Package: mogavs 1.1.0
Tommi Pajala
mogavs: Multiobjective Genetic Algorithm for Variable Selection in Regression
Functions for exploring the best subsets in regression with a genetic algorithm. The package is much faster than methods relying on complete enumeration, and is suitable for data sets with large number of variables. For more information, see Sinha, Malo & Kuosmanen (2015) <doi:10.1080/10618600.2014.899236>.
Authors:
mogavs_1.1.0.tar.gz
mogavs_1.1.0.tar.gz(r-4.5-noble)mogavs_1.1.0.tar.gz(r-4.4-noble)
mogavs_1.1.0.tgz(r-4.4-emscripten)mogavs_1.1.0.tgz(r-4.3-emscripten)
mogavs.pdf |mogavs.html✨
mogavs/json (API)
| # Install 'mogavs' in R: |
| install.packages('mogavs', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- crimeData - Crime Data Set with Imputed Values
- sampleData - Simulated Data Set for MOGA-VS
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 7 years agofrom:af381ad16e. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 31 2024 |
| R-4.5-linux | OK | Oct 31 2024 |
Exports:createAdditionalPlotscv.mogavsgetBestModelgetBestModelVarsmogavsmogavs.defaultmogavs.formulamogavsToLinearplotVarUsagesummary.mogavs
Dependencies:cvToolsDEoptimRlatticerobustbase
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Package for regression variable selection with genetic algorithm MOGA-VS | mogavs-package |
| Function for plotting boundaries of the archive set. | createAdditionalPlots |
| Crime Data Set with Imputed Values | crimeData |
| k-Fold Crossvalidation for a mogavs model | cv.mogavs |
| Get the best model with nvar variables, or by AIC, BIC or knee-point. | getBestModel |
| Get variable names of the best model with nvar variables, or defined by lowest MSE, AIC, BIC or knee-point. | getBestModelVars |
| Multiobjective Genetic Algorithm for Variable Selection | mogavs mogavs.default mogavs.formula |
| Transform a mogavs model into a linear model. | mogavsToLinear |
| Produce a visual summary of how many times each variable appears on the efficient frontier. | plotVarUsage |
| Simulated Data Set for MOGA-VS | sampleData |
| Summary function for mogavs | summary.mogavs |