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() and ranger() models.
| Version: | 0.2.0 |
| Depends: | R (≥ 3.1) |
| Imports: | dplyr (≥ 0.7), rlang, purrr, tibble, tidyr |
| Suggests: | dbplyr, testthat, randomForest, ranger, knitr, rmarkdown, nycflights13, RSQLite, methods, DBI |
| Published: | 2018-02-25 |
| Author: | Edgar Ruiz [aut, cre] |
| Maintainer: | Edgar Ruiz <edgar at rstudio.com> |
| BugReports: | https://github.com/edgararuiz/tidypredict/issues |
| License: | GPL-3 |
| URL: | http://tidypredict.netlify.com/ |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| In views: | ModelDeployment |
| CRAN checks: | tidypredict results |
| Reference manual: | tidypredict.pdf |
| Vignettes: |
lm lm randomForest randomForest randomForest |
| Package source: | tidypredict_0.2.0.tar.gz |
| Windows binaries: | r-devel: tidypredict_0.2.0.zip, r-release: tidypredict_0.2.0.zip, r-oldrel: tidypredict_0.2.0.zip |
| OS X binaries: | r-release: tidypredict_0.2.0.tgz, r-oldrel: tidypredict_0.2.0.tgz |
| Old sources: | tidypredict archive |
| Reverse suggests: | modeldb |
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