random forest takes too long

[EmilHvitfeldt]

parsing, most likely in {tidypredict} take a LONG time for random forest models. A single tree takes me over 45 seconds and allocates a lot of memory, i'm confident we can make some improvements.

library(tidymodels)
library(orbital)

rec_spec <- recipe(Sale_Price ~ ., data = ames) |>
  step_normalize(all_numeric_predictors()) |>
  step_dummy(all_nominal_predictors())

mod_spec <- rand_forest("regression", trees = 1)

wf_spec <- workflow(rec_spec, mod_spec)

wf_fit <- fit(wf_spec, ames)

wf_fit

tictoc::tic()
orb <- orbital(wf_fit)
tictoc::toc()
48.52 sec elapsed