combss
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) <doi:10.1007/s11222-024-10387-8> and Mathur, Liquet, Muller and Moka (2026) <doi:10.48550/arXiv.2603.21952>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | combss_0.1.0.tar.gz |
74.7 KiB |
0.1.0 |
rolling linux/noble R-4.5 | combss_0.1.0.tar.gz |
74.6 KiB |
0.1.0 |
rolling source/ R- | combss_0.1.0.tar.gz |
37.1 KiB |
0.1.0 |
latest linux/jammy R-4.5 | combss_0.1.0.tar.gz |
74.7 KiB |
0.1.0 |
latest linux/noble R-4.5 | combss_0.1.0.tar.gz |
74.6 KiB |
0.1.0 |
latest source/ R- | combss_0.1.0.tar.gz |
37.1 KiB |
0.1.0 |
2026-04-23 source/ R- | combss_0.1.0.tar.gz |
0 B |