jsat.clustering.kmeans

Class LloydKernelKMeans

java.lang.Object

jsat.clustering.ClustererBase

jsat.clustering.KClustererBase

jsat.clustering.kmeans.KernelKMeans

jsat.clustering.kmeans.LloydKernelKMeans

All Implemented Interfaces:

Serializable, Clusterer, KClusterer, Parameterized

public class LloydKernelKMeans
extends KernelKMeans

An implementation of the naive algorithm for performing kernel k-means.

Author:

Edward Raff

See Also:

Serialized Form

Field Summary

Fields inherited from class jsat.clustering.kmeans.KernelKMeans

accel, kernel, maximumIterations, meanSqrdNorms, newDesignations, normConsts, ownes, selfK, W, X

Constructor Summary

Constructors

Constructor and Description
LloydKernelKMeans(KernelTrick kernel) Creates a new Kernel K Means object
LloydKernelKMeans(LloydKernelKMeans toCopy) Copy constructor

Method Summary

Modifier and Type	Method and Description
KernelKMeans	clone()
int[]	cluster(DataSet dataSet, int K, ExecutorService threadpool, int[] designations)
int[]	cluster(DataSet dataSet, int K, int[] designations)

Methods inherited from class jsat.clustering.kmeans.KernelKMeans

applyMeanUpdates, cluster, cluster, cluster, cluster, distance, distance, distance, evalSumK, evalSumK, findClosestCluster, findClosestCluster, getMaximumIterations, getParameter, getParameters, meanToMeanDistance, meanToMeanDistance, meanToMeanDistance, meanToMeanDistance, meanToMeanDistance, setMaximumIterations, setup, supportsWeightedData, updateMeansFromChange, updateMeansFromChange, updateNormConsts

Methods inherited from class jsat.clustering.KClustererBase

cluster, cluster, cluster, cluster

Methods inherited from class jsat.clustering.ClustererBase

cluster, cluster, createClusterListFromAssignmentArray, getDatapointsFromCluster

Methods inherited from class java.lang.Object

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

Methods inherited from interface jsat.clustering.Clusterer

cluster, cluster

Constructor Detail

LloydKernelKMeans

public LloydKernelKMeans(KernelTrick kernel)

Creates a new Kernel K Means object

Parameters:

kernel - the kernel to use

LloydKernelKMeans

public LloydKernelKMeans(LloydKernelKMeans toCopy)

Copy constructor

Parameters:

toCopy - the object to copy

Method Detail

cluster

public int[] cluster(DataSet dataSet,
                     int K,
                     ExecutorService threadpool,
                     int[] designations)

cluster

public int[] cluster(DataSet dataSet,
                     int K,
                     int[] designations)

clone

public KernelKMeans clone()

Specified by:

clone in interface Clusterer

Specified by:

clone in interface KClusterer

Specified by:

clone in class KernelKMeans