workflows: Modeling Workflows

Managing both a 'parsnip' model and a preprocessor, such as a model formula or recipe from 'recipes', can often be challenging. The goal of 'workflows' is to streamline this process by bundling the model alongside the preprocessor, all within the same object.

Version: 1.1.4
Depends: R (≥ 3.6)
Imports: cli (≥ 3.3.0), generics (≥ 0.1.2), glue (≥ 1.6.2), hardhat (≥ 1.2.0), lifecycle (≥ 1.0.3), modelenv (≥ 0.1.0), parsnip (≥ 1.2.0), rlang (≥ 1.0.3), tidyselect (≥ 1.2.0), vctrs (≥ 0.4.1)
Suggests: butcher (≥ 0.2.0), covr, dials (≥ 1.0.0), knitr, magrittr, modeldata (≥ 1.0.0), recipes (≥ 1.0.0), rmarkdown, testthat (≥ 3.0.0)
Published: 2024-02-19
Author: Davis Vaughan [aut], Simon Couch ORCID iD [aut, cre], Posit Software, PBC [cph, fnd]
Maintainer: Simon Couch <simon.couch at posit.co>
BugReports: https://github.com/tidymodels/workflows/issues
License: MIT + file LICENSE
URL: https://github.com/tidymodels/workflows, https://workflows.tidymodels.org
NeedsCompilation: no
Materials: README NEWS
CRAN checks: workflows results

Documentation:

Reference manual: workflows.pdf
Vignettes: Workflow Stages

Downloads:

Package source: workflows_1.1.4.tar.gz
Windows binaries: r-devel: workflows_1.1.4.zip, r-release: workflows_1.1.4.zip, r-oldrel: workflows_1.1.4.zip
macOS binaries: r-release (arm64): workflows_1.1.4.tgz, r-oldrel (arm64): workflows_1.1.4.tgz, r-release (x86_64): workflows_1.1.4.tgz
Old sources: workflows archive

Reverse dependencies:

Reverse imports: agua, finetune, finnts, healthyR.ai, MLDataR, modeltime, modeltime.ensemble, modeltime.resample, probably, stacks, text, tidyAML, tidymodels, tidysdm, tune, viraldomain, viralmodels, viralx, viruslearner, workflowsets
Reverse suggests: additive, bayesian, bundle, coefplot, easyalluvial, gtsummary, healthyR.ts, marginaleffects, nestedmodels, offsetreg, recipes, tabnet, tidyclust, tidydann, timetk, vetiver
Reverse enhances: vip

Linking:

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