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BOSO (version 1.0.4)

Bilevel Optimization Selector Operator

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 .

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Install

install.packages('BOSO')

Monthly Downloads

108

Version

1.0.4

License

GPL-3

Issues

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Maintainer

Luis V. Valcarcel

Last Published

April 10th, 2024

Functions in BOSO (1.0.4)

SimResultsVignette

sim.results for the vignette
coef.BOSO

Extract coefficients from a BOSO object
BOSO.multiple.coldstart

BOSO.single and associates functions
BOSO

BOSO and associates functions
BOSO.single

BOSO.single and associates functions
predict.BOSO

Predict function for BOSO object.
BOSO.multiple.warmstart

BOSO.single and associates functions
InternalFunctions

BOSO Internal Functions
sim.xy

High-5 and Low setting data