GAparsimony: Searching Parsimony Models with Genetic Algorithms

Methodology that combines feature selection, model tuning, and parsimonious model selection with Genetic Algorithms (GA) proposed in {Martinez-de-Pison} (2015) <doi:10.1016/j.asoc.2015.06.012>. To this objective, a novel GA selection procedure is introduced based on separate cost and complexity evaluations.

Version: 0.9.2
Depends: R (≥ 3.0), methods, foreach, iterators
Imports: stats, graphics, grDevices, utils
Suggests: parallel, doParallel, doRNG (≥ 1.6), knitr (≥ 1.8), lhs, MASS, caret, mlbench, e1071, nnet, kernlab
Published: 2018-05-18
Author: F.J. Martinez-de-Pison [aut, cre]
Maintainer: F.J. Martinez-de-Pison <fjmartin at unirioja.es>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/jpison/GAparsimony
NeedsCompilation: no
Materials: NEWS
CRAN checks: GAparsimony results

Downloads:

Reference manual: GAparsimony.pdf
Package source: GAparsimony_0.9.2.tar.gz
Windows binaries: r-devel: GAparsimony_0.9.2.zip, r-release: GAparsimony_0.9.2.zip, r-oldrel: GAparsimony_0.9.2.zip
OS X binaries: r-release: GAparsimony_0.9.2.tgz, r-oldrel: GAparsimony_0.9.2.tgz
Old sources: GAparsimony archive

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