Tidy tools for quantifying how well model fits to a data set such as confusion matrices, class probability curve summaries, and regression metrics (e.g., RMSE).
| Version: | 0.0.7 |
| Depends: | R (≥ 2.10) |
| Imports: | dplyr (≥ 0.8.5), generics, pROC (≥ 1.15.0), rlang (≥ 0.4.0), tidyselect, utils |
| Suggests: | covr, crayon, ggplot2, kableExtra, knitr, purrr, rmarkdown, testthat, tidyr |
| Published: | 2020-07-13 |
| Author: | Max Kuhn [aut], Davis Vaughan [aut, cre], RStudio [cph] |
| Maintainer: | Davis Vaughan <davis at rstudio.com> |
| BugReports: | https://github.com/tidymodels/yardstick/issues |
| License: | GPL-2 |
| URL: | https://github.com/tidymodels/yardstick, https://yardstick.tidymodels.org |
| NeedsCompilation: | yes |
| Materials: | README NEWS |
| CRAN checks: | yardstick results |
| Reference manual: | yardstick.pdf |
| Vignettes: |
Custom metrics Metric types Multiclass averaging |
| Package source: | yardstick_0.0.7.tar.gz |
| Windows binaries: | r-devel: yardstick_0.0.7.zip, r-release: yardstick_0.0.7.zip, r-oldrel: yardstick_0.0.7.zip |
| macOS binaries: | r-release: yardstick_0.0.7.tgz, r-oldrel: yardstick_0.0.7.tgz |
| Old sources: | yardstick archive |
| Reverse imports: | diceR, finetune, modeltime, modeltime.ensemble, modeltime.resample, probably, stacks, text, tidymodels, treeheatr, trendeval, tune |
| Reverse suggests: | baguette, garma, timetk |
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