discrim_flexible.Rd

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/discrim_flexible.R
\name{discrim_flexible}
\alias{discrim_flexible}
\title{Flexible discriminant analysis}
\usage{
discrim_flexible(
  mode = "classification",
  num_terms = NULL,
  prod_degree = NULL,
  prune_method = NULL,
  engine = "earth"
)
}
\arguments{
\item{mode}{A single character string for the prediction outcome mode.
Possible values for this model are "unknown", "regression", or
"classification".}

\item{num_terms}{The number of features that will be retained in the
final model, including the intercept.}

\item{prod_degree}{The highest possible interaction degree.}

\item{prune_method}{The pruning method.}

\item{engine}{A single character string specifying what computational engine
to use for fitting.}
}
\description{
\code{discrim_flexible()} defines a model that fits a discriminant analysis model
that can use nonlinear features created using multivariate adaptive
regression splines (MARS).

There are different ways to fit this model. The method of estimation is
chosen by setting the model \emph{engine}.

\Sexpr[stage=render,results=rd]{parsnip:::make_engine_list("discrim_flexible")}

More information on how \pkg{parsnip} is used for modeling is at
\url{https://www.tidymodels.org/}.
}
\details{
This function only defines what \emph{type} of model is being fit. Once an engine
is specified, the \emph{method} to fit the model is also defined.

The model is not trained or fit until the \code{\link[=fit.model_spec]{fit.model_spec()}} function is used
with the data.
}
\references{
\url{https://www.tidymodels.org}, \href{https://www.tmwr.org/}{\emph{Tidy Models with R}}
}
\seealso{
\Sexpr[stage=render,results=rd]{parsnip:::make_seealso_list("discrim_flexible")}
}