In parsnip: A Common API to Modeling and Analysis Functions

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

Tuning Parameters

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

param <-
 bag_tree() %>% 
  set_engine("C5.0") %>% 
  set_mode("classification") %>% 
  make_parameter_list(defaults)

This model has r nrow(param) tuning parameters:

param$item

Translation from parsnip to the original package (classification)

r uses_extension("bag_tree", "C5.0", "classification")

library(baguette)

bag_tree(min_n = integer()) %>% 
  set_engine("C5.0") %>% 
  set_mode("classification") %>% 
  translate()

Preprocessing requirements

Case weights

References

• Breiman, L. 1996. "Bagging predictors". Machine Learning. 24 (2): 123-140

• Kuhn, M, and K Johnson. 2013. Applied Predictive Modeling. Springer.

parsnip documentation built on Aug. 18, 2023, 1:07 a.m.