https://github.com/modal-inria/mlgl
Procedure of variable selection in the context of redundancy between explanatory variables, which holds true with high dimensional data
https://github.com/modal-inria/mlgl
group-lasso r variable-selection
Last synced: 3 days ago
JSON representation
Procedure of variable selection in the context of redundancy between explanatory variables, which holds true with high dimensional data
- Host: GitHub
- URL: https://github.com/modal-inria/mlgl
- Owner: modal-inria
- Created: 2020-02-19T14:40:45.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2023-03-15T18:38:00.000Z (over 2 years ago)
- Last Synced: 2025-06-09T17:42:47.053Z (19 days ago)
- Topics: group-lasso, r, variable-selection
- Language: R
- Homepage:
- Size: 172 KB
- Stars: 3
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# MLGL
[](https://github.com/modal-inria/MLGL/actions)
[](https://cran.r-project.org/package=MLGL) [](http://cranlogs.r-pkg.org/badges/grand-total/MLGL) [](https://cran.rstudio.com/web/packages/MLGL/index.html)
The code was originally on an [R-forge repository](https://r-forge.r-project.org/projects/hcgglasso/).
This package implements a new procedure of variable selection in the context of redundancy between explanatory variables, which holds true with high dimensional data.
## Installation
From github:
``` r
library(devtools)
install_github("modal-inria/MLGL")
```
From CRAN:
``` r
install.packages("MLGL", repos = "https://cran.rstudio.com")
```
### Dependencies
``` r
install.packages(c("gglasso", "MASS", "Matrix", "fastcluster", "FactoMineR", "parallelDist"), repos = "https://cran.rstudio.com")
```
## Credits
**MLGL** is developed by Quentin Grimonprez, Guillemette Marot, Alain Celisse and Samuel Blanck.
Copyright Inria - Université de Lille
## Licence
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as
published by the Free Software Foundation, either version 3 of the
License, or (at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
[GNU Affero General Public License](https://www.gnu.org/licenses/agpl-3.0.en.html) for more details.
## References
* Q. Grimonprez, S. Blanck, A. Celisse, G. Marot, MLGL: An R package implementing correlated variable selection by hierarchical clustering and group-Lasso. https://hal.inria.fr/hal-01857242