BOSO: Bilevel Optimization Selector Operator
A novel feature selection algorithm for linear regression called
BOSO (Bilevel Optimization Selector Operator). The main contribution is the
use a bilevel optimization problem to select the variables in the training
problem that minimize the error in the validation set. Preprint available:
[Valcarcel, L. V., San Jose-Eneriz, E., Cendoya, X., Rubio, A., Agirre, X.,
Prosper, F., & Planes, F. J. (2020). "BOSO: a novel feature selection
algorithm for linear regression with high-dimensional data." bioRxiv.
<doi:10.1101/2020.11.18.388579>].
In order to run the vignette, it is recommended to install the 'bestsubset' package,
using the following command: devtools::install_github(repo="ryantibs/best-subset", subdir="bestsubset").
If you do not have gurobi, run devtools::install_github(repo="lvalcarcel/best-subset", subdir="bestsubset").
Moreover, to install cplexAPI you can check <https://github.com/lvalcarcel/cplexAPI>.
| Version: |
1.0.4 |
| Depends: |
R (≥ 4.0) |
| Imports: |
Matrix, MASS, methods |
| Suggests: |
cplexAPI, testthat, glmnet, knitr, rmarkdown, ggplot2, ggpubr, dplyr, kableExtra, devtools, BiocStyle, bestsubset |
| Published: |
2024-04-10 |
| Author: |
Luis V. Valcarcel 
[aut, cre, ctb],
Edurne San Jose-Eneriz
[aut],
Xabier Cendoya
[aut, ctb],
Angel Rubio [aut,
ctb],
Xabier Agirre
[aut],
Felipe Prósper
[aut],
Francisco J. Planes
[aut, ctb] |
| Maintainer: |
Luis V. Valcarcel <lvalcarcel at alumni.unav.es> |
| BugReports: |
https://github.com/lvalcarcel/BOSO/issues |
| License: |
GPL-3 |
| URL: |
https://github.com/lvalcarcel/BOSO |
| NeedsCompilation: |
no |
| SystemRequirements: |
IBM ILOG CPLEX (>= 12.1) |
| Materials: |
NEWS |
| CRAN checks: |
BOSO results |
Documentation:
Downloads:
Linking:
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