imbalance: Preprocessing Algorithms for Imbalanced Datasets

Algorithms to treat imbalanced datasets. Imbalanced datasets usually damage the performance of the classifiers. Thus, it is important to treat data before applying a classifier algorithm. This package includes recent preprocessing algorithms in the literature.

Version: 0.1.1
Depends: R (≥ 3.3.0)
Imports: bnlearn, KernelKnn, ggplot2, utils, stats, mvtnorm, Rcpp
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, C50, knitr, rmarkdown, FNN, smotefamily
Published: 2017-11-15
Author: Ignacio Cordón [aut, cre]
Maintainer: Ignacio Cordón <nacho.cordon.castillo at>
License: GPL-2 | GPL-3 | file LICENSE [expanded from: GPL (≥ 2) | file LICENSE]
NeedsCompilation: yes
Materials: README
CRAN checks: imbalance results


Reference manual: imbalance.pdf
Vignettes: Working with imbalanced dataset
Package source: imbalance_0.1.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: imbalance_0.1.1.tgz
OS X Mavericks binaries: r-oldrel: imbalance_0.1.1.tgz
Old sources: imbalance archive


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