ROC curve and AUC
Also: ROC curve, ROC-AUC, AUC, AUROC, area under the curve
Sweeping a classifier’s decision threshold traces the ROC curve from (0, 0) to (1, 1). The area under it (AUC) is the probability that a randomly chosen positive is scored above a randomly chosen negative: 0.5 is chance, 1.0 is perfect ranking.
TPR = TP / (TP + FN), FPR = FP / (FP + TN)
Example
A fraud model with AUC = 0.85 ranks a random fraudulent transaction above a random legitimate one 85% of the time, regardless of which threshold is later chosen.