ROC Curve (Receiver Operating Characteristic)
For a binary classifier that outputs a score/probability, the ROC curve plots true positive rate (recall) vs false positive rate as the classification threshold varies from 0 to 1.
- TPR = TP / (TP + FN) — fraction of positives correctly identified
- FPR = FP / (FP + TN) — fraction of negatives incorrectly flagged
A random classifier lies on the diagonal (TPR = FPR).
Better classifiers bow toward the top-left corner (high TPR, low FPR).
The area under this curve is the AUROC.
![[ROC curve-1764061952603.webp]]
Interactive demo:
