Package: varrank 0.5

Annina Cincera

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.

Authors:Gilles Kratzer [aut], Reinhard Furrer [ctb], Annina Cincera [cre]

varrank_0.5.tar.gz
varrank_0.5.tar.gz(r-4.5-noble)varrank_0.5.tar.gz(r-4.4-noble)
varrank_0.5.tgz(r-4.4-emscripten)varrank_0.5.tgz(r-4.3-emscripten)
varrank.pdf |varrank.html
varrank/json (API)
NEWS

# Install 'varrank' in R:
install.packages('varrank', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • nassCDS - Airbag and other influences on accident fatalities

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.56 score 18 scripts 204 downloads 2 mentions 5 exports 1 dependencies

Last updated 2 years agofrom:d55ca4bd9b. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 22 2024
R-4.5-linuxOKNov 22 2024

Exports:discretizationentropy.datami.dataplot.varrankvarrank

Dependencies:FNN

varrank: An R Package for Variable Ranking Based on Mutual Information with Applications to Systems Epidemiology

Rendered fromvarrank.Rmdusingknitr::knitron Nov 22 2024.

Last update: 2021-04-12
Started: 2018-04-23