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).

Version: 1.3.3
Depends: R (≥ 3.5)
Imports: checkmate (≥ 2.0.0), data.table (≥ 1.12), dplyr (≥ 0.8.5), ggplot2, 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 (≥ 0.2.8), ggnewscale (≥ 0.4.3), groupdata2 (≥ 1.4.1), knitr, nnet (≥ 7.3-12), randomForest (≥ 4.6-14), rmarkdown, rsvg, testthat (≥ 2.3.2), xpectr (≥ 0.4.1)
Published: 2021-11-14
Author: Ludvig Renbo Olsen [aut, cre], Hugh Benjamin Zachariae [aut], Indrajeet Patil ORCID iD [ctb] (@patilindrajeets)
Maintainer: Ludvig Renbo Olsen <r-pkgs at ludvigolsen.dk>
BugReports: https://github.com/ludvigolsen/cvms/issues
License: MIT + file LICENSE
URL: https://github.com/ludvigolsen/cvms
NeedsCompilation: no
Materials: README NEWS
CRAN checks: cvms results

Documentation:

Reference manual: cvms.pdf
Vignettes: creating_confusion_matrix
available_metrics
cross_validating_custom_functions
evaluate_by_id
picking_the_number_of_folds_for_cross-validation

Downloads:

Package source: cvms_1.3.3.tar.gz
Windows binaries: r-devel: cvms_1.3.3.zip, r-release: cvms_1.3.3.zip, r-oldrel: cvms_1.3.3.zip
macOS binaries: r-release (arm64): cvms_1.3.3.tgz, r-release (x86_64): cvms_1.3.3.tgz, r-oldrel: cvms_1.3.3.tgz
Old sources: cvms archive

Linking:

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