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>.

Depends: R (≥ 3.5), survival, igraph, methods
Published: 2023-04-25
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>
License: Artistic-2.0
NeedsCompilation: yes
Citation: mRMRe citation info
CRAN checks: mRMRe results


Reference manual: mRMRe.pdf
Vignettes: mRMRe: an R package for parallelized mRMR ensemble feature selection


Package source: mRMRe_2.1.2.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): mRMRe_2.1.2.1.tgz, r-oldrel (arm64): mRMRe_2.1.2.1.tgz, r-release (x86_64): mRMRe_2.1.2.1.tgz, r-oldrel (x86_64): mRMRe_2.1.2.1.tgz
Old sources: mRMRe archive

Reverse dependencies:

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


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