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:
gaselect_1.0.22.tar.gz
gaselect_1.0.22.tar.gz(r-4.5-noble)gaselect_1.0.22.tar.gz(r-4.4-noble)
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 = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/dakep/gaselect/issues
Last updated 1 years agofrom:66d335de9c. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 06 2024 |
| R-4.5-linux-x86_64 | OK | Dec 06 2024 |
Exports:evaluatorFitevaluatorLMevaluatorPLSevaluatorUserFunctionfitnessfitnessEvolutiongenAlggenAlgControlsubsets
Dependencies:RcppRcppArmadillo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Evaluate the fitness of variable subsets | evaluate 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 Evaluator | evaluatorFit |
| LM Evaluator | evaluatorLM |
| PLS Evaluator | evaluatorPLS |
| User Defined Evaluator | evaluatorUserFunction |
| Get the fitness of a variable subset | fitness |
| Get the evolution of the fitness | fitnessEvolution |
| Format the raw segmentation list returned from the C++ code into a usable list | formatSegmentation formatSegmentation,GenAlgFitEvaluator,list-method formatSegmentation,GenAlgLMEvaluator,list-method formatSegmentation,GenAlgPLSEvaluator,list-method formatSegmentation,GenAlgUserEvaluator,list-method |
| Genetic algorithm for variable subset selection | genAlg |
| Result of a genetic algorithm run | GenAlg GenAlg-class |
| Set control arguments for the genetic algorithm | genAlgControl |
| Control class for the genetic algorithm | GenAlgControl GenAlgControl-class |
| Evaluator Base Class | GenAlgEvaluator GenAlgEvaluator-class |
| Fit Evaluator | GenAlgFitEvaluator GenAlgFitEvaluator-class |
| LM Evaluator | GenAlgLMEvaluator GenAlgLMEvaluator-class |
| PLS Evaluator | GenAlgPLSEvaluator GenAlgPLSEvaluator-class |
| User Function Evaluator | GenAlgUserEvaluator GenAlgUserEvaluator-class |
| Get the evaluation function from a GenAlgUserEvaluator | getEvalFun 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 list | toCControlList toCControlList,GenAlgControl-method toCControlList,GenAlgFitEvaluator-method toCControlList,GenAlgLMEvaluator-method toCControlList,GenAlgPLSEvaluator-method toCControlList,GenAlgUserEvaluator-method |
| Get the transformed fitness values | trueFitnessVal trueFitnessVal,GenAlgFitEvaluator,numeric-method trueFitnessVal,GenAlgLMEvaluator,numeric-method trueFitnessVal,GenAlgPLSEvaluator,numeric-method trueFitnessVal,GenAlgUserEvaluator,numeric-method |
| Check if the data is valid for the evaluator | validData validData,GenAlgEvaluator,GenAlg-method validData,GenAlgFitEvaluator,GenAlg-method validData,GenAlgLMEvaluator,GenAlg-method validData,GenAlgPLSEvaluator,GenAlg-method |