9i+X9JPgd+uVMvK7t8v1Lj+LP4MuJFy/2A/4JTuXYsoNxZrzoa9X9Ketr8Ja26o1xzut0cvxDs/BPbu3unV7Cu/TNIy218dx8WaDHLbb+/uCt9Bucnx57YvrFhSb0jdf03QkDokvXCm87bfP+5aeroRR68ElgLHUyZy7EOFCTiSrmGWYaIVA3PiXoD7/DFwsaQbKS8suwMvrljPf0r6N8pEJYDnApd079J/XK8szqaE+f9QRkKN9EW4yZudMRhJ7+w73Ap4CnCl7SMqlYSkf6X09b6wWzZga+Ay24+tUMvusz0+ScM0Je0M3FZzJFRfLVsyNUrketsjGx89QC2izBI+pDt1G/Ag269c/3eNXref8WuAa5jqIx/Z/6mmWuSSLrV9iKQ7Wbsl1Xu1275SXbtRxrIe3NV1KXCC7Vtq1NNj+1X9x5J2oF6fYc9YZ7zNZpKCul83qeVU4HbgzZTf2c7AIkkvtH1+hZoOtf25GUaJ7ClpZKMxNqS7V/ZNSp/48yhzJT5ao5Zpvm37k+O6WFNBbvuQ7t/a601MdxbwL5SxvwDHdecOq1bRzH4K7FW5hrHOeBvEtIbBFpRRGXfVahgA7wJOBnYAPgccbvtySY8AzqWMvx+3X+tq+b8zPDay0Rjr0y3edTRlVM9tlJFZsv3kcdYxi+sl/QvwKdaeZDaSn1OTXStdi+W63gQXSb8EPMr2lyrVc9X0roGZzo3btGF1iyizzD5k+3UVaxrrjLeNIelZwBNtn1zp+mv+70haZfuRfY992fbjatTVXf9h0yfezXRuDHX8AvhP4KW2v9Gdu7HWDNPpJJ01w2nbfskM5+etqRZ5n9MoS9f2/HSGc+N0q6TjKK0lmGol1NY/rO4+4OYJ6O65UNKVTM14O2GUM942hu2PS6r2YkdfnyplmGa/2i2vj7Lu39lHgCeMuY7nUlrkF0s6nzJMs86EhBnYHusN4FaDXP03fWz/opumW8tLKG+H/47yh/ZFpsZw17QCuLv7+ewNPF7SDyZgCvNWlLVfFgPLuj7WS2oVM63fdxFl1nDNwNxP0h2UYNq6+5zueKsaBXXdOo8Cdpj289q+Rk22zwPO60an9GYI7yrpNOC8Wusu9Yz7vlmrXSsfo0wN7i2n+QrgybafVa2oCSRpJfB/gB0ps91WAD+1fWzFmv6asobIWjPeas6inPY2+D7gJuB9tad4TxJJv00JzGcC/Tfx7gQ+aPuLVQrr0y2PcSRwlCttdNFXy4WU+2a9wQXHURasG8l9s1aDfBfgH4BDKa92F1EWXqryhyfpbMqr7Y+74x2Bvx1Vf9gc6rrS9uNVNk7Y2vbbJqCP9QZg35pD1mLjSTrI9mW165h0475v1uQOQbZ/aPto27vY3tX28yu3nvbthXhX348oa8HUJkkHAcdSlmiF+t1pNzK13spEkPQ2SdtL2lzSRZJ69zxiXS+X9IDegcq+q2fWLGhC3SrpOEmbdR/HMcL7ZrX/qDdKtz7Hy1h3ZbFaLeBFknbsArz3Fm8SfrYnUrZ6O8/2dd2M04s38D2j9lPgKkkXsfawrJqbJTzN9p+orMh4C+Xt+cVAtaV1J9g6jRZJk9BomTRjvW82CWGzMT5BGXr0Wequ89Dzt8AXJX2kOz4S+KuK9QBr1hD5AqxZn/zWyoEJpX91bBMlBjQxKzI2YFIbLRPFZePusd33afUXsI3tP61dRI/t90taQemzF/CccS2WM5tuQsLLKS92KykjDt5h+28qlnVtb7GqHkkzTTIZp0lakXHSTWSjZdKM+75Zqzc73wJ80fa/164FQNLSmc53r8rVaGoTh2Mp43z/FFhZc/W8bgz5i2xf0x0fQ7lRfUCtmro6dmRqRcZtgO1t/0/NmiaVpEcBT6Y0Wi6ahEbLpJlpUMEoBxq02iI/AThZ0s+An1N5rRXKjcTeK+LWlNXrbqCMu61pc5UdXZ4FvMv2z9Wt4V7REcBHuheXQyj7nD6tbkkAPBLYY9p8hGqrRE6465maB4CkpbUbLRNorF1QTQb5pK21Yvsx/ccqO7v8XqVy+r2XMib6asrSnrtTlv6txvaNko4GPk7Zvf5ptqfPXhwrSecAe1J2d+rdczEJ8nV0Q1nfCPyA8rMS5WdVc430SdTfBWXKgl6njOpiTXatwJq3wnvRN6us5uzA6XpjuGvXMZ2kxa6w24zWXft7F8reij+Dqmt/I2kVsMyt/jGMkcryrAfYnoQlKCaapGVM3TcbaRdUky1ylS3VTgB2o7SiDgQuo/zQatTTvzfnIspaFKtr1NJPZdurU4AH2z68+491EHBGhXJ+q8I1B3Ut8EDg+7ULacB3KC/AMQtJ59h+AfDVGc4NXZNBTgnx/YHLbT+5WwfiLyrW09/Vcx+lz3wS1kT+J8pyur3t575GWe5z7EHeW/t7hpUrt6OshFhzbfCdga9KuoK1x7ZX3Xx5Qt0IfF7Sp1n7Z/WOeiVNpLXuj0najBEuLNZqkN9j+x5JSNrS9vWS9qlVjO2aLyKz2dn2hySdBGD7Pkm1x91PX6XyrhnOjdubKl67Nd/uPrboPqJP97d2MlOLnfUmJNwLnD6q67Ya5Ld004Q/Dlwo6UfA98ZdhNZe73sdE9Ciu0vSTkxt4nAg9d8WT9rKlZO4+fLEmuBGy0Sw/VbgrZLeavukcV232ZudPZJ+jbKTyvm2761w7el6P1DVDohu9Mw7gUdT+oGXAEfY/krFmiZm5Uqtu2XgmoeoO5x1Ykm6mBl+ZrVXG5w0kp400/lRDchotUXe63PalbJHH5SbVeMey/oAYDfb7+5quoISlqZMvqmmm5K/FWWLrt5GuTdMwFrkL6esXPkGplauPL5GIZM2jLURr+37fCvKBg9jHwXVgD/u+3wr4ImU2dUjecFrskU+bSxr/5rWYx3CJum/gKNtf6c7voqyU/22wFm2nzLOemao7zLbB9WsITZ9kr5ge6Z3p9GR9FDgbbaPGcXzt9oiPwHYZwLGsm7RC/HOpV1Nt6nsXFLbBZKeC3ys9hhpSX/SrYf+TmZ+a157Ma8YQDdDsWcRZSTGAyuV05JbKF2cI9FqkE/KWNYd+w9s/0Hf4ZIx1zKT11DeHdwn6R7q9v2u6v5dUeHaMTwrKS/EonSpfAt4adWKJtC0Bssiyv4EV4/seo12rZxB6fetOpZV0geAz9t+37Tzvwf8+qjeRkXEZJP0+8BmlDD/CfAt2/81quu12iKflLGsrwY+Lun5wJXduScAW1IWqqpCZSu8k4FfAb4CnGq76horPSqbQL+WdTcFyaiHCSbpFNsnd58fZvvC2jVNom4o7SmUTSS+TXnn8lDgTElXjGqwQZMt8kkj6VCmZnJdZ/tzles5n/IW+BLK1PjtbP9OzZp6JF0N/D9KfWsmJ01fozwmS//aQZO6jtAkkPR3lJner+6bvbw98HbgbtsnjOS6LQb5eibi/ITS//pe2wt6UwBN2+R1kv7wJK20PbKpyjEaCfLBSPo6sPf0wQXdcOnrbe81iuu22rVyI+Vm4rnd8VGUoYh7A+8DRrIwTUPUrQ7Zmx68Wf+x7dsrFNQb7fApSa8AzmPt+xtjrynmZJducTj1fb5G1lpZwzONEOs2LBlZq7nVFvkltp800zlJ19muvaFDVZJuooyvn2njSdt++HgrAknfYmq0w3RVaorBSXrjbI9n6n4h6eOU4b7vn3b+OOB5o1q2o9UgXwX8Rm9Xkm6rtfNtLxvldkqx8SQdZPuy2nVEjJKkhwAfo+z/2huquT9l57Bn2/7uKK7batfKHwGXSvompYX3MMqmudsCZ1etbAJ0a6ysl+0rZ3t8RN5N3RUOYwi6UUenAbvafrSkfYFn2n5L5dImQhfUB/QNgBDwH7YvGuV1m2yRA0jaEngE5Qd1/UK/wdmvW9gIyhoPyykTEUTZjutLtg+pUFPeKW0CJH2Bso7Ie3u/T0nX2h7ZrMXYsCZb5Cq7nL8G2N32yyTtJWkf2/9Wu7ZJYPvJAJI+CBzvqR3rH83aix6N08MkfXJ9D07Akr8xmG1sXyGtdasji2ZV1mSQU3a9WUnZtgzKOgYfBhLka3tEL8QBbF8r6bGzfcMIraZsSBttu1XSnkytcX8E2SKvulaDfE/bR0k6BsD23ZrWRAgAVkn6R+CfKX94xzG15sm43Vl7ffYYildSdrp5hKTvUtZaOa5uSdFqkN8raWumWgV70jcmOdZ4MfD7lNUiocz0PG39Xz5SN1W6bgyR7RuBp3YDCxb1Zi9GXU3e7JR0GGVjgmXABcDBwO/Y/nzNuiaRpC0oC4yZydhYAkm/yrprrbx/vd8QE0PSrpS1RB5s+3BJy4CDbI99Q++Y0lyQd10ouwE/BQ6kjMa43PatVQubQJJ+nTIc8yamFu950ai2mxqwpnOAPYGrmFprxVmPvA2S/oNyj+r1tvfrFon6su3HVC5tQWsuyCHrdQxK0krg+bZv6I73Bs6t+bPrJnMtq73RRWwcSf9te//+4aTT1/aJ8VtUu4CNdLmk/WsX0YDNeyEOYPtrwOYV64GyCXR2lGnXXZJ2Yur+1IFMxiYvC1qrLfKvUvp9bwLuYmrnm7Hu2TnpJJ1J+YM7pzt1LLDY9osr1nQx8FjgCtZeNCvjyBvQzRp+J2Xbsmspi9cdYfsrVQtb4FoN8t1nOm/75nHXMsm62a+vBA6hvNhdArzHdrURPpJm3KQ3QxMnn6RFlPtSV1AaUmJCbqAvdE0FuaStgJdTdr65BjjDdmaVzWISR61EuyRdZvugDX9ljFNrfeRnU9YOuQY4nMwUnFU3auXrwLuA9wBfk/SkWb9pdLVc2v17p6Q7+j7ulDQR29DFQC6Q9NxMwJssrbXIr+kNc+qGPV2RnUrWbxJHrUTbJN0JbEtZX+Uepu5PbV+1sAWutRb5mm6BdKkMZOJGrUh66QznTq1RS8yd7e1sL7K9he3tu+OEeGWtTdHfr+9tuICtu+O0Cma2QtIZrD1qpfYmx0dIusf2BwAkvYey3G40YD1r3f8EuDmNq3qa6lqJuZnQUStbA58EzqTc57jd9om16om5kXQ5ZYOQ3qqaj6Gsd78T8HLbF9SqbSFLkMdY9G2+DLAd8AngUuDPIZsvt6Jb4/7Ntq/rjpdRNpp4M2WvyszwrCBBvgmSdA3dzLuZ1Jg4NW3z5f5/ezVl8+UGzDQdv3cuU/Xraa2PPAbzW7ULmMFRwHdsfx9A0ouA51Jm576pXlkxRzdIOg34YHd8FGVY65b0DUaI8UqLfIGQtDNwW63FqiRdCTzV9u3dWPYPAq+iTNd/pO0jatQVc9Pd43gFU/ddLqXMUbiHsg3c/1Ysb8FKkG+CuoWMTgVup/RdngPsTBlu+kLb51eo6Wrb+3WfvxtYbftN3XHekkfMQ7pWNk3vAk4GdgA+Bxxu+3JJjwDOBcYe5MBmkhZ3Q9SeAhzf91j+H044SR+y/bz13X/JgnV15Q9o07S4NwxM0l/avhzA9vUVZ1afC3xB0q3A3cB/dvX9ClkGtQW97QIn8f7Lgpcg3zT9ou/zu6c9VqUvzfZfSboIeBBwQV9f/SJKX3lMsN5N6qwwOpnSR74JknQ/U+u0b03ZFo/ueCvbtTeXiMZ0a6zMNqQ1s6orSot8E2R7s9o1xKbF9nZQuuqA/6HcQBdl2YftKpYWpEUeEXMg6Uu2D9jQuRiv1lY/jIi67pd0rKTNJC2SdCxwf+2iFroEeUTMxfOB5wE/6D6O7M5FRelaiYhoXFrkETEwSXtLukjStd3xvpLeULuuhS5BHhFz8T7gJLoFsmx/BTi6akWRII+IOdnG9hXTzmVnoMoS5BExF7dK2pNucpCkI4Dv1y0pcrMzIgYm6eHA6cCvAj8CvgUcm6n7dSXII2LOJG0LLLJ9Z+1aIl0rETEASQdIulrS/0q6DFiaEJ8cCfKIGMS7gdcCOwHvAP6+bjnRL0EeEYNYZPtC2z+z/WFgSe2CYkpWP4yIQTxA0nPWd2z7YxVqik5udkbEBkk6a5aHbfslYysm1pEgj4hoXPrII2Jgkk6QtL2Kf5R0paSn1a5roUuQR8RcvMT2HcDTgF2AFwOn1i0pEuQRMRfq/v1N4CzbV/edi0oS5BExFyslXUAJ8s9I2g74ReWaFrzc7IyIgUlaBDwWuNH2jyXtBDykW842KkmLPCLmwsAy4A+7422BreqVE5AWeUTMgaTTKF0ph9p+pKQdgQts71+5tAUtMzsjYi4OsP14SV8GsP0jSVvULmqhS9dKRMzFzyVtxtTGEkvIzc7qEuQRMRf/AJwH7CLpr4BLgbfWLSnSRx4RcyLpEcBTKOPHL7K9qnJJC16CPCIGJukc2y/Y0LkYr3StRMRcPKr/oOsvf0KlWqKTII+IDZJ0kqQ7gX0l3SHpzu74h8AnKpe34KVrJSIGJumttk+qXUesLUEeEQPrpug/H3iY7TdLeijwINtXVC5tQUuQR8TAMrNzMti0MgMAAAHuSURBVGVmZ0TMRWZ2TqDc7IyIucjMzgmUII+IuejN7Ny1b2bnKXVLivSRR8Sc9M3sBPhcZnbWlz7yiJirbYBe98rWlWsJ0rUSEXMg6c+Bs4FfBnYGzpL0hrpVRbpWImJgklYBj7N9T3e8NXCl7UfWrWxhS4s8IubiJtbe2m1L4Jt1Some9JFHxAZJeielT/xnwHWSLuyOD6OMXImK0rUSERsk6UWzPW777HHVEutKkEdENC5dKxExMEl7UbZ2W0ZfX7nth1crKnKzMyLm5CzgNOA+4MnA+4FzqlYUCfKImJOtbV9E6Za92fabgEMr17TgpWslIubinm5N8q9L+gPgu8AulWta8HKzMyIGJml/YBXwAODNwA7A22xfXrWwBS5BHhHRuHStRMQGSfp72ydK+hTdWuT9bD+zQlnRSZBHxCB6I1PeXrWKmFG6ViJiTrpdgbC9unYtUWT4YURskIo3SboVuB74mqTV3bK2UVmCPCIGcSJwMLC/7Z1s7wgcABws6dV1S4t0rUTEBkn6MnCY7VunnV8CXGD7cXUqC0iLPCIGs/n0EIc1/eSbV6gn+iTII2IQ927kYzEG6VqJiA2SdD9w10wPAVvZTqu8ogR5RETj0rUSEdG4BHlEROMS5BERjUuQR0Q0LkEeEdG4/w80WN6klQMbuwAAAABJRU5ErkJggg==\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -930,7 +930,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -944,7 +944,7 @@
     },
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 432x288 with 9 Axes>"
       ]
@@ -974,7 +974,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -983,13 +983,13 @@
        "<function matplotlib.pyplot.show(*args, **kw)>"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 432x288 with 9 Axes>"
       ]
@@ -1021,12 +1021,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 432x288 with 9 Axes>"
