Package: BOSO 1.0.4

Luis V. Valcarcel

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>.

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]

BOSO_1.0.4.tar.gz
BOSO_1.0.4.zip(r-4.5)BOSO_1.0.4.zip(r-4.4)BOSO_1.0.4.zip(r-4.3)
BOSO_1.0.4.tgz(r-4.4-any)BOSO_1.0.4.tgz(r-4.3-any)
BOSO_1.0.4.tar.gz(r-4.5-noble)BOSO_1.0.4.tar.gz(r-4.4-noble)
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BOSO.pdf |BOSO.html✨
BOSO/json (API)
NEWS

Peer review:

Bug tracker:https://github.com/lvalcarcel/boso/issues

On CRAN:

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6 exports 5 stars 0.82 score 3 dependencies 13 scripts 342 downloads

Last updated 29 days agofrom:72dfc71e97 (on package/BOSO). Checks:ERROR: 1 NOTE: 6. Indexed: no.

Exports:BOSOBOSO.multiple.coldstartBOSO.multiple.warmstartBOSO.singlecoef.BOSOpredict.BOSO

Dependencies:latticeMASSMatrix