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:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=varrank
to link to this page.