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gaselect: Genetic Algorithm (GA) for Variable Selection from High-Dimensional Data

Provides a genetic algorithm for finding variable subsets in high dimensional data with high prediction performance. The genetic algorithm can use ordinary least squares (OLS) regression models or partial least squares (PLS) regression models to evaluate the prediction power of variable subsets. By supporting different cross-validation schemes, the user can fine-tune the tradeoff between speed and quality of the solution.

Version: 1.0.22
Depends: R (≥ 3.0.2), methods (≥ 2.10.0)
Imports: Rcpp (≥ 0.10.5)
LinkingTo: Rcpp (≥ 0.10.5), RcppArmadillo (≥ 0.9.800.4)
Suggests: chemometrics
Published: 2023-12-11
DOI: 10.32614/CRAN.package.gaselect
Author: David Kepplinger
Maintainer: David Kepplinger <david.kepplinger at gmail.com>
BugReports: https://github.com/dakep/gaselect/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/dakep/gaselect
NeedsCompilation: yes
Materials: README ChangeLog
CRAN checks: gaselect results

Documentation:

Reference manual: gaselect.pdf

Downloads:

Package source: gaselect_1.0.22.tar.gz
Windows binaries: r-devel: gaselect_1.0.22.zip, r-release: gaselect_1.0.22.zip, r-oldrel: gaselect_1.0.22.zip
macOS binaries: r-release (arm64): gaselect_1.0.22.tgz, r-oldrel (arm64): gaselect_1.0.22.tgz, r-release (x86_64): gaselect_1.0.22.tgz, r-oldrel (x86_64): gaselect_1.0.22.tgz
Old sources: gaselect archive

Reverse dependencies:

Reverse suggests: tidyfit

Linking:

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

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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