mRMRe

Parallelized Minimum Redundancy, Maximum Relevance (mRMR) Ensemble Feature Selection

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.

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Description file content

Package
mRMRe
Type
Package
Title
Parallelized Minimum Redundancy, Maximum Relevance (mRMR) Ensemble Feature Selection
Version
2.0.7
Date
2017-05-03
Author
Nicolas De Jay, Simon Papillon-Cavanagh, Catharina Olsen, Gianluca Bontempi, Benjamin Haibe-Kains
Maintainer
Benjamin Haibe-Kains
Description
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.
License
Artistic-2.0
Depends
survival, igraph, methods
URL
NeedsCompilation
yes
Packaged
2017-11-03 18:58:14 UTC; root
Repository
CRAN
Date/Publication
2017-11-03 23:41:27 UTC

install.packages('mRMRe')

2.0.7

a year ago

http://www.pmgenomics.ca/bhklab/

Benjamin Haibe-Kains

Artistic-2.0

Depends on

survival, igraph, methods

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