Confusion Matrix and Basic Metrics
Understanding the 2x2 confusion matrix, extracting TP, TN, FP, FN, and diagnosing the dangerous Accuracy Paradox on imbalanced datasets.
Precision and Recall
Two complementary metrics exposing what accuracy hides—false alarms versus missed detections, and mastering the threshold tradeoff.
F-Scores and Balanced Metrics
Synthesizing precision and recall via the harmonic mean, custom weighting with F-beta, and evaluating imbalanced cohorts with Balanced Accuracy and MCC.
ROC-AUC and Threshold Tuning
Visualizing classifier discrimination across all cutoffs, interpreting the Area Under the Curve, and optimizing decision thresholds via Youden's J.
Multiclass and Choosing Metrics
Extending binary metrics to multiclass problems via Macro, Micro, and Weighted averaging, plus an interactive master metric selection guide.