swaglm: Fast Sparse Wrapper Algorithm for Generalized Linear Models andTesting Procedures for Network of Highly Predictive Variables
Provides a fast implementation of the SWAG algorithm for Generalized Linear Models which allows to perform a meta-learning procedure that combines screening and wrapper methods to find a set of extremely low-dimensional attribute combinations. The package then performs test on the network of selected models to identify the variables that are highly predictive by using entropy-based network measures.
| Version: | 0.0.1 |
| Imports: | Rcpp,fastglm, stats,igraph,gdata,plyr,progress,DescTools,scales,fields |
| LinkingTo: | Rcpp,RcppArmadillo |
| Suggests: | knitr,MASS,rmarkdown |
| Published: | 2025-09-18 |
| DOI: | 10.32614/CRAN.package.swaglm |
| Author: | Lionel Voirol [aut, cre], Yagmur Ozdemir [aut] |
| Maintainer: | Lionel Voirol <lionelvoirol at hotmail.com> |
| License: | AGPL-3 |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | swaglm results |
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