mda.start: Initialization for Mixture Discriminant Analysis

In mda: Mixture and Flexible Discriminant Analysis

Initialization for Mixture Discriminant Analysis

Description

Provide starting weights for the mda function which performs discriminant analysis by gaussian mixtures.

Usage

mda.start(x, g, subclasses = 3, trace.mda.start = FALSE,
          start.method = c("kmeans", "lvq"), tries = 5,
          criterion = c("misclassification", "deviance"), ...)

Arguments

x	The x data, or an mda object.
g	The response vector g.
subclasses	number of subclasses per class, as in mda.
trace.mda.start	Show results of each iteration.
start.method	Either "kmeans" or "lvq". The latter requires package class (from the VR package bundle.
tries	Number of random starts.
criterion	By default, classification errors on the training data. Posterior deviance is also an option.
...	arguments to be passed to the mda fitter when using posterior deviance.

Value

A list of weight matrices, one for each class.

mda documentation built on July 9, 2023, 7:14 p.m.