org.apache.commons.math3.ml.clustering

Class Clusterer<T extends Clusterable>

java.lang.Object

org.apache.commons.math3.ml.clustering.Clusterer<T>

Type Parameters:

T - the type of points that can be clustered

Direct Known Subclasses:

DBSCANClusterer, FuzzyKMeansClusterer, KMeansPlusPlusClusterer, MultiKMeansPlusPlusClusterer

public abstract class Clusterer<T extends Clusterable>
extends java.lang.Object

Base class for clustering algorithms.

Since:

3.2

Method Summary

Modifier and Type	Method and Description
abstract java.util.List<? extends Cluster<T>>	cluster(java.util.Collection<T> points) Perform a cluster analysis on the given set of Clusterable instances.
DistanceMeasure	getDistanceMeasure() Returns the DistanceMeasure instance used by this clusterer.

Methods inherited from class java.lang.Object

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

Method Detail

cluster

public abstract java.util.List<? extends Cluster<T>> cluster(java.util.Collection<T> points)
                                                      throws MathIllegalArgumentException,
                                                             ConvergenceException

Perform a cluster analysis on the given set of Clusterable instances.

Parameters:

points - the set of Clusterable instances

Returns:

a List of clusters

Throws:

MathIllegalArgumentException - if points are null or the number of data points is not compatible with this clusterer

ConvergenceException - if the algorithm has not yet converged after the maximum number of iterations has been exceeded

getDistanceMeasure

public DistanceMeasure getDistanceMeasure()

Returns the DistanceMeasure instance used by this clusterer.

Returns:

the distance measure