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 |
| Reference manual: | gaselect.pdf |
| 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 suggests: | tidyfit |
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