Robust Performance Metrics for Imbalanced Binary Classification Problems

Established performance metrics like F-score, Jaccard similarity coefficient, and Matthews correlation coefficient are not robust to class imbalance, favoring classifiers that ignore the minority class. Robust modifications of these metrics are proposed to ensure the true positive rate remains bounded away from 0 even in strongly imbalanced settings.