       ]
@@ -1064,7 +1064,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -1075,7 +1075,7 @@
        "      dtype='object')"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1086,7 +1086,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
@@ -1133,22 +1133,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<seaborn.axisgrid.PairGrid at 0x119dd43c8>"
+       "<seaborn.axisgrid.PairGrid at 0x123d20b50>"
       ]
      },
-     "execution_count": 18,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 1620x1620 with 90 Axes>"
       ]
@@ -1224,7 +1224,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[  6.   , 148.   ,  72.   , ...,   0.627,  50.   ,   1.   ],\n",
+       "       [  1.   ,  85.   ,  66.   , ...,   0.351,  31.   ,   0.   ],\n",
+       "       [  8.   , 183.   ,  64.   , ...,   0.672,  32.   ,   1.   ],\n",
+       "       ...,\n",
+       "       [  5.   , 121.   ,  72.   , ...,   0.245,  30.   ,   0.   ],\n",
+       "       [  1.   , 126.   ,  60.   , ...,   0.349,  47.   ,   1.   ],\n",
+       "       [  1.   ,  93.   ,  70.   , ...,   0.315,  23.   ,   0.   ]])"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
@@ -1267,7 +1293,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
@@ -1308,7 +1334,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
@@ -1354,7 +1380,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [
     {
@@ -1428,7 +1454,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [
     {
@@ -1477,7 +1503,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [
     {
@@ -1520,7 +1546,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [
     {
@@ -1565,14 +1591,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[0.107 0.262 0.1   0.078 0.068 0.133 0.12  0.132]\n"
+      "[0.1   0.232 0.1   0.073 0.076 0.148 0.111 0.162]\n"
      ]
     }
    ],
@@ -1661,7 +1687,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [
     {
@@ -1722,7 +1748,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [
     {
@@ -1766,7 +1792,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [
     {
@@ -1808,7 +1834,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [
     {
@@ -1948,7 +1974,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [
     {
@@ -1989,14 +2015,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Logloss: (-0.4925542125228744, 0.04700518583644249)\n"
+      "Logloss: (0.4925542125228744, 0.04700518583644249)\n"
      ]
     }
    ],
@@ -2030,7 +2056,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [
