In parsnip: A Common API to Modeling and Analysis Functions

r descr_models("discrim_flexible", "earth")

Tuning Parameters

defaults <- 
  tibble::tibble(parsnip = c("num_terms", "prod_degree", "prune_method"),
                 default = c("(see below)", "1L", "'backward'"))

param <-
  discrim_flexible() %>% 
  set_engine("earth") %>% 
  make_parameter_list(defaults)

This model has r nrow(param) tuning parameter:

param$item

The default value of num_terms depends on the number of columns (p): min(200, max(20, 2 * p)) + 1. Note that num_terms = 1 is an intercept-only model.

Translation from parsnip to the original package

r uses_extension("discrim_flexible", "earth", "classification")

library(discrim)

discrim_flexible(
  num_terms = integer(0),
  prod_degree = integer(0),
  prune_method = character(0)
) %>% 
  translate()

Preprocessing requirements

Case weights

References

• Hastie, Tibshirani & Buja (1994) Flexible Discriminant Analysis by Optimal Scoring, Journal of the American Statistical Association, 89:428, 1255-1270

• Friedman (1991). Multivariate Adaptive Regression Splines. The Annals of Statistics, 19(1), 1-67.

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