ROBOSRMSMOTE
Robust Oversampling with RM-SMOTE for Imbalanced Classification
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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.0 |
rolling linux/jammy R-4.5 | ROBOSRMSMOTE_1.0.0.tar.gz |
37.4 KiB |
1.0.0 |
rolling linux/noble R-4.5 | ROBOSRMSMOTE_1.0.0.tar.gz |
37.3 KiB |
1.0.0 |
rolling source/ R- | ROBOSRMSMOTE_1.0.0.tar.gz |
16.0 KiB |
1.0.0 |
latest linux/jammy R-4.5 | ROBOSRMSMOTE_1.0.0.tar.gz |
37.4 KiB |
1.0.0 |
latest linux/noble R-4.5 | ROBOSRMSMOTE_1.0.0.tar.gz |
37.3 KiB |
1.0.0 |
latest source/ R- | ROBOSRMSMOTE_1.0.0.tar.gz |
16.0 KiB |
1.0.0 |
2026-04-26 source/ R- | ROBOSRMSMOTE_1.0.0.tar.gz |
16.0 KiB |
1.0.0 |
2026-04-23 source/ R- | ROBOSRMSMOTE_1.0.0.tar.gz |
16.0 KiB |
1.0.0 |
2026-04-09 windows/windows R-4.5 | ROBOSRMSMOTE_1.0.0.zip |
41.3 KiB |