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(), earth(), xgb.Booster.complete(), cubist(), and ctree() models.
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curl https://depscope.dev/api/check/conda/r-tidypredictFirst published · 2020-07-23 15:02:35.079000+00:00
Last updated · 2026-02-27 08:40:07.027000+00:00