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.

rmcfs: The MCFS-ID Algorithm for Feature Selection and Interdependency Discovery

MCFS-ID (Monte Carlo Feature Selection and Interdependency Discovery) is a Monte Carlo method-based tool for feature selection. It also allows for the discovery of interdependencies between the relevant features. MCFS-ID is particularly suitable for the analysis of high-dimensional, 'small n large p' transactional and biological data. M. Draminski, J. Koronacki (2018) <doi:10.18637/jss.v085.i12>.

Version: 1.3.6
Depends: rJava (≥ 0.5-0), R (≥ 2.70)
Imports: yaml, ggplot2, gridExtra, reshape2, dplyr, stringi, igraph (≥ 2.0.0), data.table (≥ 1.0.1)
Suggests: testthat, R.rsp
Published: 2024-08-19
DOI: 10.32614/CRAN.package.rmcfs
Author: Michal Draminski [aut, cre], Jacek Koronacki [aut], Julian Zubek [ctb]
Maintainer: Michal Draminski <michal.draminski at ipipan.waw.pl>
License: GPL-3
URL: https://home.ipipan.waw.pl/m.draminski/mcfs.html
NeedsCompilation: no
SystemRequirements: Java (>= 7)
Citation: rmcfs citation info
Materials: NEWS
CRAN checks: rmcfs results

Documentation:

Reference manual: rmcfs.pdf
Vignettes: Draminski & Koronacki (2018): rmcfs paper (Journal of Statistical Software) (source)

Downloads:

Package source: rmcfs_1.3.6.tar.gz
Windows binaries: r-devel: rmcfs_1.3.6.zip, r-release: rmcfs_1.3.6.zip, r-oldrel: rmcfs_1.3.6.zip
macOS binaries: r-release (arm64): rmcfs_1.3.6.tgz, r-oldrel (arm64): rmcfs_1.3.6.tgz, r-release (x86_64): rmcfs_1.3.6.tgz, r-oldrel (x86_64): rmcfs_1.3.6.tgz
Old sources: rmcfs archive

Reverse dependencies:

Reverse imports: BASiNET

Linking:

Please use the canonical form https://CRAN.R-project.org/package=rmcfs 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.