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: 1.3.5
Depends: rJava (≥ 0.5-0), R (≥ 2.70)
Imports: yaml, ggplot2, gridExtra, reshape2, dplyr, stringi, igraph, data.table (≥ 1.0.1)
Suggests: testthat, R.rsp
Published: 2021-09-18
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


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


Package source: rmcfs_1.3.5.tar.gz
Windows binaries: r-devel: rmcfs_1.3.5.zip, r-release: rmcfs_1.3.5.zip, r-oldrel: rmcfs_1.3.5.zip
macOS binaries: r-release (arm64): rmcfs_1.3.5.tgz, r-oldrel (arm64): rmcfs_1.3.5.tgz, r-release (x86_64): rmcfs_1.3.5.tgz, r-oldrel (x86_64): rmcfs_1.3.5.tgz
Old sources: rmcfs archive

Reverse dependencies:

Reverse imports: BASiNET


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