In parsnip: A Common API to Modeling and Analysis Functions

r descr_models("discrim_linear", "mda")

Tuning Parameters

defaults <- 
  tibble::tibble(parsnip = c("penalty"),
                 default = c("1.0"))

param <-
  discrim_linear() %>% 
  set_engine("mda") %>% 
  make_parameter_list(defaults)

This model has r nrow(param) tuning parameter:

param$item

Translation from parsnip to the original package

r uses_extension("discrim_linear", "mda", "classification")

library(discrim)

discrim_linear(penalty = numeric(0)) %>% 
  set_engine("mda") %>% 
  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