balanced_accuracy_score函数是 scikit-learn 库中的一个实现,它可以计算平衡准确率,从而避免在标签不平衡的数据集上过高估计性能。当参数 adjusted 设置为 False 时,平衡准确率的最佳值为 1,最差值为 0。下面是一个常用的计算示例: 代码语言:javascript 复制 from sklearn.metricsimportbalanced_accuracy_score y_t...
本文简要介绍python语言中 sklearn.metrics.balanced_accuracy_score 的用法。 用法: sklearn.metrics.balanced_accuracy_score(y_true, y_pred, *, sample_weight=None, adjusted=False) 计算平衡精度。 处理不平衡数据集的二元和多类分类问题的平衡精度。它被定义为在每个类上获得的平均召回率。 adjusted=False ...
Sklearn have classes incolumnsas we can see in the code for the same example: confusion_matrix(y_true,y_pred)# array([[40, 12],# [18, 30]]) If we change the code in thebalanced_accuracy_scorefunction, found atsklearn/metrics/_classification.py # as isper_class=np.diag(C)/C.su...
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Our performance measure precision should not be as affected by this like accuracy would, however we still need to address it. There are three ways to deal with the imbalance. Get more data (ideal, but not an option) Use a model that naturally deals with the imbalance Resample our training...
class_acc = metrics.balanced_accuracy_score(test_true, test_pred)returnoverall_acc, class_acc, opt 开发者ID:lightaime,项目名称:deep_gcns_torch,代码行数:25,代码来源:main.py 示例2: test_sklearn_custom_scoring_and_cv ▲点赞 6▼ # 需要导入模块: from sklearn import metrics [as 别名]# 或...
本文简要介绍python语言中 sklearn.metrics.balanced_accuracy_score 的用法。 用法: sklearn.metrics.balanced_accuracy_score(y_true, y_pred, *, sample_weight=None, adjusted=False) 计算平衡精度。 处理不平衡数据集的二元和多类分类问题的平衡精度。它被定义为在每个类上获得的平均召回率。 adjusted=False ...