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/*
* File: ClusterCompleteLinkDivergenceFunction.java
* Authors: Justin Basilico
* Company: Sandia National Laboratories
* Project: Cognitive Foundry
*
* Copyright June 28, 2006, Sandia Corporation. Under the terms of Contract
* DE-AC04-94AL85000, there is a non-exclusive license for use of this work by
* or on behalf of the U.S. Government. Export of this program may require a
* license from the United States Government. See CopyrightHistory.txt for
* complete details.
*
*/
package gov.sandia.cognition.learning.algorithm.clustering.divergence;
import gov.sandia.cognition.annotation.CodeReview;
import gov.sandia.cognition.learning.algorithm.clustering.cluster.Cluster;
import gov.sandia.cognition.math.DivergenceFunction;
import java.util.Collection;
/**
* The ClusterCompleteLinkDivergenceFunction class implements the complete
* linkage distance metric between two clusters. That is, the value returned
* by the metric is the maximum distance between any point in the first
* cluster and any point in the second cluster.
*
*
* @param type of {@code Cluster} used in the
* {@code learn()} method
* @param The algorithm operates on a {@code Collection},
* so {@code DataType} will be something like Vector or String
* @author Justin Basilico
* @since 1.0
*/
@CodeReview(
reviewer="Kevin R. Dixon",
date="2008-07-23",
changesNeeded=false,
comments={
"Cleaned up javadoc a little bit with code annotations.",
"Otherwise, looks fine."
}
)
public class ClusterCompleteLinkDivergenceFunction, DataType>
extends AbstractClusterToClusterDivergenceFunction
{
/**
* Creates a new instance of ClusterCompleteLinkDivergenceFunction.
*/
public ClusterCompleteLinkDivergenceFunction()
{
this(null);
}
/**
* Creates a new instance of ClusterCompleteLinkDivergenceFunction using
* the given divergence function for elements.
*
* @param divergenceFunction The divergence function for elements.
*/
public ClusterCompleteLinkDivergenceFunction(
DivergenceFunction super DataType, ? super DataType>
divergenceFunction)
{
super(divergenceFunction);
}
/**
* This method computes the complete link distance between the two given
* Clusters. The distance returned is the maximum distance between a
* member of the first cluster and a member of the second cluster.
*
* @param from The first Cluster.
* @param to The second Cluster.
* @return The complete link distance between the two given Clusters.
*/
public double evaluate(
ClusterType from,
ClusterType to)
{
// Get the members of each cluster.
Collection fromMembers = from.getMembers();
Collection toMembers = to.getMembers();
// We are going to compute the maximum distance so start with the
// minimum distance value.
double maxDistance = Double.MIN_VALUE;
// Do a double loop through the members of the two clusters.
for ( DataType first : fromMembers )
{
for ( DataType second : toMembers )
{
// Compute the distance between the two memebers.
double distance = this.divergenceFunction.evaluate(first, second);
if ( distance > maxDistance )
{
// This is the maximum distance seen so far so
// store it.
maxDistance = distance;
}
}
}
// Return the maximum distance that was found.
return maxDistance;
}
}
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