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: | 1.0.1 |
| Depends: | R (≥ 3.6) |
| Imports: | cli,dplyr (≥ 0.7),generics,jsonlite,knitr,purrr,rlang (≥ 1.1.1),tibble,tidyr |
| Suggests: | covr,Cubist (≥ 0.5.1),DBI,dbplyr,earth (≥ 5.1.2),glmnet, methods,mlbench,modeldata,nycflights13,parsnip,partykit,randomForest,ranger,rmarkdown,RSQLite,testthat (≥ 3.2.0),xgboost,yaml |
| Published: | 2025-12-13 |
| 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 + fileLICENSE |
| URL: | https://tidypredict.tidymodels.org,https://github.com/tidymodels/tidypredict |
| NeedsCompilation: | no |
| Materials: | README,NEWS |
| In views: | ModelDeployment |
| CRAN checks: | tidypredict results |