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# create an object of the LinearRegression Model | |
model_LR = LinearRegression() | |
# fit the model with the training data | |
model_LR.fit(train_x, train_y) | |
# predict the target on train and test data | |
predict_train = model_LR.predict(train_x) | |
predict_test = model_LR.predict(test_x) | |
# Root Mean Squared Error on train and test date | |
print('RMSE on train data: ', mean_squared_error(train_y, predict_train)**(0.5)) | |
print('RMSE on test data: ', mean_squared_error(test_y, predict_test)**(0.5)) |
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