Package: gaselect 1.0.25

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 [aut, cre]

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gaselect_1.0.25.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
gaselect/json (API)

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

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

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

On CRAN:

Conda:

openblascpp

2.00 score 1 stars 4 scripts 438 downloads 1 mentions 9 exports 2 dependencies

Last updated from:cd5a8f82bc. Checks:10 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK119
linux-devel-x86_64OK147
source / vignettesOK212
linux-release-arm64OK116
linux-release-x86_64OK139
windows-devel-arm64OK246
windows-devel-x86_64OK205
windows-release-arm64OK259
windows-release-x86_64OK118
wasm-releaseOK113

Exports:evaluatorFitevaluatorLMevaluatorPLSevaluatorUserFunctionfitnessfitnessEvolutiongenAlggenAlgControlsubsets

Dependencies:RcppRcppArmadillo

Readme and manuals

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