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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.0.1 |
rolling linux/jammy R-4.5 | swaglm_0.0.1.tar.gz |
463.9 KiB |
0.0.1 |
rolling linux/noble R-4.5 | swaglm_0.0.1.tar.gz |
467.3 KiB |
0.0.1 |
rolling source/ R- | swaglm_0.0.1.tar.gz |
344.3 KiB |
0.0.1 |
latest linux/jammy R-4.5 | swaglm_0.0.1.tar.gz |
463.9 KiB |
0.0.1 |
latest linux/noble R-4.5 | swaglm_0.0.1.tar.gz |
467.3 KiB |
0.0.1 |
latest source/ R- | swaglm_0.0.1.tar.gz |
344.3 KiB |
0.0.1 |
2026-04-26 source/ R- | swaglm_0.0.1.tar.gz |
344.3 KiB |
0.0.1 |
2026-04-23 source/ R- | swaglm_0.0.1.tar.gz |
344.3 KiB |
0.0.1 |
2026-04-09 windows/windows R-4.5 | swaglm_0.0.1.zip |
780.0 KiB |