In parsnip: A Common API to Modeling and Analysis Functions

#| child: aaa.Rmd
#| include: false

r descr_models("multinom_reg", "keras")

Tuning Parameters

#| label: keras-param-info
#| echo: false
defaults <- 
  tibble::tibble(parsnip = c("penalty"),
                 default = c("0.0"))

param <-
  multinom_reg() |> 
  set_engine("keras") |> 
  make_parameter_list(defaults)

This model has one tuning parameter:

#| label: keras-param-list
#| echo: false
#| results: asis
param$item

For penalty, the amount of regularization is only L2 penalty (i.e., ridge or weight decay).

Translation from parsnip to the original package

#| label: keras-csl
multinom_reg(penalty = double(1)) |> 
  set_engine("keras") |> 
  translate()

[keras_mlp()] is a parsnip wrapper around keras code for neural networks. This model fits a linear regression as a network with a single hidden unit.

Preprocessing requirements

#| child: template-makes-dummies.Rmd

#| child: template-same-scale.Rmd

Case weights

#| child: template-no-case-weights.Rmd

Saving fitted model objects

#| child: template-bundle.Rmd

Examples

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

References

• Hoerl, A., & Kennard, R. (2000). Ridge Regression: Biased Estimation for Nonorthogonal Problems. Technometrics, 42(1), 80-86.

parsnip documentation built on June 8, 2025, 12:10 p.m.