I am using GridSearchCV to tune hyperparameters of regression decision tree. When I do, I get mean_test_score but I thought it would return mean MSE since it is a regressor. how to interpret mean_test_score? Is there a way to tweak GridSearchCV so it returns mean MSE?
here is my code
tree_reg = GridSearchCV(DecisionTreeRegressor(criterion="mse"), {
"min_samples_split":[2,3,4],
"min_samples_leaf":[1,2,3]
}, cv=5, return_train_score=False)
tree_reg.fit(X, y)
pd.DataFrame(tree_reg.cv_results_)
>>> params split0_test_score .... mean_test_score
{"min_samples_leaf":2, 0.998782 0.9989933
"min_samples_split":3}
{"min_samples_leaf":2, 0.998823 0.998930
"min_samples_split":4}
...
what does mean_test_score mean?