AUC-PR (Area Under the Precision-Recall Curve)

Measures classifier performance specifically on the positive class. More informative than AUC-ROC when positive examples are rare. A model with 99.9% AUC-ROC on 0.1% fraud data may still have terrible AUC-PR - it might correctly classify all negatives but miss all positives.

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