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Robust performance metrics for imbalanced classification problems
Hajo Holzmann, Bernhard Klar
https://arxiv.org/abs/2404.07661 https://

Robust performance metrics for imbalanced classification problems
We show that established performance metrics in binary classification, such as the F-score, the Jaccard similarity coefficient or Matthews' correlation coefficient (MCC), are not robust to class imbalance in the sense that if the proportion of the minority class tends to $0$, the true positive rate (TPR) of the Bayes classifier under these metrics tends to $0$ as well. Thus, in imbalanced classification problems, these metrics favour classifiers which ignore the minority class. To alleviate thi…