probably: Tools for Post-Processing Predicted Values
Models can be improved by post-processing class
probabilities, by: recalibration, conversion to hard probabilities,
assessment of equivocal zones, and other activities. 'probably'
contains tools for conducting these operations as well as calibration
tools and conformal inference techniques for regression models.
Version: |
1.0.3 |
Depends: |
R (≥ 3.6) |
Imports: |
butcher, cli, dplyr (≥ 1.1.0), furrr, generics (≥ 0.1.3), ggplot2, hardhat, pillar, purrr, rlang (≥ 1.0.4), tidyr (≥
1.3.0), tidyselect (≥ 1.1.2), tune (≥ 1.1.2), vctrs (≥
0.4.1), withr, workflows (≥ 1.1.4), yardstick (≥ 1.3.0) |
Suggests: |
betacal, covr, knitr, MASS, mgcv, modeldata (≥ 1.1.0), nnet, parsnip (≥ 1.2.0), quantregForest, randomForest, recipes, rmarkdown, rsample, testthat (≥ 3.0.0) |
Published: |
2024-02-23 |
DOI: |
10.32614/CRAN.package.probably |
Author: |
Max Kuhn [aut, cre],
Davis Vaughan [aut],
Edgar Ruiz [aut],
Posit Software, PBC [cph, fnd] |
Maintainer: |
Max Kuhn <max at posit.co> |
BugReports: |
https://github.com/tidymodels/probably/issues |
License: |
MIT + file LICENSE |
URL: |
https://github.com/tidymodels/probably,
https://probably.tidymodels.org |
NeedsCompilation: |
no |
Materials: |
README NEWS |
CRAN checks: |
probably results |
Documentation:
Downloads:
Reverse dependencies:
Linking:
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https://CRAN.R-project.org/package=probably
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