Update branch

README.md

@@ -1,3 +1,4 @@
+
 #  ML Module that makes learning process smooth
 
 ### Project Overview

mlhybridx/check.py → mlhybridx/EasyReg.py

@@ -1,7 +1,7 @@
 
 import sys
 import pandas as pd 
-from .hub import check_file,ols,multiple,GDR,SE,split_data,train_data,predict_gdr,predict_olr,perdict_multiple, By_default
+from .hub import check_file,ols,multiple,GDR,SE,split_data,train_data,predict_gdr,predict_olr,perdict_multiple, By_default, visuals
 import time
 
 class EasyRegressor:
@@ -89,7 +89,7 @@ def model_gdr(self, lr=0.0001, epochs=50):
     def predict(self, model, val=None):  
       self.df()
       x, y  = split_data(self.data, self.target)
-      x_train, x_test, y_train, y_test = train_data(x, y, self.test_size)
+      x_train, x_test, y_train, self.y_test = train_data(x, y, self.test_size)
       m,b =  ols(x_train, y_train)   
       try:
         if model == 'ols':
@@ -98,8 +98,8 @@ def predict(self, model, val=None):
                  pred = predict_olr(float(val),m,b)
                  output = f"Predicted Values = {pred}"
                  return self.typer(output)
-            pred = predict_olr(x_test, m, b)
-            output = f"Predicted values = {pred}"
+            self.pred = predict_olr(x_test, m, b)
+            output = f"Predicted values = {self.pred}"
             return self.typer(output)
 
         if model == 'mlr':
@@ -108,8 +108,8 @@ def predict(self, model, val=None):
                  pred = perdict_multiple(float(val),m,b)
                  output = f"Predicted Values = {pred}"
                  return self.typer(output)
-            pred = predict_olr(x_test, m, b)
-            output = f"Predicted values = {pred}"
+            self.pred = predict_olr(x_test, m, b)
+            output = f"Predicted values = {self.pred}"
             return self.typer(output)
 
         if model == 'gdr':
@@ -118,8 +118,8 @@ def predict(self, model, val=None):
                  pred = predict_gdr(x_test, m, b)
                  output = f"Predicted values = {pred}"
                  return self.typer(output)
-            pred = predict_gdr(x_test, m, b)
-            output = f"Predicted values = {pred}"
+            self.pred = predict_gdr(x_test, m, b)
+            output = f"Predicted values = {self.pred}"
             return self.typer(output)
       except ValueError:
           print("Inalid params")  
@@ -144,3 +144,7 @@ def score(self, score, model):
             m,b = GDR(x_train,y_train,lr=0.01,epochs= 50) 
             y_pred = predict_gdr(x_test,m,b)
             return SE(y_test, y_pred, score) 
+
+
+def plot(self, y_pred, y_actual, plot_type:str):
+    return visuals(y_pred, y_actual, plot_type)

mlhybridx/Visualization.py

@@ -0,0 +1,36 @@
+import pandas as pd
+import matplotlib.pyplot as plt
+import seaborn as sns
+
+
+def visuals(self, y_pred, y_actual, plot_type:str, title:str, xlabel: str, ylabel:str):
+
+    title = f'{plot_type} Chart' 
+    xlabel = f'{xlabel}'
+    ylabel = f'{ylabel}'
+    if plot_type == 'plot':
+        sns.lineplot(x=y_actual, y=y_pred, color='blue', label='Line 1')
+        sns.lineplot(x=y_actual, y=y_pred, color='red', label='Line 2')
+        plt.legend()     
+        plt.title(title)
+        plt.xlabel(xlabel)
+        plt.ylabel(ylabel)
+
+        plt.show()
+
+
+    if plot_type == 'scatter':
+        sns.scatterplot(x=y_actual, y=y_pred, color='blue', label='Line 1')
+        sns.lineplot(x=y_actual, y=y_pred, color='red', label='Line 2')
+        plt.legend()     
+        plt.title(title)
+        plt.xlabel(xlabel)
+        plt.ylabel(ylabel)
+
+        plt.show()
+
+
+def main():
+    visuals([1,2,3,4,5],[2,5,8,8,5],'plot')
+
+main()

mlhybridx/__init__.py

@@ -1 +1 @@
-from .check import EasyRegressor
+from .EasyReg import EasyRegressor

mlhybridx/default.py

@@ -5,6 +5,7 @@
 from .split import split_data
 from .predict import predict_olr, perdict_multiple, predict_gdr
 from .train import train_data
+from .Visualization import visuals
 
 def datasets():
         flight = sns.load_dataset('flights').replace({'Jan': 1, 'Feb':2,'Mar':3,'Apr':4,'May':5,'Jun':6,'Jul':7,'Aug':8,'Sep':9,'Oct':10,'Nov':11,'Dec':12}) 
@@ -45,7 +46,9 @@ def By_default():
         m,b = ols( x_train,  y_train)
         print(f"m = {m}\nb = {b} ")
         pred = predict_olr(x_test,m,b)
-        print(f" Predicted value = {pred}")
+        print(f" Predicted Value = {pred}")
+
+        visuals(pred, y_test,'plot')
 
         print("\n\n\n//////////////////////////////////////////// ●▬▬▬▬◤ By Multiple Regression ◢▬▬▬▬● ///////////////////////////////////////\n")
         x_train,  x_test,  y_train,  y_test = train_data( x,  y , size)
@@ -55,7 +58,7 @@ def By_default():
         print(f" Predicted value = {pred}")
 
 
-        print("\n\n\n///////////////////////////////////// ●▬▬▬▬◤ By Gradient Descent Regression ◢▬▬▬▬● //////////////////////////////////////\n")
+        print("\n\n\n//////////////////////////////// ●▬▬▬▬◤ By Gradient Descent Regression ◢▬▬▬▬● //////////////////////////////////////\n")
         print("\n\n\n For lr = 0.001 and epochs = 50\n\n")
         x_train,  x_test,  y_train,  y_test = train_data( x,  y , size)
         intercept_, coef_= GDR(x_train, y_train, lr=0.001, epochs=50)
@@ -67,6 +70,8 @@ def By_default():
 
 
 
+
+
 
 
 

mlhybridx/hub.py

@@ -4,4 +4,5 @@
 from .split import split_data
 from .predict import predict_olr, perdict_multiple, predict_gdr 
 from .train import train_data 
-from .default import By_default
+from .default import By_default
+from .Visualization import visuals