Linear Regression using boston data.py

#Import Libraries
from sklearn.datasets import load_boston
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_absolute_error 
from sklearn.metrics import mean_squared_error 
from sklearn.metrics import median_absolute_error
#----------------------------------------------------

#load boston data

BostonData = load_boston()

#X Data
X = BostonData.data

#y Data
y = BostonData.target

#----------------------------------------------------
#Splitting data

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=44, shuffle =True)

#----------------------------------------------------
#Applying Linear Regression Model 

LinearRegressionModel = LinearRegression(fit_intercept=True, normalize=True,copy_X=True,n_jobs=-1)
LinearRegressionModel.fit(X_train, y_train)

#Calculating Details
print('Linear Regression Train Score is : ' , LinearRegressionModel.score(X_train, y_train))
print('Linear Regression Test Score is : ' , LinearRegressionModel.score(X_test, y_test))
print('Linear Regression Coef is : ' , LinearRegressionModel.coef_)
print('Linear Regression intercept is : ' , LinearRegressionModel.intercept_)
print('----------------------------------------------------')

#Calculating Prediction
y_pred = LinearRegressionModel.predict(X_test)
print('Predicted Value for Linear Regression is : ' , y_pred[:10])

#----------------------------------------------------
#Calculating Mean Absolute Error
MAEValue = mean_absolute_error(y_test, y_pred, multioutput='uniform_average') # it can be raw_values
print('Mean Absolute Error Value is : ', MAEValue)

#----------------------------------------------------
#Calculating Mean Squared Error
MSEValue = mean_squared_error(y_test, y_pred, multioutput='uniform_average') # it can be raw_values
print('Mean Squared Error Value is : ', MSEValue)

#----------------------------------------------------
#Calculating Median Squared Error
MdSEValue = median_absolute_error(y_test, y_pred)
print('Median Squared Error Value is : ', MdSEValue )