
·6 min read
Practical ML Evaluation: Beyond Accuracy with Precision, Recall, and AUC
Stop using accuracy on imbalanced data: master Precision-Recall tradeoffs, F-beta scores, ROC-AUC vs PR-AUC, probability calibration (Brier score & Platt scaling), and threshold tuning.