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Class imbalance usually damages the performance of classifiers. Thus, it is important to treat data before applying a classifier algorithm. This package includes recent resampling algorithms in the literature: (Barua et al. 2014) <doi:10.1109/tkde.2012.232>; (Das et al. 2015) <doi:10.1109/tkde.2014.2324567>, (Zhang et al. 2014) <doi:10.1016/j.inffus.2013.12.003>; (Gao et al. 2014) <doi:10.1016/j.neucom.2014.02.006>; (Almogahed et al. 2014) <doi:10.1007/s00500-014-1484-5>. It also includes an useful interface to perform oversampling.
Version: | 1.0.2.1 |
Depends: | R (≥ 3.3.0) |
Imports: | bnlearn, KernelKnn, ggplot2, utils, stats, mvtnorm, Rcpp, smotefamily, FNN, C50 |
LinkingTo: | Rcpp, RcppArmadillo |
Suggests: | testthat, knitr, rmarkdown |
Published: | 2020-04-07 |
DOI: | 10.32614/CRAN.package.imbalance |
Author: | Ignacio Cordón [aut, cre], Salvador García [aut], Alberto Fernández [aut], Francisco Herrera [aut] |
Maintainer: | Ignacio Cordón <nacho.cordon.castillo at gmail.com> |
BugReports: | http://github.com/ncordon/imbalance/issues |
License: | GPL-2 | GPL-3 | file LICENSE [expanded from: GPL (≥ 2) | file LICENSE] |
URL: | http://github.com/ncordon/imbalance |
NeedsCompilation: | yes |
Citation: | imbalance citation info |
Materials: | README NEWS |
CRAN checks: | imbalance results |
Reference manual: | imbalance.pdf |
Vignettes: |
Working with imbalanced dataset |
Package source: | imbalance_1.0.2.1.tar.gz |
Windows binaries: | r-devel: imbalance_1.0.2.1.zip, r-release: imbalance_1.0.2.1.zip, r-oldrel: imbalance_1.0.2.1.zip |
macOS binaries: | r-release (arm64): imbalance_1.0.2.1.tgz, r-oldrel (arm64): imbalance_1.0.2.1.tgz, r-release (x86_64): imbalance_1.0.2.1.tgz, r-oldrel (x86_64): imbalance_1.0.2.1.tgz |
Old sources: | imbalance archive |
Reverse suggests: | randomForestSRC, rbooster |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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