Step 6: Train the model
Now we are ready to train the model. we use ‘LinearRegression().fit()’ to train it. and this model object has a
score() function to return the score of the model, which is the coefficient of determination R^2 of the prediction. For now you only need to know the higher the better.
# prepare training data x_train = train_data[features] y_train = train_data[target] # Applying Linear regression # fit() is the method to train the model model = LinearRegression().fit(x_train,y_train) # Model's score print("Score: " + str(model.score(x_train,y_train)))