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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 [aut], María José Del Jesus [aut], Antonio Rivera [aut] |
Maintainer: | Miguel Ángel Dávila <madr0008 at red.ujaen.es> |
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: mldr.resampling_0.2.3.zip, r-release: mldr.resampling_0.2.3.zip, r-oldrel: mldr.resampling_0.2.3.zip |
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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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.