SMOTEWB: Imbalanced Resampling using SMOTE with Boosting (SMOTEWB)

Provides the SMOTE with Boosting (SMOTEWB) algorithm. See F. Sağlam, M. A. Cengiz (2022) <doi:10.1016/j.eswa.2022.117023>. It is a SMOTE-based resampling technique which creates synthetic data on the links between nearest neighbors. SMOTEWB uses boosting weights to determine where to generate new samples and automatically decides the number of neighbors for eacg sample. It is robust to noise and outperforms most of the alternatives according to Matthew Correlation Coefficient metric. Alternative resampling methods are also available in the package.

Version: 1.2.0
Depends: R (≥ 4.2)
Imports: stats, FNN, RANN, rpart, Rfast
Published: 2024-04-08
DOI: 10.32614/CRAN.package.SMOTEWB
Author: Fatih Saglam ORCID iD [aut, cre]
Maintainer: Fatih Saglam <saglamf89 at>
License: MIT + file LICENSE
NeedsCompilation: no
Citation: SMOTEWB citation info
Materials: README
CRAN checks: SMOTEWB results


Reference manual: SMOTEWB.pdf


Package source: SMOTEWB_1.2.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): SMOTEWB_1.2.0.tgz, r-oldrel (arm64): SMOTEWB_1.2.0.tgz, r-release (x86_64): SMOTEWB_1.2.0.tgz, r-oldrel (x86_64): SMOTEWB_1.2.0.tgz
Old sources: SMOTEWB archive

Reverse dependencies:

Reverse imports: imbalanceDatRel


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