Designed to assist novice to intermediate analysts in choosing an optimal classification model, particularly for working with relatively small data sets. It provides cross-validated results comparing several different models at once using a consistent set of performance metrics, so users can hone in on the most promising approach rather than attempting single model fittings at a time. The package predefined 12 most common classification models, although users are free to select from the 200+ other options available in caret package.
| Version: | 0.1.3 |
| Imports: | mlbench, e1071, purrr, magrittr, ggplot2, ModelMetrics, dplyr, stringr, gridExtra, tibble, psych, utils, knitr, caret |
| Suggests: | testthat |
| Published: | 2017-04-11 |
| Author: | Younggun You [cre], Eric Stickney [aut] |
| Maintainer: | Younggun You <younggun at stanford.edu> |
| License: | CC0 |
| NeedsCompilation: | no |
| CRAN checks: | modeval results |
| Reference manual: | modeval.pdf |
| Vignettes: |
An introduction to the modeval package |
| Package source: | modeval_0.1.3.tar.gz |
| Windows binaries: | r-devel: modeval_0.1.3.zip, r-release: modeval_0.1.3.zip, r-oldrel: modeval_0.1.3.zip |
| OS X El Capitan binaries: | r-release: modeval_0.1.3.tgz |
| OS X Mavericks binaries: | r-oldrel: modeval_0.1.3.tgz |
| Old sources: | modeval archive |
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