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() and randomForest() models.
Version: | 0.1.0 |
Depends: | R (≥ 3.1), dplyr (≥ 0.7), rlang, purrr, tibble, tidyr |
Suggests: | dbplyr, testthat, randomForest, knitr, rmarkdown, nycflights13, RSQLite, methods, DBI |
Published: | 2018-01-17 |
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 |
CRAN checks: | tidypredict results |
Reference manual: | tidypredict.pdf |
Vignettes: |
lm lm randomForest randomForest |
Package source: | tidypredict_0.1.0.tar.gz |
Windows binaries: | r-devel: tidypredict_0.1.0.zip, r-release: tidypredict_0.1.0.zip, r-oldrel: tidypredict_0.1.0.zip |
OS X El Capitan binaries: | r-release: tidypredict_0.1.0.tgz |
OS X Mavericks binaries: | r-oldrel: not available |
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