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(), ranger() and earth() models.
person("Edgar", "Ruiz", email = "edgar@rstudio.com", role = c("aut", "cre"))
dbplyr, testthat, randomForest, ranger, earth, rmarkdown,
nycflights13, RSQLite, methods, DBI, covr