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discrim_flexible() defines a model that fits a discriminant analysis model that can use nonlinear features created using multivariate adaptive regression splines (MARS). This function can fit classification models.

There are different ways to fit this model, and the method of estimation is chosen by setting the model engine. The engine-specific pages for this model are listed below.

¹ The default engine. ² Requires a parsnip extension package.

More information on how parsnip is used for modeling is at https://www.tidymodels.org/.

Usage

discrim_flexible(
  mode = "classification",
  num_terms = NULL,
  prod_degree = NULL,
  prune_method = NULL,
  engine = "earth"
)

Arguments

mode

A single character string for the prediction outcome mode. Possible values for this model are "unknown", "regression", or "classification".

num_terms

The number of features that will be retained in the final model, including the intercept.

prod_degree

The highest possible interaction degree.

prune_method

The pruning method.

engine

A single character string specifying what computational engine to use for fitting.

Details

This function only defines what type of model is being fit. Once an engine is specified, the method to fit the model is also defined. See set_engine() for more on setting the engine, including how to set engine arguments.

The model is not trained or fit until the fit() function is used with the data.