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: 1.2.0
Depends: R (≥ 3.4.0)
Imports: cli, dplyr (≥ 1.1.0), generics (≥ 0.1.2), hardhat (≥ 1.3.0), lifecycle (≥ 1.0.3), rlang (≥ 1.0.6), tibble, tidyselect (≥ 1.2.0), utils, vctrs (≥ 0.5.0)
Suggests: covr, crayon, ggplot2, knitr, probably (≥ 0.0.6), rmarkdown, survival (≥ 3.5-0), testthat (≥ 3.0.0), tidyr
Published: 2023-04-21
Author: Max Kuhn [aut], Davis Vaughan [aut], Emil Hvitfeldt ORCID iD [aut, cre], Posit Software, PBC [cph, fnd]
Maintainer: Emil Hvitfeldt <emil.hvitfeldt at posit.co>
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: Metric types
Multiclass averaging


Package source: yardstick_1.2.0.tar.gz
Windows binaries: r-devel: yardstick_1.2.0.zip, r-release: yardstick_1.2.0.zip, r-oldrel: yardstick_1.2.0.zip
macOS binaries: r-release (arm64): yardstick_1.2.0.tgz, r-oldrel (arm64): yardstick_1.2.0.tgz, r-release (x86_64): yardstick_1.2.0.tgz, r-oldrel (x86_64): yardstick_1.2.0.tgz
Old sources: yardstick archive

Reverse dependencies:

Reverse imports: adjROC, diceR, finnts, forestecology, healthyR.ai, matric, modeltime, modeltime.ensemble, modeltime.resample, probably, shinymodels, stacks, text, tidyfit, tidymodels, treeheatr, trendeval, tune, vip, waywiser
Reverse suggests: baguette, brulee, EZtune, FCPS, finetune, garma, spatialsample, tabnet, tidydann, tidyposterior, timetk, vetiver, workflowsets


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