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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.

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Install

install.packages('RobustMetrics')

Monthly Downloads

156

Version

0.1.1

License

GPL (>= 3)

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Maintainer

Bernhard Klar

Last Published

September 2nd, 2025

Functions in RobustMetrics (0.1.1)

robFScore

Robust F-Beta Score
MCC

Matthews correlation coefficient
robFScore2

General robust F-Beta Score
FScore

F-Beta Score
robMCC

Robust Matthews correlation coefficient
ROC_curve

ROC curve
rf.data

Example Random Forest Data