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AI & Machine Learning · Intermediate

Area Under the Curve (AUC)

The area under the ROC curve, summarizing a classifier's ability to rank positives above negatives (0.5 = random, 1.0 = perfect).

Definition

ROC AUC equals the probability that a random positive is scored higher than a random negative. It is threshold-independent and widely used to compare binary classifiers. On heavily imbalanced data, PR AUC is often more informative.

Exam tip

AUC 0.5 means no better than chance; for rare positives prefer PR AUC.

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