Scikitlearn GridSearchCV best model scores

user_17122083 0
Viewed 79

I am trying to print the training and test score of the best model from my GridSearchCV object. My initial guess was to use cv_results['best_train_score'] and cv_results['best_test_score'] but after looking at the documentation I dont think there is a 'best_train_score' for cv_results.

I also see that there is a best_estimator_ but I'm not sure if I can use this to print a test and a training score. Any help is greatly appreciated.

scikit-learn machine-learning python
1 Answers

You can use the best_estimator_ of your fitted GridSearchCV to retrieve the best model and then use the score function of your estimator to calculate the train and test accuracy.

As follows:

from sklearn import svm, datasets
from sklearn.model_selection import GridSearchCV, train_test_split

iris = datasets.load_iris()
X_train, X_test, y_train, y_test = train_test_split(
    iris.data, iris.target, test_size=0.2
)

parameters = {"kernel": ("linear", "rbf"), "C": [1, 10]}
svc = svm.SVC()
cv = GridSearchCV(svc, parameters)
cv.fit(iris.data, iris.target)
model = cv.best_estimator_

print(f"train score: {model.score(X_train, y_train)}")
print(f"test score: {model.score(X_test, y_test)}")

Output:

train score: 0.9916666666666667
test score: 1.0
user_45746330
Related