Imbalanced Resampling using SMOTE with Boosting (SMOTEWB)

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.


Reference manual

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install.packages("SMOTEWB")

1.2.5 by Fatih Saglam, a year ago


Browse source code at https://github.com/cran/SMOTEWB


Authors: Fatih Saglam [aut, cre] (ORCID:


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports stats, FNN, RANN, rpart, Rfast


Imported by imbalanceDatRel.


See at CRAN