ML//Evaluation//ROC-AUC

Area under the ROC curve: the probability the model ranks a random positive above a random negative.

Area under the ROC curve: the probability the model ranks a random positive above a random negative.

0.5 is a coin, 1.0 is a perfect oracle. Reads cleanly and is threshold-independent.

Deceptive under class imbalance: rewards ranking even when almost every alarm is a false positive. Pair it with PR-AUC.

A model can be directionally right (ROC 0.72) and operationally useless at the same time.