Package elki.clustering.kmeans.initialization.betula

Class AbstractCFKMeansInitialization

java.lang.Object

elki.clustering.kmeans.initialization.betula.AbstractCFKMeansInitialization

Direct Known Subclasses:

CFKPlusPlusLeaves, CFKPlusPlusTree, CFRandomlyChosen, CFWeightedRandomlyChosen

public abstract class AbstractCFKMeansInitialization
extends java.lang.Object

Abstract base class for CF k-means initializations. For regular k-means use AbstractKMeansInitialization instead.

Since:

0.8.0

Author:

Andreas Lang

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	AbstractCFKMeansInitialization.Par	Parameterization class.

Field Summary

Fields

Modifier and Type	Field	Description
protected RandomFactory	rf	Random number generator

Constructor Summary

Constructors

Constructor	Description
AbstractCFKMeansInitialization(RandomFactory rf)	Constructor.

Method Summary

Modifier and Type	Method	Description
abstract double[][]	chooseInitialMeans(CFTree<?> tree, java.util.List<? extends ClusterFeature> cfs, int k)	Build the initial models.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

rf

protected RandomFactory rf

Random number generator

Constructor Detail

AbstractCFKMeansInitialization

public AbstractCFKMeansInitialization(RandomFactory rf)

Constructor.

Parameters:

rf - Random number generator

Method Detail

chooseInitialMeans

public abstract double[][] chooseInitialMeans(CFTree<?> tree,
                                              java.util.List<? extends ClusterFeature> cfs,
                                              int k)

Build the initial models.

Parameters:

tree - CF tree

cfs - Cluster features of the tree (may be ignored for tree-based initializations, should be an array list for efficiency)

k - Number of clusters.

Returns:

initial cluster means