varrank: Heuristics Tools Based on Mutual Information for Variable Ranking

A computational toolbox of heuristics approaches for performing variable ranking and feature selection based on mutual information well adapted for multivariate system epidemiology datasets. The core function is a general implementation of the minimum redundancy maximum relevance model. R. Battiti (1994) <doi:10.1109/72.298224>. Continuous variables are discretized using a large choice of rule. Variables ranking can be learned with a sequential forward/backward search algorithm. The two main problems that can be addressed by this package is the selection of the most representative variable within a group of variables of interest (i.e. dimension reduction) and variable ranking with respect to a set of features of interest.

Version:	0.5
Depends:	R (≥ 3.5.0)
Imports:	stats, FNN, grDevices
Suggests:	Boruta, FSelector, caret, e1071, mlbench, psych, varSelRF, gplots, entropy, testthat, knitr, markdown
Published:	2022-10-12
DOI:	10.32614/CRAN.package.varrank
Author:	Gilles Kratzer [aut], Reinhard Furrer [ctb], Annina Cincera [cre]
Maintainer:	Annina Cincera <annina.cincera at math.uzh.ch>
License:	GPL-3
URL:	https://www.math.uzh.ch/pages/varrank/
NeedsCompilation:	no
Citation:	varrank citation info
Materials:	NEWS
CRAN checks:	varrank results

Documentation:

Reference manual:	varrank.pdf
Vignettes:	varrank

Downloads:

Package source:	varrank_0.5.tar.gz
Windows binaries:	r-devel: varrank_0.5.zip, r-release: varrank_0.5.zip, r-oldrel: varrank_0.5.zip
macOS binaries:	r-release (arm64): varrank_0.5.tgz, r-oldrel (arm64): varrank_0.5.tgz, r-release (x86_64): varrank_0.5.tgz, r-oldrel (x86_64): varrank_0.5.tgz
Old sources:	varrank archive

Linking:

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