Package: SMOTEWB 1.2.0

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 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.

Authors:Fatih Saglam [aut, cre]

SMOTEWB_1.2.0.tar.gz
SMOTEWB_1.2.0.zip(r-4.5)SMOTEWB_1.2.0.zip(r-4.4)SMOTEWB_1.2.0.zip(r-4.3)
SMOTEWB_1.2.0.tgz(r-4.5-any)SMOTEWB_1.2.0.tgz(r-4.4-any)SMOTEWB_1.2.0.tgz(r-4.3-any)
SMOTEWB_1.2.0.tar.gz(r-4.5-noble)SMOTEWB_1.2.0.tar.gz(r-4.4-noble)
SMOTEWB_1.2.0.tgz(r-4.4-emscripten)SMOTEWB_1.2.0.tgz(r-4.3-emscripten)
SMOTEWB.pdf |SMOTEWB.html
SMOTEWB/json (API)

# Install 'SMOTEWB' in R:
install.packages('SMOTEWB', repos = c('https://fatihsaglam.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/fatihsaglam/smotewb/issues

On CRAN:

Conda:

3.77 score 1 stars 1 packages 13 scripts 243 downloads 11 exports 8 dependencies

Last updated 2 months agofrom:a215a7af5f. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 31 2025
R-4.5-winOKMar 31 2025
R-4.5-macOKMar 31 2025
R-4.5-linuxOKMar 31 2025
R-4.4-winOKMar 31 2025
R-4.4-macOKMar 31 2025
R-4.4-linuxOKMar 31 2025
R-4.3-winOKMar 31 2025
R-4.3-macOKMar 31 2025

Exports:ADASYNBLSMOTEGSMOTEROSROSERSLSMOTERUSRWOSLSMOTESMOTESMOTEWB

Dependencies:FNNRANNRcppRcppArmadilloRcppParallelRfastrpartzigg