mRMRe: Parallelized Minimum Redundancy, Maximum Relevance (mRMR)

Computes mutual information matrices from continuous, categorical and survival variables, as well as feature selection with minimum redundancy, maximum relevance (mRMR) and a new ensemble mRMR technique. Published in De Jay et al. (2013) <doi:10.1093/bioinformatics/btt383>.

Version:	2.1.2.2
Depends:	R (≥ 3.5), survival, igraph, methods
Published:	2024-11-05
DOI:	10.32614/CRAN.package.mRMRe
Author:	Nicolas De Jay [aut], Simon Papillon-Cavanagh [aut], Catharina Olsen [aut], Gianluca Bontempi [aut], Bo Li [aut], Christopher Eeles [ctb], Benjamin Haibe-Kains [aut, cre]
Maintainer:	Benjamin Haibe-Kains <benjamin.haibe.kains at utoronto.ca>
License:	Artistic-2.0
URL:	https://www.pmgenomics.ca/bhklab/
NeedsCompilation:	yes
Citation:	mRMRe citation info
CRAN checks:	mRMRe results

Documentation:

Reference manual:	mRMRe.pdf
Vignettes:	mRMRe: an R package for parallelized mRMR ensemble feature selection (source, R code)

Downloads:

Package source:	mRMRe_2.1.2.2.tar.gz
Windows binaries:	r-devel: mRMRe_2.1.2.2.zip, r-release: mRMRe_2.1.2.2.zip, r-oldrel: mRMRe_2.1.2.2.zip
macOS binaries:	r-release (arm64): mRMRe_2.1.2.2.tgz, r-oldrel (arm64): mRMRe_2.1.2.2.tgz, r-release (x86_64): mRMRe_2.1.2.2.tgz, r-oldrel (x86_64): mRMRe_2.1.2.2.tgz
Old sources:	mRMRe archive

Reverse dependencies:

Reverse imports:	PAA, UBayFS
Reverse suggests:	FRESA.CAD, mlr, mlrCPO, tidyfit

Linking:

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