Robust Oversampling with RM-SMOTE for Imbalanced Classification R package ROBOSRMSMOTE version 1.0.0 Provides the ROBOSRMSMOTE (Robust Oversampling with RM-SMOTE) framework for imbalanced classification tasks. This package extends Mahalanobis distance-based oversampling techniques by integrating robust covariance estimators to better handle outliers and complex data distributions. The implemented methodology builds upon and significantly expands the RM-SMOTE algorithm originally proposed by Taban et al. (2025) <doi:10.1007/s10260-025-00819-8>. Software Depends: R (>= 4.0.0) Imports: rrcov (>= 1.7.0), meanShiftR (>= 0.56), stats Suggests: testthat (>= 3.0.0), knitr, rmarkdown Zainab Subhi Mahmood Hawrami <zaianbsubhi@gmail.com> Comprehensive R Archive Network (CRAN) Emre Dunder [aut], Mehmet Ali Cengiz [aut], Zainab Subhi Mahmood Hawrami [aut, cre], Abdulmohsen Alharthi [aut] GPL-3 2026-03-09 application/tgz https://CRAN.R-project.org/package=ROBOSRMSMOTE doi:10.32614/CRAN.package.ROBOSRMSMOTE