It parses a fitted 'R' model object, and returns a formula in 'Tidy Eval' code that calculates the predictions. It works with several databases back-ends because it leverages 'dplyr' and 'dbplyr' for the final 'SQL' translation of the algorithm. It currently supports lm(), glm(), randomForest(), ranger(), earth(), xgb.Booster.complete(), cubist(), and ctree() models.
Version: 0.5.1 Depends: R (≥ 3.6) Imports: cli, dplyr (≥ 0.7), generics, knitr, purrr, rlang (≥ 1.1.1), tibble, tidyr Suggests: covr, Cubist, DBI, dbplyr, earth (≥ 5.1.2), methods, mlbench, modeldata, nycflights13, parsnip, partykit, randomForest, ranger, rmarkdown, RSQLite, testthat (≥ 3.2.0), xgboost, yaml Published: 2024-12-19 DOI: 10.32614/CRAN.package.tidypredict Author: Emil Hvitfeldt [aut, cre], Edgar Ruiz [aut], Max Kuhn [aut] Maintainer: Emil Hvitfeldt <emil.hvitfeldt at posit.co> BugReports: https://github.com/tidymodels/tidypredict/issues License: MIT + file LICENSE URL: https://tidypredict.tidymodels.org, https://github.com/tidymodels/tidypredict NeedsCompilation: no Materials: README NEWS In views: ModelDeployment CRAN checks: tidypredict results Documentation: Reference manual: tidypredict.pdf Vignettes: Cubist models (source, R code)Please use the canonical form https://CRAN.R-project.org/package=tidypredict to link to this page.
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