     {
@@ -2076,7 +2102,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [
     {
@@ -2128,7 +2154,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [
     {
@@ -2193,14 +2219,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "MAE: (-4.004946635323998, 2.0835992687095275)\n"
+      "MAE: (-4.004946635323989, 2.0835992687095346)\n"
      ]
     }
    ],
@@ -2236,14 +2262,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 41,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "MSE: (-34.705255944524865, 45.57399920030862)\n"
+      "MSE: (-34.70525594452485, 45.57399920030876)\n"
      ]
     }
    ],
@@ -2284,14 +2310,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 42,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "R^2: (0.20252899006055886, 0.5952960169512295)\n"
+      "R^2: (0.20252899006055952, 0.5952960169512396)\n"
      ]
     }
    ],
@@ -2392,7 +2418,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [
     {
@@ -2432,7 +2458,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [
     {
@@ -2486,7 +2512,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 45,
    "metadata": {},
    "outputs": [
     {
@@ -2532,7 +2558,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 46,
    "metadata": {},
    "outputs": [
     {
@@ -2574,14 +2600,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 47,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0.6900205058099795\n"
+      "0.7003930280246069\n"
      ]
     }
    ],
@@ -2618,7 +2644,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 48,
    "metadata": {},
    "outputs": [
     {
@@ -2681,14 +2707,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 49,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "-34.705255944524865\n"
+      "-34.70525594452485\n"
      ]
     }
    ],
@@ -2728,14 +2754,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 50,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "-34.078246209259305\n"
+      "-34.078246209259284\n"
      ]
     }
    ],
@@ -2792,7 +2818,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 51,
    "metadata": {},
    "outputs": [
     {
@@ -2889,7 +2915,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 52,
    "metadata": {
     "scrolled": false
    },
@@ -2901,14 +2927,14 @@
       "('LR', 0.7695146958304853, 0.04841051924567195)\n",
       "('LDA', 0.773462064251538, 0.05159180390446138)\n",
       "('KNN', 0.7265550239234451, 0.06182131406705549)\n",
-      "('CART', 0.6821941216678058, 0.0587306826895643)\n",
+      "('CART', 0.6926179084073821, 0.07436972431355568)\n",
