Machine Learning, Linear Regression, Data Science, Artificial Intelligence.
grid.fit(X_train, y_train) best_model = grid.best_estimator_ best_params = grid.best_params_ # Prediction predictions = best_model.predict(X_test) # Test error mse = mean_squared_error(y_test, predictions) return best_params, mse Testing the trained models Finally, after the model is fitted with