For this engine, there is a single mode: classification
This engine has no tuning parameters.
The discrim extension package is required to fit this model.
library(discrim)
discrim_quad() %>%
set_engine("MASS") %>%
translate()
## Quadratic Discriminant Model Specification (classification)
##
## Computational engine: MASS
##
## Model fit template:
## MASS::qda(formula = missing_arg(), data = missing_arg())
Factor/categorical predictors need to be converted to numeric values (e.g., dummy or indicator variables) for this engine. When using the formula method via \code{\link[=fit.model_spec]{fit()}}, parsnip will convert factor columns to indicators.
Variance calculations are used in these computations within each outcome class. For this reason, zero-variance predictors (i.e., with a single unique value) within each class should be eliminated before fitting the model.
The underlying model implementation does not allow for case weights.
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