Class KMeansPlusPlusClusterer<T extends Clusterable<T>>
- java.lang.Object
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- org.apache.commons.math3.stat.clustering.KMeansPlusPlusClusterer<T>
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- Type Parameters:
T
- type of the points to cluster
@Deprecated public class KMeansPlusPlusClusterer<T extends Clusterable<T>> extends java.lang.Object
Deprecated.As of 3.2 (to be removed in 4.0), useKMeansPlusPlusClusterer
insteadClustering algorithm based on David Arthur and Sergei Vassilvitski k-means++ algorithm.- Since:
- 2.0
- See Also:
- K-means++ (wikipedia)
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Nested Class Summary
Nested Classes Modifier and Type Class Description static class
KMeansPlusPlusClusterer.EmptyClusterStrategy
Deprecated.Strategies to use for replacing an empty cluster.
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Field Summary
Fields Modifier and Type Field Description private KMeansPlusPlusClusterer.EmptyClusterStrategy
emptyStrategy
Deprecated.Selected strategy for empty clusters.private java.util.Random
random
Deprecated.Random generator for choosing initial centers.
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Constructor Summary
Constructors Constructor Description KMeansPlusPlusClusterer(java.util.Random random)
Deprecated.Build a clusterer.KMeansPlusPlusClusterer(java.util.Random random, KMeansPlusPlusClusterer.EmptyClusterStrategy emptyStrategy)
Deprecated.Build a clusterer.
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Deprecated Methods Modifier and Type Method Description private static <T extends Clusterable<T>>
intassignPointsToClusters(java.util.List<Cluster<T>> clusters, java.util.Collection<T> points, int[] assignments)
Deprecated.Adds the given points to the closestCluster
.private static <T extends Clusterable<T>>
java.util.List<Cluster<T>>chooseInitialCenters(java.util.Collection<T> points, int k, java.util.Random random)
Deprecated.Use K-means++ to choose the initial centers.java.util.List<Cluster<T>>
cluster(java.util.Collection<T> points, int k, int maxIterations)
Deprecated.Runs the K-means++ clustering algorithm.java.util.List<Cluster<T>>
cluster(java.util.Collection<T> points, int k, int numTrials, int maxIterationsPerTrial)
Deprecated.Runs the K-means++ clustering algorithm.private T
getFarthestPoint(java.util.Collection<Cluster<T>> clusters)
Deprecated.Get the point farthest to its cluster centerprivate static <T extends Clusterable<T>>
intgetNearestCluster(java.util.Collection<Cluster<T>> clusters, T point)
Deprecated.Returns the nearestCluster
to the given pointprivate T
getPointFromLargestNumberCluster(java.util.Collection<Cluster<T>> clusters)
Deprecated.Get a random point from theCluster
with the largest number of pointsprivate T
getPointFromLargestVarianceCluster(java.util.Collection<Cluster<T>> clusters)
Deprecated.Get a random point from theCluster
with the largest distance variance.
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Field Detail
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random
private final java.util.Random random
Deprecated.Random generator for choosing initial centers.
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emptyStrategy
private final KMeansPlusPlusClusterer.EmptyClusterStrategy emptyStrategy
Deprecated.Selected strategy for empty clusters.
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Constructor Detail
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KMeansPlusPlusClusterer
public KMeansPlusPlusClusterer(java.util.Random random)
Deprecated.Build a clusterer.The default strategy for handling empty clusters that may appear during algorithm iterations is to split the cluster with largest distance variance.
- Parameters:
random
- random generator to use for choosing initial centers
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KMeansPlusPlusClusterer
public KMeansPlusPlusClusterer(java.util.Random random, KMeansPlusPlusClusterer.EmptyClusterStrategy emptyStrategy)
Deprecated.Build a clusterer.- Parameters:
random
- random generator to use for choosing initial centersemptyStrategy
- strategy to use for handling empty clusters that may appear during algorithm iterations- Since:
- 2.2
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Method Detail
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cluster
public java.util.List<Cluster<T>> cluster(java.util.Collection<T> points, int k, int numTrials, int maxIterationsPerTrial) throws MathIllegalArgumentException, ConvergenceException
Deprecated.Runs the K-means++ clustering algorithm.- Parameters:
points
- the points to clusterk
- the number of clusters to split the data intonumTrials
- number of trial runsmaxIterationsPerTrial
- the maximum number of iterations to run the algorithm for at each trial run. If negative, no maximum will be used- Returns:
- a list of clusters containing the points
- Throws:
MathIllegalArgumentException
- if the data points are null or the number of clusters is larger than the number of data pointsConvergenceException
- if an empty cluster is encountered and theemptyStrategy
is set toERROR
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cluster
public java.util.List<Cluster<T>> cluster(java.util.Collection<T> points, int k, int maxIterations) throws MathIllegalArgumentException, ConvergenceException
Deprecated.Runs the K-means++ clustering algorithm.- Parameters:
points
- the points to clusterk
- the number of clusters to split the data intomaxIterations
- the maximum number of iterations to run the algorithm for. If negative, no maximum will be used- Returns:
- a list of clusters containing the points
- Throws:
MathIllegalArgumentException
- if the data points are null or the number of clusters is larger than the number of data pointsConvergenceException
- if an empty cluster is encountered and theemptyStrategy
is set toERROR
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assignPointsToClusters
private static <T extends Clusterable<T>> int assignPointsToClusters(java.util.List<Cluster<T>> clusters, java.util.Collection<T> points, int[] assignments)
Deprecated.Adds the given points to the closestCluster
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chooseInitialCenters
private static <T extends Clusterable<T>> java.util.List<Cluster<T>> chooseInitialCenters(java.util.Collection<T> points, int k, java.util.Random random)
Deprecated.Use K-means++ to choose the initial centers.- Type Parameters:
T
- type of the points to cluster- Parameters:
points
- the points to choose the initial centers fromk
- the number of centers to chooserandom
- random generator to use- Returns:
- the initial centers
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getPointFromLargestVarianceCluster
private T getPointFromLargestVarianceCluster(java.util.Collection<Cluster<T>> clusters) throws ConvergenceException
Deprecated.Get a random point from theCluster
with the largest distance variance.- Parameters:
clusters
- theCluster
s to search- Returns:
- a random point from the selected cluster
- Throws:
ConvergenceException
- if clusters are all empty
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getPointFromLargestNumberCluster
private T getPointFromLargestNumberCluster(java.util.Collection<Cluster<T>> clusters) throws ConvergenceException
Deprecated.Get a random point from theCluster
with the largest number of points- Parameters:
clusters
- theCluster
s to search- Returns:
- a random point from the selected cluster
- Throws:
ConvergenceException
- if clusters are all empty
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getFarthestPoint
private T getFarthestPoint(java.util.Collection<Cluster<T>> clusters) throws ConvergenceException
Deprecated.Get the point farthest to its cluster center- Parameters:
clusters
- theCluster
s to search- Returns:
- point farthest to its cluster center
- Throws:
ConvergenceException
- if clusters are all empty
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getNearestCluster
private static <T extends Clusterable<T>> int getNearestCluster(java.util.Collection<Cluster<T>> clusters, T point)
Deprecated.Returns the nearestCluster
to the given point
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