swaglm: Fast Sparse Wrapper Algorithm for Generalized Linear Models and
Testing 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 |
Documentation:
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