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.
|Author||Edgar Ruiz [aut, cre]|
|Maintainer||Edgar Ruiz <[email protected]>|
|Package repository||View on CRAN|
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