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author | Peter Lo <peterloleungyau@gmail.com> | 2020-06-29 13:50:35 +0800 |
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committer | Ricardo Wurmus <rekado@elephly.net> | 2020-09-11 18:29:48 +0200 |
commit | 156c558866e28834df545f66291112341e240c92 (patch) | |
tree | abab2ca471398d66c676a0cf857a264f59d56539 /gnu/packages | |
parent | 3dbe8a57ec4967f1719a5a3a4cecee7c863d420d (diff) | |
download | guix-patches-156c558866e28834df545f66291112341e240c92.tar guix-patches-156c558866e28834df545f66291112341e240c92.tar.gz |
gnu: Add r-tidypredict.
* gnu/packages/cran.scm (r-tidypredict): New variable.
Signed-off-by: Ricardo Wurmus <rekado@elephly.net>
Diffstat (limited to 'gnu/packages')
-rw-r--r-- | gnu/packages/cran.scm | 33 |
1 files changed, 33 insertions, 0 deletions
diff --git a/gnu/packages/cran.scm b/gnu/packages/cran.scm index 3f61763f0e..90ce8525d5 100644 --- a/gnu/packages/cran.scm +++ b/gnu/packages/cran.scm @@ -23899,3 +23899,36 @@ the @dfn{root mean squared error} (RMSE) using 10-fold cross-validation, there are 10 paired statistics. These can be used to make comparisons between models without involving a test set.") (license license:gpl2))) + +(define-public r-tidypredict + (package + (name "r-tidypredict") + (version "0.4.5") + (source + (origin + (method url-fetch) + (uri (cran-uri "tidypredict" version)) + (sha256 + (base32 + "1i6zl6wjz6wbpkmkc9z9ikp8zgck3qh38lar0r6q2jzl8fxpimg4")))) + (properties `((upstream-name . "tidypredict"))) + (build-system r-build-system) + (propagated-inputs + `(("r-dplyr" ,r-dplyr) + ("r-generics" ,r-generics) + ("r-knitr" ,r-knitr) + ("r-purrr" ,r-purrr) + ("r-rlang" ,r-rlang) + ("r-tibble" ,r-tibble))) + (native-inputs + `(("r-knitr" ,r-knitr))) + (home-page "https://tidypredict.tidymodels.org") + (synopsis "Run predictions inside the database") + (description + "This package parses a fitted R model object, and returns a formula in +Tidy Eval code that calculates the predictions. It works with several +database backends because it leverages @code{dplyr} and @code{dbplyr} for the +final SQL translation of the algorithm. It currently supports @code{lm()}, +@code{glm()}, @code{randomForest()}, @code{ranger()}, @code{earth()}, +@code{xgb.Booster.complete()}, @code{cubist()}, and @code{ctree()} models.") + (license license:gpl3))) |