Run predictions inside the database.
tidypredict 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
dbplyr for the final SQL translation of the algorithm. It currently supports
tidypredict from CRAN using:
Or install the development version using
devtools as follows:
tidypredict is able to parse an R model object, such as:
model <- lm(mpg ~ wt + cyl, data = mtcars)
And then creates the SQL statement needed to calculate the fitted prediction:
## <SQL> ((39.6862614802529) + ((`wt`) * (-3.19097213898374))) + ((`cyl`) * (-1.5077949682598))
The following R models are currently supported. For more info please review the corresponding vignette: