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: | 0.3.2 |
| Depends: | R (≥ 3.5) |
| Imports: | data.table (≥ 1.12), dplyr, plyr, tidyr (≥ 0.8.3), ggplot2, purrr, tibble (≥ 2.1.1), caret (≥ 6.0-84), pROC (≥ 1.14.0), stats, lme4 (≥ 1.1-21), MuMIn (≥ 1.43.6), broom (≥ 0.5.2), stringr, mltools (≥ 0.3.5), rlang, utils, lifecycle |
| Suggests: | knitr, groupdata2 (≥ 1.1.2), e1071 (≥ 1.7-2), rmarkdown, testthat (≥ 2.2.1), AUC, furrr, ModelMetrics (≥ 1.2.2), covr (≥ 3.3.1), nnet (≥ 7.3-12), randomForest (≥ 4.6-14) |
| Published: | 2019-12-01 |
| 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: |
Introduction_to_cvms |
| Package source: | cvms_0.3.2.tar.gz |
| Windows binaries: | r-devel: cvms_0.3.2.zip, r-devel-gcc8: cvms_0.3.2.zip, r-release: cvms_0.3.2.zip, r-oldrel: cvms_0.3.2.zip |
| OS X binaries: | r-release: cvms_0.3.2.tgz, r-oldrel: cvms_0.3.2.tgz |
| Old sources: | cvms archive |
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