demo_hddc

<p>This demonstration uses a PCA on the first two principal axis of the Crabs dataset -that can be found in the package- to show the clustering process of HDDC. At each step of the clustering, the means and directions are shown by, respectively, points and lines.
This function should only be used in demo(hddc).</p>

 demo 

Discriminant analysis and data clustering methods for high
dimensional data, based on the assumption that high-dimensional data live in
different subspaces with low dimensionality proposing a new parametrization of
the Gaussian mixture model which combines the ideas of dimension reduction and
constraints on the model.

Laurent Berge

HDclassif

High Dimensional Supervised Classification and Clustering

demo_hddc function

<p>Laurent Berge, Charles Bouveyron and Stephane Girard</p>

demo_hddc: Demonstration of the clustering process of HDDC.

Description

Usage

Arguments

Value

Author

See Also