yardstick: Tidy Characterizations of Model Performance

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: 0.0.8
Depends: R (≥ 2.10)
Imports: dplyr (≥ 0.8.5), generics, pROC (≥ 1.15.0), rlang (≥ 0.4.0), tidyselect, utils, vctrs (≥ 0.3.6)
Suggests: covr, crayon, ggplot2, knitr, probably (≥ 0.0.6), purrr, rmarkdown, testthat (≥ 3.0.0), tidyr
Published: 2021-03-28
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: MIT + file LICENSE
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_0.0.8.tar.gz
Windows binaries: r-devel: yardstick_0.0.8.zip, r-devel-UCRT: yardstick_0.0.8.zip, r-release: yardstick_0.0.8.zip, r-oldrel: yardstick_0.0.8.zip
macOS binaries: r-release (arm64): yardstick_0.0.8.tgz, r-release (x86_64): yardstick_0.0.8.tgz, r-oldrel: yardstick_0.0.8.tgz
Old sources: yardstick archive

Reverse dependencies:

Reverse imports: autostats, diceR, finetune, forestecology, modeltime, modeltime.ensemble, modeltime.resample, probably, stacks, text, tidymodels, treeheatr, trendeval, tune
Reverse suggests: baguette, garma, sknifedatar, spatialsample, tidyposterior, timetk, workflowsets


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