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ROBOSRMSMOTE  

Robust Oversampling with RM-SMOTE for Imbalanced Classification
View on CRAN: Click here


Download and install ROBOSRMSMOTE package within the R console
Install from CRAN:
install.packages("ROBOSRMSMOTE")

Install from Github:
library("remotes")
install_github("cran/ROBOSRMSMOTE")

Install by package version:
library("remotes")
install_version("ROBOSRMSMOTE", "1.0.0")



Attach the package and use:
library("ROBOSRMSMOTE")
Maintained by
Zainab Subhi Mahmood Hawrami
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-03-09
Latest Update: 2026-03-09
Description:
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>.
How to cite:
Zainab Subhi Mahmood Hawrami (2026). ROBOSRMSMOTE: Robust Oversampling with RM-SMOTE for Imbalanced Classification. R package version 1.0.0, https://cran.r-project.org/web/packages/ROBOSRMSMOTE. Accessed 11 Sep. 2026.
Previous versions and publish date:
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Complete documentation for ROBOSRMSMOTE
Functions, R codes and Examples using the ROBOSRMSMOTE R package
Full ROBOSRMSMOTE package functions and examples
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