cvms: Cross-Validation for Model Selection (original) (raw)

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).

Version: 1.6.2
Depends: R (≥ 3.5)
Imports: checkmate (≥ 2.0.0), data.table (≥ 1.12), dplyr (≥ 0.8.5), ggplot2, groupdata2 (≥ 2.0.2), lifecycle, lme4 (≥ 1.1-23), MuMIn (≥ 1.43.17), parameters (≥ 0.15.0), plyr, pROC (≥ 1.16.0), purrr, rearrr (≥ 0.3.0), recipes (≥ 0.1.13), rlang (≥ 0.4.7), stats, stringr, tibble (≥ 3.0.3), tidyr (≥ 1.1.2), utils
Suggests: AUC, covr (≥ 3.3.1), e1071 (≥ 1.7-2), furrr, ggimage (≥ 0.3.3), ggnewscale (≥ 0.5.0), knitr, merDeriv (≥ 0.2-4), nnet (≥ 7.3-12), randomForest (≥ 4.6-14), rmarkdown, rsvg, testthat (≥ 2.3.2), xpectr (≥ 0.4.1)
Published: 2024-07-31
DOI: 10.32614/CRAN.package.cvms
Author: Ludvig Renbo OlsenORCID iD [aut, cre] (@ludvigolsen), Hugh Benjamin Zachariae [aut], Indrajeet Patil ORCID iD [ctb] (@patilindrajeets), Daniel Lüdecke ORCID iD [ctb]
Maintainer: Ludvig Renbo Olsen
BugReports: https://github.com/ludvigolsen/cvms/issues
License: MIT + file
URL: https://github.com/ludvigolsen/cvms
NeedsCompilation: no
Materials: README NEWS
CRAN checks: cvms results

Documentation:

Downloads:

Reverse dependencies:

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=cvmsto link to this page.