r descr_models("C5_rules", "C5.0")

Tuning Parameters

defaults <- 
  tibble::tibble(parsnip = c("trees", "min_n"),
                 default = c("1L",       "2L"))

param <-
  C5_rules() %>% 
  set_engine("C5.0") %>% 
  tunable() %>% 
  dplyr::select(-source, -component, -component_id, parsnip = name) %>% 
  dplyr::mutate(
    dials = purrr::map(call_info, get_dials),
    label = purrr::map_chr(dials, ~ .x$label),
    type = purrr::map_chr(dials, ~ .x$type)
  ) %>% 
  dplyr::full_join(defaults, by = "parsnip") %>% 
  mutate(
    item = 
      glue::glue("- `{parsnip}`: {label} (type: {type}, default: {default})\n\n")
  )

This model has r nrow(param) tuning parameters:

param$item

Note that C5.0 has a tool for early stopping during boosting where less iterations of boosting are performed than the number requested. C5_rules() turns this feature off (although it can be re-enabled using [C50::C5.0Control()]).

Translation from parsnip to the underlying model call (regression)

C5_rules(
  trees = integer(1),
  min_n = integer(1)
) %>%
  set_engine("C5.0") %>%
  set_mode("classification") %>%
  translate()

Preprocessing requirements


References



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rules documentation built on Aug. 8, 2021, 1:06 a.m.