The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

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 red.ujaen.es>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README NEWS
CRAN checks: mldr.resampling results

Documentation:

Reference manual: mldr.resampling.pdf

Downloads:

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

Linking:

Please use the canonical form https://CRAN.R-project.org/package=mldr.resampling to link to this page.

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.
Health stats visible at Monitor.