Package: imbalanceKit
Type: Package
Title: Resampling Methods and Tools for Imbalanced Classification
Version: 0.2.0
Authors@R: 
    c(person("Fatih", "Saglam", email = "saglamf89@gmail.com", 
    role = c("aut", "cre"), 
    comment = c(ORCID = "0000-0002-2084-2008")))
Description: A collection of resampling methods for class imbalance in
    classification problems. Includes the oversampling methods SMOTE with
    boosting (SMOTEWB) by F. Sağlam and M. A. Cengiz (2022)
    <doi:10.1016/j.eswa.2022.117023>, Markov chain SMOTE (MCSMOTE) by
    F. Sağlam and M. A. Cengiz (2025) <doi:10.1016/j.asoc.2025.113906>,
    uncertainty guided oversampling (UGO) by F. Sağlam and M. A. Cengiz (2026)
    <doi:10.1016/j.knosys.2026.115886>, and bi-directional SMOTE (BiSMOTE) by
    F. Sağlam and U. Yamak (2027) <doi:10.1016/j.eswa.2026.134648>, and the
    data relocation approach DatRel by F. Sağlam (2025)
    <doi:10.1007/s10994-025-06755-8>, which can also be applied to synthetic
    samples from any other source, together with commonly used alternatives
    such as SMOTE, ADASYN, Borderline-SMOTE, Safe-Level-SMOTE, Radius-SMOTE,
    VS-SMOTE, geometric SMOTE, random oversampling and undersampling.
    The methods share the same interface: they take a feature matrix and a
    factor class variable and return the resampled data together with the
    synthetic samples. The package also provides performance metrics for
    imbalanced classification and data complexity measures of class
    imbalance, class overlap and noise.
Depends: R (>= 4.0.0)
Imports: stats, utils, FNN, rpart, Rfast, Rcpp
LinkingTo: Rcpp
Suggests: randomForest, nnet, testthat (>= 3.0.0), knitr, rmarkdown
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
Config/testthat/edition: 3
URL: https://fatihsaglam.github.io/imbalanceKit/
Config/roxygen2/version: 8.1.1
NeedsCompilation: yes
Packaged: 2026-11-13 19:48:04 UTC; sagla
Author: Fatih Saglam [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-2084-2008>)
Maintainer: Fatih Saglam <saglamf89@gmail.com>
Repository: CRAN
Date/Publication: 2026-11-14 15:50:38 UTC
