Unverified50% confidenceFactExact time
Theoretical analysis shows that UtilityAUC can distinguish between models that perform similarly on standard accuracy and AURC.
1
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50%
Confidence
Long-term
Relevance
10/20/2026
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UnverifiedCommon evaluation metrics for classification models include accuracy, precision, recall, F1 score, and the ROC-AUC curve71% similarUnverified校准性（Calibration）指模型表达的置信度与实际准确率之间的一致程度，是评估AI模型质量的核心指标之一71% similarUnverifiedAUROC是通过绘制不同阈值下真正率与假正率的关系曲线并计算曲线下面积来评估分类模型区分能力的指标71% similarUnverifiedUtilityAUC can capture how well a model aligns with utility preferences, not merely error frequency.68% similarUnverifiedIn this experiment, logistic regression achieved the best result with an AUC of 0.89.68% similar
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