Linear regression model.py

#import linear regression 
from sklearn.linear_model import LinearRegression 

#fit on training data 
lr=LinearRegression() 
lr.fit(X_train,y_train) 

#accuracy 
print('Training accuracy =',lr.score(X_train,y_train)) 
print('Testing accuracy =',lr.score(X_test,y_test)) 

#RMSE score 
pred = lr.predict(X_test) 
rmse = np.sqrt(mean_squared_error(y_test,pred)) 
print('RMSE =',rmse)