LDAModel: Linear Discriminant Analysis Model

View source: R/ML_LDAModel.R

LDAModelR Documentation

Linear Discriminant Analysis Model

Description

Performs linear discriminant analysis.

Usage

LDAModel(
  prior = numeric(),
  tol = 1e-04,
  method = c("moment", "mle", "mve", "t"),
  nu = 5,
  dimen = integer(),
  use = c("plug-in", "debiased", "predictive")
)

Arguments

prior

prior probabilities of class membership if specified or the class proportions in the training set otherwise.

tol

tolerance for the determination of singular matrices.

method

type of mean and variance estimator.

nu

degrees of freedom for method = "t".

dimen

dimension of the space to use for prediction.

use

type of parameter estimation to use for prediction.

Details

Response types:

factor

Automatic tuning of grid parameter:

dimen

The predict function for this model additionally accepts the following argument.

prior

prior class membership probabilities for prediction data if different from the training set.

Default argument values and further model details can be found in the source See Also links below.

Value

MLModel class object.

See Also

lda, predict.lda, fit, resample

Examples

fit(Species ~ ., data = iris, model = LDAModel)


MachineShop documentation built on Sept. 11, 2024, 6:28 p.m.