Continuous Optimisation Towards Best Subset Selection

Best subset selection in generalised linear models via continuous optimisation. Reformulates the NP-hard discrete subset selection problem as a continuous optimisation over the hypercube [0,1]^p, solved via a Frank-Wolfe homotopy algorithm with closed-form ridge inner solves. Supports linear (Gaussian), binary logistic, and multinomial regression. For methodological details see Moka, Liquet, Zhu and Muller (2024) and Mathur, Liquet, Muller and Moka (2026) .


Reference manual

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install.packages("combss")

0.1.0 by Benoit Liquet, 5 months ago


https://github.com/benoit-liquet/combss


Browse source code at https://github.com/cran/combss


Authors: Benoit Liquet [aut, cre] (ORCID: , Anant Mathur [aut] , Sarat Moka [aut]


Documentation:   PDF Manual  


GPL-3 license


Imports glmnet, stats

Suggests testthat, knitr, rmarkdown


See at CRAN