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BOSO
View on CRAN: Click
here
Download and install BOSO package within the R console
Install from CRAN:
install.packages("BOSO")
Install from Github:
library("remotes")
install_github("cran/BOSO") Install by package version:
library("remotes")
install_version("BOSO", "1.0.4") Attach the package and use:
library("BOSO")
Maintained by
Luis V. Valcarcel
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-07-01
Latest Update:
Description:
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.
].
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 .
How to cite:
Luis V. Valcarcel (2021). BOSO: Bilevel Optimization Selector Operator. R package version 1.0.4, https://cran.r-project.org/web/packages/BOSO. Accessed 07 Oct. 2026.
Previous versions and publish date:
Other packages that cited BOSO R package
View BOSO citation profile
Other R packages that BOSO depends,
imports, suggests or enhances
Functions, R codes and Examples using
the BOSO R package
Some associated functions: BOSO.multiple.coldstart . BOSO.multiple.warmstart . BOSO . BOSO.single . InternalFunctions . SimResultsVignette . coef.BOSO . predict.BOSO . sim.xy .
Some associated R codes: BOSO.R . BOSO_multiple_ColdStart.R . BOSO_multiple_WarmStart.R . utils.R . Full BOSO package functions and examples
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