Package: gaselect 1.0.22

David Kepplinger

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.

Authors:David Kepplinger

gaselect_1.0.22.tar.gz
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gaselect_1.0.22.tgz(r-4.4-emscripten)gaselect_1.0.22.tgz(r-4.3-emscripten)
gaselect.pdf |gaselect.html✨
gaselect/json (API)

# Install 'gaselect' in R:
install.packages('gaselect', repos = 'https://cloud.r-project.org')

Bug tracker:https://github.com/dakep/gaselect/issues1 issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

openblascpp

1.70 score 1 stars 341 downloads 1 mentions 9 exports 2 dependencies

Last updated 1 years agofrom:66d335de9c. Checks:3 OK. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 06 2025
R-4.5-linux-x86_64OKMar 06 2025
R-4.4-linux-x86_64OKMar 06 2025

Exports:evaluatorFitevaluatorLMevaluatorPLSevaluatorUserFunctionfitnessfitnessEvolutiongenAlggenAlgControlsubsets

Dependencies:RcppRcppArmadillo

Citation

To cite package ‘gaselect’ in publications use:

Kepplinger D (2023). gaselect: Genetic Algorithm (GA) for Variable Selection from High-Dimensional Data. R package version 1.0.22, https://CRAN.R-project.org/package=gaselect.

ATTENTION: This citation information has been auto-generated from the package DESCRIPTION file and may need manual editing, see ‘help("citation")’.

Corresponding BibTeX entry: 

  @Manual{,
    title = {gaselect: Genetic Algorithm (GA) for Variable Selection
      from High-Dimensional Data},
    author = {David Kepplinger},
    year = {2023},
    note = {R package version 1.0.22},
    url = {https://CRAN.R-project.org/package=gaselect},
  }

Readme and manuals

gaselect R package

This R package implements a genetic algorithm (GA) for variable selection as described in Kepplinger, D., Filzmoser, P., and Varmuza, K. (2017). Variable selection with genetic algorithms using repeated cross-validation of PLS regression models as fitness measure. https://arxiv.org/abs/1711.06695.

Installation

To install the latest release from CRAN, run the following R code in the R console:

install.packages('gaselect')

The most recent stable version as well as the developing version might not yet be available on CRAN. These can be directly installed from github using the devtools package:

# Install the most recent stable version:
install_github('dakep/gaselect')
# Install the (unstable) develop version:
install_github('dakep/gaselect', ref = 'develop')

Help Manual

Help pageTopics
Evaluate the fitness of variable subsetsevaluate evaluate,GenAlgEvaluator,matrix,numeric,ANY,integer,missing-method evaluate,GenAlgEvaluator,matrix,numeric,ANY,missing,integer-method evaluate,GenAlgEvaluator,matrix,numeric,ANY,missing,missing-method evaluate,GenAlgEvaluator,matrix,numeric,logical,integer,integer-method evaluate,GenAlgEvaluator,matrix,numeric,matrix,integer,integer-method
Fit EvaluatorevaluatorFit
LM EvaluatorevaluatorLM
PLS EvaluatorevaluatorPLS
User Defined EvaluatorevaluatorUserFunction
Get the fitness of a variable subsetfitness
Get the evolution of the fitnessfitnessEvolution
Format the raw segmentation list returned from the C++ code into a usable listformatSegmentation formatSegmentation,GenAlgFitEvaluator,list-method formatSegmentation,GenAlgLMEvaluator,list-method formatSegmentation,GenAlgPLSEvaluator,list-method formatSegmentation,GenAlgUserEvaluator,list-method
Genetic algorithm for variable subset selectiongenAlg
Result of a genetic algorithm runGenAlg GenAlg-class
Set control arguments for the genetic algorithmgenAlgControl
Control class for the genetic algorithmGenAlgControl GenAlgControl-class
Evaluator Base ClassGenAlgEvaluator GenAlgEvaluator-class
Fit EvaluatorGenAlgFitEvaluator GenAlgFitEvaluator-class
LM EvaluatorGenAlgLMEvaluator GenAlgLMEvaluator-class
PLS EvaluatorGenAlgPLSEvaluator GenAlgPLSEvaluator-class
User Function EvaluatorGenAlgUserEvaluator GenAlgUserEvaluator-class
Get the evaluation function from a GenAlgUserEvaluatorgetEvalFun getEvalFun,GenAlgEvaluator,GenAlg-method getEvalFun,GenAlgEvaluator,matrix-method getEvalFun,GenAlgUserEvaluator,GenAlg-method getEvalFun,GenAlgUserEvaluator,matrix-method
Get the found variable subset(s)subsets
Transform the object to a listtoCControlList toCControlList,GenAlgControl-method toCControlList,GenAlgFitEvaluator-method toCControlList,GenAlgLMEvaluator-method toCControlList,GenAlgPLSEvaluator-method toCControlList,GenAlgUserEvaluator-method
Get the transformed fitness valuestrueFitnessVal trueFitnessVal,GenAlgFitEvaluator,numeric-method trueFitnessVal,GenAlgLMEvaluator,numeric-method trueFitnessVal,GenAlgPLSEvaluator,numeric-method trueFitnessVal,GenAlgUserEvaluator,numeric-method
Check if the data is valid for the evaluatorvalidData validData,GenAlgEvaluator,GenAlg-method validData,GenAlgFitEvaluator,GenAlg-method validData,GenAlgLMEvaluator,GenAlg-method validData,GenAlgPLSEvaluator,GenAlg-method