Calculates Robust Performance Metrics for Imbalanced Classification Problems

Calculates robust Matthews Correlation Coefficient (MCC), Cohen's Kappa, and robust F-Beta Scores, as introduced by Holzmann and Klar (2026) . These performance metrics are designed for imbalanced classification problems. Plots the receiver operating characteristic curve (ROC curve) together with the recall / 1-precision curve.

This package implements some of the tools described in

Holzmann, H. and Klar, B. (2026). Robust performance metrics for imbalanced classification problems.

arXiv:2404.07661. \href{https://arxiv.org/abs/2404.07661}{LINK}

It calculates the robust Matthews Correlation Coefficient (MCC), Cohen's Kappa, and the robust F-Beta Score, which are performance metrics designed for imbalanced classification problems. Along with the robust MCC, the receiver operating characteristic curve and the recall/1-precision curve are plotted.