Description
Calculates Robust Performance Metrics for Imbalanced Classification Problems.
Description
Calculates robust Matthews Correlation Coefficient (MCC) and robust F-Beta Scores, as introduced by Holzmann and Klar (2024) <doi:10.48550/arXiv.2404.07661>. These performance metrics are designed for imbalanced classification problems. Plots the receiver operating characteristic curve (ROC curve) together with the recall / 1-precision curve.
README.md
This package implements some of the tools described in
Holzmann, H. and Klar, B. (2024). 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) 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.