       "('NB', 0.7551777170198223, 0.04276593954064409)\n",
       "('SVM', 0.6510252904989747, 0.07214083485055327)\n"
      ]
     },
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -3050,7 +3076,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 53,
    "metadata": {},
    "outputs": [
     {
@@ -3118,7 +3144,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 54,
    "metadata": {},
    "outputs": [
     {
@@ -3230,7 +3256,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 55,
    "metadata": {},
    "outputs": [
     {
@@ -3298,14 +3324,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 56,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0.7681647300068353\n"
+      "0.7694292549555708\n"
      ]
     }
    ],
@@ -3356,14 +3382,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 57,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0.7642686261107314\n"
+      "0.766848940533151\n"
      ]
     }
    ],
@@ -3436,7 +3462,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 58,
    "metadata": {},
    "outputs": [
     {
@@ -3494,7 +3520,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 59,
    "metadata": {},
    "outputs": [
     {
@@ -3536,7 +3562,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 62,
    "metadata": {},
    "outputs": [
     {
@@ -3596,17 +3622,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0.7642515379357484\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Voting Ensemble for Classification\n",
     "from pandas import read_csv\n",
@@ -3671,17 +3689,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0.7559055118110236\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Save Model Using Pickle\n",
     "from pandas import read_csv\n",
@@ -3734,25 +3744,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0.7559055118110236\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/anaconda3/lib/python3.6/site-packages/sklearn/externals/joblib/__init__.py:15: DeprecationWarning: sklearn.externals.joblib is deprecated in 0.21 and will be removed in 0.23. Please import this functionality directly from joblib, which can be installed with: pip install joblib. If this warning is raised when loading pickled models, you may need to re-serialize those models with scikit-learn 0.21+.\n",
-      "  warnings.warn(msg, category=DeprecationWarning)\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Save Model Using joblib\n",
     "from pandas import read_csv\n",
@@ -3806,7 +3800,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [