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.

AuthorKevin R. Coombes
Bioconductor views Clustering Microarray
Date of publication2016-05-09 21:26:32
MaintainerKevin R. Coombes <krc@silicovore.com>
LicenseApache License (== 2.0)
Version2.1.2
http://oompa.r-forge.r-project.org/

View on R-Forge

Files

DESCRIPTION
NAMESPACE
NEWS
R
R/AllGenerics.R R/cp00-utility.R R/cp01-genalg.R
TODO
build
build/vignette.rds
data
data/gaTourResults.rda
data/tourData09.rda
inst
inst/doc
inst/doc/genalg.R
inst/doc/genalg.Rnw
inst/doc/genalg.pdf
man
man/gaTourResults.Rd man/genalg-class.Rd man/genalg-tools.Rd man/genalg.Rd man/maha.Rd man/tourData09.Rd
vignettes
vignettes/genalg.Rnw

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.