mvs
Methods for High-Dimensional Multi-View Learning
Methods for high-dimensional multi-view learning based on the multi-view stacking (MVS) framework. For technical details on the MVS and stacked penalized logistic regression (StaPLR) methods see Van Loon, Fokkema, Szabo, & De Rooij (2020) <doi:10.1016/j.inffus.2020.03.007> and Van Loon et al. (2022) <doi:10.3389/fnins.2022.830630>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
2.1.0 |
rolling linux/jammy R-4.5 | mvs_2.1.0.tar.gz |
1.9 MiB |
2.1.0 |
rolling linux/noble R-4.5 | mvs_2.1.0.tar.gz |
1.9 MiB |
2.1.0 |
rolling source/ R- | mvs_2.1.0.tar.gz |
3.7 MiB |
2.1.0 |
latest linux/jammy R-4.5 | mvs_2.1.0.tar.gz |
1.9 MiB |
2.1.0 |
latest linux/noble R-4.5 | mvs_2.1.0.tar.gz |
1.9 MiB |
2.1.0 |
latest source/ R- | mvs_2.1.0.tar.gz |
3.7 MiB |
2.1.0 |
2026-04-26 source/ R- | mvs_2.1.0.tar.gz |
3.7 MiB |
2.1.0 |
2026-04-23 source/ R- | mvs_2.1.0.tar.gz |
3.7 MiB |
2.1.0 |
2026-04-09 windows/windows R-4.5 | mvs_2.1.0.zip |
1.9 MiB |
2.1.0 |
2025-04-20 source/ R- | mvs_2.1.0.tar.gz |
3.7 MiB |