gov.sandia.cognition.learning.algorithm.clustering.initializer

Interface FixedClusterInitializer<ClusterType extends Cluster<DataType>,DataType>

Type Parameters:

ClusterType - Type of Cluster<DataType> used in the learn() method.

DataType - The algorithm operates on a Collection<DataType>, so DataType will be something like Vector or String

All Known Implementing Classes:

AbstractMinDistanceFixedClusterInitializer, DistanceSamplingClusterInitializer, GreedyClusterInitializer, NeighborhoodGaussianClusterInitializer, RandomClusterInitializer

@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 interface FixedClusterInitializer<ClusterType extends Cluster<DataType>,DataType>

The FixedClusterInitializer interface defines the functionality of a class that can initialize a given number of clusters from a set of elements. Such an initializer is used in some clustering algorithms to provide the starting clusters for the algorithm.

Since:

1.0

Author:

Justin Basilico, Kevin R. Dixon

Method Summary

Modifier and Type	Method and Description
java.util.ArrayList<ClusterType>	initializeClusters(int numClusters, java.util.Collection<? extends DataType> elements) Initializes a given number of clusters from the given elements.

Method Detail

initializeClusters

java.util.ArrayList<ClusterType> initializeClusters(int numClusters,
                                                    java.util.Collection<? extends DataType> elements)

Initializes a given number of clusters from the given elements.

Parameters:

numClusters - The number of clusters to create.

elements - The elements to create the clusters from.

Returns:

The initial clusters to use.

Throws:

java.lang.IllegalArgumentException - If numClusters is less than 0.

java.lang.NullPointerException - If elements is null.