r descr_models("multinom_reg", "glmnet")

Tuning Parameters

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

param <-
multinom_reg() %>% 
  set_engine("glmnet") %>% 
  make_parameter_list(defaults)

This model has r nrow(param) tuning parameters:

param$item

The penalty parameter has no default and requires a single numeric value. For more details about this, and the glmnet model in general, see [glmnet-details]. As for mixture:

Translation from parsnip to the original package

multinom_reg(penalty = double(1), mixture = double(1)) %>% 
  set_engine("glmnet") %>% 
  translate()

Preprocessing requirements



By default, [glmnet::glmnet()] uses the argument standardize = TRUE to center and scale the data.

Examples

The "Fitting and Predicting with parsnip" article contains examples for multinom_reg() with the "glmnet" engine.

Case weights


Saving fitted model objects


References



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