AttributeError: 'SVC' object has no attribute 'best_estimator_'
AttributeError: 'SVC' object has no attribute 'best_estimator_'
我正在尝试将 GridSearchCV 用于 SVM 线性,但出现此错误:
AttributeError: 'SVC' object has no attribute 'best_estimator_'
线性SVM的代码:
classifier = SVC()
classifier = GridSearchCV(classifier, {'C':[0.001, 0.01, 0.1, 1, 10,0.1, 100, 1000]}, cv=3, n_jobs=4)
classifier = SVC(kernel='linear')
classifier.fit(train_vectors, train_labels)
classifier = classifier.best_estimator_
有人可以帮忙吗?
这样做:
classifier = SVC(kernel='linear')
gridsearch = GridSearchCV(classifier, {'C':[0.001, 0.01, 0.1, 1, 10,0.1, 100, 1000]}, cv=3, n_jobs=4)
gridsearch.fit(train_vectors, train_labels)
best_params = gridsearch.best_params_
classifier = gridsearch.best_estimator_
我正在尝试将 GridSearchCV 用于 SVM 线性,但出现此错误:
AttributeError: 'SVC' object has no attribute 'best_estimator_'
线性SVM的代码:
classifier = SVC()
classifier = GridSearchCV(classifier, {'C':[0.001, 0.01, 0.1, 1, 10,0.1, 100, 1000]}, cv=3, n_jobs=4)
classifier = SVC(kernel='linear')
classifier.fit(train_vectors, train_labels)
classifier = classifier.best_estimator_
有人可以帮忙吗?
这样做:
classifier = SVC(kernel='linear')
gridsearch = GridSearchCV(classifier, {'C':[0.001, 0.01, 0.1, 1, 10,0.1, 100, 1000]}, cv=3, n_jobs=4)
gridsearch.fit(train_vectors, train_labels)
best_params = gridsearch.best_params_
classifier = gridsearch.best_estimator_