mldr.resampling: Resampling Algorithms for Multi-Label Datasets

Collection of the state of the art multi-label resampling algorithms. The objective of these algorithms is to achieve balance in multi-label datasets.

Version: 0.2.3
Imports: data.table, e1071, mldr, pbapply, vecsets
Suggests: parallel
Published: 2023-08-22
DOI: 10.32614/CRAN.package.mldr.resampling
Author: Miguel Ángel Dávila [cre], Francisco Charte ORCID iD [aut], María José Del Jesus ORCID iD [aut], Antonio Rivera ORCID iD [aut]
Maintainer: Miguel Ángel Dávila <madr0008 at>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README NEWS
CRAN checks: mldr.resampling results


Reference manual: mldr.resampling.pdf


Package source: mldr.resampling_0.2.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): mldr.resampling_0.2.3.tgz, r-oldrel (arm64): mldr.resampling_0.2.3.tgz, r-release (x86_64): mldr.resampling_0.2.3.tgz, r-oldrel (x86_64): mldr.resampling_0.2.3.tgz
Old sources: mldr.resampling archive


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