Building modeling packages is hard. A large amount of effort generally goes into providing an implementation for a new method that is efficient, fast, and correct, but often less emphasis is put on the user interface. A good interface requires specialized knowledge about S3 methods and formulas, which the average package developer might not have. The goal of 'hardhat' is to reduce the burden around building new modeling packages by providing functionality for preprocessing, predicting, and validating input.
Version: 1.4.1 Depends: R (≥ 3.5.0) Imports: cli (≥ 3.6.0), glue (≥ 1.6.2), rlang (≥ 1.1.0), sparsevctrs (≥ 0.2.0), tibble (≥ 3.2.1), vctrs (≥ 0.6.0) Suggests: covr, crayon, devtools, knitr, Matrix, modeldata (≥ 0.0.2), recipes (≥ 1.0.5), rmarkdown (≥ 2.3), roxygen2, testthat (≥ 3.0.0), usethis (≥ 2.1.5), withr (≥ 3.0.0) Published: 2025-01-31 DOI: 10.32614/CRAN.package.hardhat Author: Hannah Frick [aut, cre], Davis Vaughan [aut], Max Kuhn [aut], Posit Software, PBC [cph, fnd] Maintainer: Hannah Frick <hannah at posit.co> BugReports: https://github.com/tidymodels/hardhat/issues License: MIT + file LICENSE URL: https://github.com/tidymodels/hardhat, https://hardhat.tidymodels.org NeedsCompilation: no Materials: README NEWS CRAN checks: hardhat results Documentation: Downloads: Reverse dependencies: Reverse imports: accept, agua, applicable, baguette, brulee, card, censored, cuda.ml, dann, dials, healthyR.ts, ldmppr, lnmixsurv, modeltime, modeltime.resample, parsnip, probably, recipes, tabnet, themis, tidyclust, tidycmprsk, tidymodels, tune, vetiver, viralmodels, waywiser, workflows, workflowsets, yardstick Reverse suggests: autostats, embed, healthyR.ai, mmrm, orbital, shapr, textrecipes Linking:Please use the canonical form https://CRAN.R-project.org/package=hardhat to link to this page.
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