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: | 1.0.2 |
Depends: | R (≥ 3.5) |
Imports: | broom (≥ 0.5.5), checkmate (≥ 2.0.0), data.table (≥ 1.12), dplyr (≥ 0.8.5), ggplot2, lifecycle, lme4 (≥ 1.1-23), MuMIn (≥ 1.43.15), plyr, pROC (≥ 1.16.0), purrr, recipes (≥ 0.1.10), rlang (≥ 0.4.0), stats, stringr, tibble (≥ 2.1.1), tidyr (≥ 1.0.2), utils |
Suggests: | AUC, covr (≥ 3.3.1), e1071 (≥ 1.7-2), furrr, ggimage (≥ 0.2.7), groupdata2 (≥ 1.2.0), knitr, nnet (≥ 7.3-12), randomForest (≥ 4.6-14), rmarkdown, rsvg, testthat (≥ 2.3.2), xpectr (≥ 0.3.0) |
Published: | 2020-05-29 |
Author: | Ludvig Renbo Olsen [aut, cre], Benjamin Hugh Zachariae [aut] |
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 |
Reference manual: | cvms.pdf |
Vignettes: |
available_metrics creating_confusion_matrix cross_validating_custom evaluate_by_id |
Package source: | cvms_1.0.2.tar.gz |
Windows binaries: | r-devel: cvms_1.0.2.zip, r-release: cvms_1.0.2.zip, r-oldrel: cvms_1.0.2.zip |
macOS binaries: | r-release: cvms_1.0.2.tgz, r-oldrel: cvms_1.0.2.tgz |
Old sources: | cvms archive |
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