Package: SMOTEWB 1.2.5

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_1.2.5.tar.gz
SMOTEWB_1.2.5.zip(r-4.7-any)SMOTEWB_1.2.5.zip(r-4.6-any)SMOTEWB_1.2.5.zip(r-4.5-any)
SMOTEWB_1.2.5.tgz(r-4.6-any)SMOTEWB_1.2.5.tgz(r-4.5-any)
SMOTEWB_1.2.5.tar.gz(r-4.7-any)SMOTEWB_1.2.5.tar.gz(r-4.6-any)
SMOTEWB_1.2.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
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:

3.48 score 1 stars 1 packages 7 scripts 253 downloads 11 exports 8 dependencies

Last updated from:164af2621c. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK147
source / vignettesOK214
linux-releaseOK124
macos-releaseOK173
macos-oldrelOK199
windows-develOK61
windows-releaseOK65
windows-oldrelOK73
wasm-releaseOK108

Exports:ADASYNBLSMOTEGSMOTEROSROSERSLSMOTERUSRWOSLSMOTESMOTESMOTEWB

Dependencies:FNNRANNRcppRcppArmadilloRcppParallelRfastrpartzigg