r descr_models("decision_tree", "C5.0")
defaults <- tibble::tibble(parsnip = c("min_n"), default = c("2L")) param <- decision_tree() %>% set_engine("C5.0") %>% set_mode("classification") %>% make_parameter_list(defaults)
This model has r nrow(param)
tuning parameters:
param$item
decision_tree(min_n = integer()) %>% set_engine("C5.0") %>% set_mode("classification") %>% translate()
[C5.0_train()] is a wrapper around [C50::C5.0()] that makes it easier to run this model.
The "Fitting and Predicting with parsnip" article contains examples for decision_tree()
with the "C5.0"
engine.
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