cvms
Cross-Validation for Model Selection
Cross-validate one or multiple regression and classification models and get relevant evaluation metrics in a tidy format. Validate the best model on a test set and compare it to a baseline evaluation. Alternatively, evaluate predictions from an external model. Currently supports regression and classification (binary and multiclass). Described in chp. 5 of Jeyaraman, B. P., Olsen, L. R., & Wambugu M. (2019, ISBN: 9781838550134).
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
2.0.0 |
rolling linux/jammy R-4.5 | cvms_2.0.0.tar.gz |
3.5 MiB |
2.0.0 |
rolling linux/noble R-4.5 | cvms_2.0.0.tar.gz |
3.5 MiB |
2.0.0 |
rolling source/ R- | cvms_2.0.0.tar.gz |
4.9 MiB |
2.0.0 |
latest linux/jammy R-4.5 | cvms_2.0.0.tar.gz |
3.5 MiB |
2.0.0 |
latest linux/noble R-4.5 | cvms_2.0.0.tar.gz |
3.5 MiB |
2.0.0 |
latest source/ R- | cvms_2.0.0.tar.gz |
4.9 MiB |
2.0.0 |
2026-04-26 source/ R- | cvms_2.0.0.tar.gz |
4.9 MiB |
2.0.0 |
2026-04-23 source/ R- | cvms_2.0.0.tar.gz |
4.9 MiB |
2.0.0 |
2026-04-09 windows/windows R-4.5 | cvms_2.0.0.zip |
3.5 MiB |
1.7.0 |
2025-04-20 source/ R- | cvms_1.7.0.tar.gz |
4.9 MiB |