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 |
| Reference manual: | GenAlgo.pdf |
| Vignettes: |
OOMPA GenAlgo |
| 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, r-oldrel (x86_64): GenAlgo_2.2.0.tgz |
| Old sources: | GenAlgo archive |
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