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 ORCID iD [aut], Reinhard Furrer ORCID iD [ctb], Annina Cincera [cre]
Maintainer: Annina Cincera <annina.cincera at>
License: GPL-3
NeedsCompilation: no
Citation: varrank citation info
Materials: NEWS
CRAN checks: varrank results


Reference manual: varrank.pdf
Vignettes: varrank


Package source: varrank_0.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
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


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