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: | 0.4.6 |
| Depends: | R (≥ 3.1) |
| Imports: | dplyr (≥ 0.7), rlang, purrr, knitr, generics, tibble |
| Suggests: | dbplyr, testthat (≥ 2.1.0), randomForest, ranger, earth, rmarkdown, nycflights13, RSQLite, methods, DBI, covr, xgboost, Cubist, mlbench, partykit, yaml, parsnip |
| Published: | 2020-07-23 |
| Author: | Max Kuhn [aut, cre] |
| Maintainer: | Max Kuhn <max at rstudio.com> |
| BugReports: | https://github.com/tidymodels/tidypredict/issues |
| License: | GPL-3 |
| URL: | https://tidypredict.tidymodels.org, https://github.com/tidymodels/tidypredict |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| In views: | ModelDeployment |
| CRAN checks: | tidypredict results |
| Reference manual: | tidypredict.pdf |
| Vignettes: |
cubist glm lm mars non-r ranger regression rf save randomForest tree xgboost |
| Package source: | tidypredict_0.4.6.tar.gz |
| Windows binaries: | r-devel: tidypredict_0.4.6.zip, r-release: tidypredict_0.4.6.zip, r-oldrel: tidypredict_0.4.6.zip |
| macOS binaries: | r-release: tidypredict_0.4.6.tgz, r-oldrel: tidypredict_0.4.6.tgz |
| Old sources: | tidypredict archive |
| Reverse imports: | modeldb |
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