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

r descr_models("discrim_quad", "sparsediscrim")

Tuning Parameters

defaults <- 
  tibble::tibble(parsnip = c("regularization_method"),
                 default = c("'diagonal'"))

param <-
  discrim_quad() %>% 
  set_engine("sparsediscrim") %>% 
  make_parameter_list(defaults)

This model has r nrow(param) tuning parameter:

param$item

The possible values of this parameter, and the functions that they execute, are:

"diagonal": [sparsediscrim::qda_diag()]
"shrink_mean": [sparsediscrim::qda_shrink_mean()]
"shrink_cov": [sparsediscrim::qda_shrink_cov()]

Translation from parsnip to the original package

r uses_extension("discrim_quad", "sparsediscrim", "classification")

library(discrim)

discrim_quad(regularization_method = character(0)) %>% 
  set_engine("sparsediscrim") %>% 
  translate()

Preprocessing requirements

Case weights

References

qda_diag(): Dudoit, Fridlyand and Speed (2002) Comparison of Discrimination Methods for the Classification of Tumors Using Gene Expression Data, Journal of the American Statistical Association, 97:457, 77-87.
qda_shrink_mean(): Tong, Chen, Zhao, Improved mean estimation and its application to diagonal discriminant analysis, Bioinformatics, Volume 28, Issue 4, 15 February 2012, Pages 531-537.
qda_shrink_cov(): Pang, Tong and Zhao (2009), Shrinkage-based Diagonal Discriminant Analysis and Its Applications in High-Dimensional Data. Biometrics, 65, 1021-1029.