T - type of the points to clusterKMeansPlusPlusClusterer instead@Deprecated public class KMeansPlusPlusClusterer<T extends Clusterable<T>> extends Object
| