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: 1.0.5
Depends: R (≥ 3.0.2), methods (≥ 2.10.0)
Imports: Rcpp (≥ 0.10.5)
LinkingTo: Rcpp (≥ 0.10.5), RcppArmadillo (≥ 0.4.000)
Suggests: chemometrics
Published: 2015-02-12
Author: David Kepplinger
Maintainer: David Kepplinger <david.kepplinger at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: ChangeLog
CRAN checks: gaselect results


Reference manual: gaselect.pdf
Package source: gaselect_1.0.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Mavericks binaries: r-release: gaselect_1.0.5.tgz, r-oldrel: gaselect_1.0.5.tgz
Old sources: gaselect archive


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