print.mlcc.reps.fit

<p>Further arguments to be passed to or from other methods. They are
ignored in this function.</p>

internal

Performs clustering of quantitative variables,
assuming that clusters lie in low-dimensional subspaces. Segmentation of
variables, number of clusters and their dimensions are selected based on
BIC. Candidate models are identified based on many runs of K-means
algorithm with different random initializations of cluster centers.

Piotr Sobczyk

print.mlcc.reps.fit: Print mlcc.reps.fit class object

Description

Usage

Arguments