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. ]. 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").


Reference manual

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1.0.3 by Luis V. Valcarcel, a month ago

Browse source code at

Authors: 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]

Documentation:   PDF Manual  

GPL-3 license

Imports Matrix, MASS, methods

Suggests cplexAPI, testthat, glmnet, knitr, rmarkdown, ggplot2, ggpubr, dplyr, kableExtra, devtools, BiocStyle, bestsubset

System requirements: IBM ILOG CPLEX (>= 12.1)

See at CRAN