Unverified50% confidenceFactExact time
AUC measures the probability that a model ranks a same-person pair ahead of a different-person pair among all same-person/different-person comparison pairs, takes values from 0 to 1, is better the closer to 1, and is independent of a specific threshold.
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50%
Confidence
Long-term
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10/20/2026
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VerifiedThe value of AUC ranges from 0 to 1, and a higher value indicates stronger classification ability of the model.78% similarVerifiedAUC equals the probability that, when one positive sample and one negative sample are randomly drawn from all positive and negative samples respectively, the predicted score of the positive sample is higher than that of the negative sample.74% similarVerifiedAUC值域为0.5到1.0，0.5代表随机猜测、1.0代表完美预测，不受样本类别不平衡影响73% similarUnverifiedAUC的概率意义是随机抽取一个正例和一个负例，模型对正例打分高于负例的概率，该特性使其对类别不平衡不敏感73% similarUnverifiedCalibration means that when the model outputs 0.9, across a large number of similar samples about 90% are indeed the correct class; an uncalibrated model can have high AUC but its values cannot be used directly as probabilities.72% similar
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