GenAlgo: Classes and Methods to Use Genetic Algorithms for Feature Selection

Defines classes and methods that can be used to implement genetic algorithms for feature selection. The idea is that we want to select a fixed number of features to combine into a linear classifier that can predict a binary outcome, and can use a genetic algorithm heuristically to select an optimal set of features.

Version: 2.2.0
Depends: R (≥ 3.0)
Imports: methods, stats, MASS, oompaBase (≥ 3.0.1), ClassDiscovery
Suggests: Biobase, xtable
Published: 2020-10-15
Author: Kevin R. Coombes
Maintainer: Kevin R. Coombes <krc at silicovore.com>
License: Apache License (== 2.0)
URL: http://oompa.r-forge.r-project.org/
NeedsCompilation: no
Materials: NEWS
CRAN checks: GenAlgo results

Documentation:

Reference manual: GenAlgo.pdf
Vignettes: OOMPA GenAlgo

Downloads:

Package source: GenAlgo_2.2.0.tar.gz
Windows binaries: r-devel: GenAlgo_2.2.0.zip, r-release: GenAlgo_2.2.0.zip, r-oldrel: GenAlgo_2.2.0.zip
macOS binaries: r-release (arm64): GenAlgo_2.2.0.tgz, r-oldrel (arm64): GenAlgo_2.2.0.tgz, r-release (x86_64): GenAlgo_2.2.0.tgz
Old sources: GenAlgo archive

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