深圳哪家网站建设服务好,安徽智能网站建设制作,网站建设个人主要事迹,洛阳网络科技有限公司排名GridSearchCV使用“评分”来选择最佳估算器.训练GridSearchCV后,我希望看到每个组合的得分. GridSearchCV是否存储每个参数组合的所有分数#xff1f;如果它如何获得分数#xff1f;谢谢.这是我在另一篇文章中使用的示例代码.from sklearn.feature_extraction.text import Co…GridSearchCV使用“评分”来选择最佳估算器.训练GridSearchCV后,我希望看到每个组合的得分. GridSearchCV是否存储每个参数组合的所有分数如果它如何获得分数谢谢.这是我在另一篇文章中使用的示例代码.from sklearn.feature_extraction.text import CountVectorizerfrom sklearn.feature_extraction.text import TfidfTransformerfrom sklearn.grid_search import GridSearchCVfrom sklearn.pipeline import Pipelinefrom sklearn.naive_bayes import MultinomialNBX_train [qwe rtyuiop, asd fghj kl, zx cv bnm, qw erty ui op, as df ghj kl, zxc vb nm, qwe rt yu iop, asdfg hj kl, zx cvb nm,qwe rt yui op, asd fghj kl, zx cvb nm, qwer tyui op, asd fg hjk l, zx cv b nm, qw ert yu iop, as df gh jkl, zx cvb nm,qwe rty uiop, asd fghj kl, zx cvbnm, qw erty ui op, as df ghj kl, zxc vb nm, qwe rtyu iop, as dfg hj kl, zx cvb nm,qwe rt yui op, asd fg hj kl, zx cvb nm, qwer tyuiop, asd fghjk l, zx cv b nm, qw ert yu iop, as df gh jkl, zx cvb nm]y_train [1, 2, 3, 1, 1, 3, 1, 2, 3,1, 2, 3, 1, 4, 1, 2, 2, 4,1, 2, 3, 1, 1, 3, 1, 2, 3,1, 2, 3, 1, 4, 1, 2, 2, 4]parameters {clf__alpha: (1e-1, 1e-2),vect__ngram_range: [(1,2),(1,3)],vect__max_df: (0.9, 0.98)}text_clf_Pipline_MultinomialNB Pipeline([(vect, CountVectorizer()),(tfidf, TfidfTransformer()),(clf, MultinomialNB()),])gs_clf GridSearchCV(text_clf_Pipline_MultinomialNB, parameters, n_jobs-1)gs_classifier gs_clf.fit(X_train, y_train)
