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SMOTEWB (version 1.2.5)

Imbalanced Resampling using SMOTE with Boosting (SMOTEWB)

Description

Provides the SMOTE with Boosting (SMOTEWB) algorithm. See F. Sağlam, M. A. Cengiz (2022) . 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 each 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.

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Version

Install

install.packages('SMOTEWB')

Monthly Downloads

526

Version

1.2.5

License

MIT + file LICENSE

Maintainer

Fatih Saglam

Last Published

October 16th, 2025

Functions in SMOTEWB (1.2.5)

SLSMOTE

Safe-level Synthetic Minority Oversampling Technique
SMOTE

Synthetic Minority Oversampling Technique (SMOTE)
RWO

Random Walk Oversampling (SMOTE)
ROSE

Randomly Over Sampling Examples
ROS

Random Oversampling (ROS)
RUS

Random Undersampling (RUS)
ADASYN

Adaptive Synthetic Sampling
BLSMOTE

Borderline Synthetic Minority Oversampling Technique
RSLSMOTE

Relocating safe-level SMOTE with minority outcast handling
GSMOTE

Geometric Synthetic Minority Oversamplnig Technique (GSMOTE)
SMOTEWB

SMOTE with boosting (SMOTEWB)