ValueError:"balanced_accuracy"在scikit-learn中不是有效的评分值 [英] ValueError: 'balanced_accuracy' is not a valid scoring value in scikit-learn

问题描述

我尝试将balanced_accuracy的其他评分指标传递给GridSearchCV进行二进制分类(而不是默认的accuracy)

I tried to pass to GridSearchCV other scoring metrics like balanced_accuracy for Binary Classification (instead of the default accuracy)

  scoring = ['balanced_accuracy','recall','roc_auc','f1','precision']
  validator = GridSearchCV(estimator=clf, param_grid=param_grid, scoring=scoring, refit=refit_scorer, cv=cv)

并收到此错误

ValueError:"balanced_accuracy"不是有效的评分值.有效的 选项是 ['accuracy'，'adjusted_mutual_info_score'，'adjusted_rand_score'，'average_precision'，'completeness_score'，'explained_variance'，'f1'，'f1_macro'，'f1_micro'，'f1_samples'，'f1_coreed'，' homogeneity_score'，'mutual_info_score'，'neg_log_loss'，'neg_mean_absolute_error'，'neg_mean_squared_error'，'neg_mean_squared_log_error'，'neg_median_absolute_error'，'normalized_mutual_ision_ision'prec''pre' ，'r2'，'recall'，'recall_macro'，'recall_micro'，'recall_samples'，'recall_weighted'，'roc_auc'，'v_measure_score']

ValueError: 'balanced_accuracy' is not a valid scoring value. Valid options are ['accuracy','adjusted_mutual_info_score','adjusted_rand_score','average_precision','completeness_score','explained_variance','f1','f1_macro','f1_micro','f1_samples','f1_weighted','fowlkes_mallows_score','homogeneity_score','mutual_info_score','neg_log_loss','neg_mean_absolute_error','neg_mean_squared_error','neg_mean_squared_log_error','neg_median_absolute_error','normalized_mutual_info_score','precision','precision_macro','precision_micro','precision_samples','precision_weighted','r2','recall','recall_macro','recall_micro','recall_samples','recall_weighted','roc_auc','v_measure_score']

这很奇怪，因为应使用'balanced_accuracy'有效 如果不定义balanced_accuracy，则代码可以正常工作

This is strange because 'balanced_accuracy' should be valid Without defining balanced_accuracy then the code works fine

    scoring = ['recall','roc_auc','f1','precision']

此外，上述错误中的得分指标似乎与

Also the scoring metrics in the error above seems to be different from the ones in the document

任何想法为何?非常感谢

Any ideas why? Thank you so much

scikit-learn版本为0.19.2

scikit-learn version is 0.19.2

推荐答案

如果要使用balanced_accuracy，请将sklearn更新到最新版本.从 0.19文档中可以看到balanced_accuracy不是有效的评分指标.在中添加了0.20 .

Update your sklearn to the latest version if you want to use balanced_accuracy. As you can see from the 0.19 documentation balanced_accuracy is not a valid scoring metric. It was added in 0.20.

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