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, A.Rada-Iglesias, S.Enroth, C.Wadelius, J. Koronacki, J.Komorowski (2008) <doi:10.1093/bioinformatics/btm486>.

Version: 1.2.10
Depends: rJava (≥ 0.5-0), R (≥ 2.70)
Imports: yaml, ggplot2, reshape2, dplyr, igraph (≥ 1.0.1)
Suggests: testthat, R.rsp
Published: 2018-03-27
Author: Michal Draminski [aut, cre], Jacek Koronacki [aut], Julian Zubek [ctb]
Maintainer: Michal Draminski <michal.draminski at ipipan.waw.pl>
License: GPL-3
URL: www.ipipan.eu/staff/m.draminski/mcfs.html
NeedsCompilation: no
SystemRequirements: Java (>= 6)
Citation: rmcfs citation info
Materials: NEWS
CRAN checks: rmcfs results

Downloads:

Reference manual: rmcfs.pdf
Vignettes: The rmcfs Package
Package source: rmcfs_1.2.10.tar.gz
Windows binaries: r-devel: rmcfs_1.2.10.zip, r-release: rmcfs_1.2.10.zip, r-oldrel: rmcfs_1.2.10.zip
OS X binaries: r-release: rmcfs_1.2.10.tgz, r-oldrel: not available
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.