man/rmd/discrim_linear_MASS.md

In topepo/parsnip: A Common API to Modeling and Analysis Functions

For this engine, there is a single mode: classification

Tuning Parameters

This engine has no tuning parameters.

Translation from parsnip to the original package

The discrim extension package is required to fit this model.

library(discrim)

discrim_linear() %>% 
  set_engine("MASS") %>% 
  translate()

## Linear Discriminant Model Specification (classification)
## 
## Computational engine: MASS 
## 
## Model fit template:
## MASS::lda(formula = missing_arg(), data = missing_arg())

Preprocessing requirements

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 so zero-variance predictors (i.e., with a single unique value) should be eliminated before fitting the model.

Case weights

The underlying model implementation does not allow for case weights.

References

• Kuhn, M, and K Johnson. 2013. Applied Predictive Modeling. Springer.

topepo/parsnip documentation built on April 16, 2024, 3:23 a.m.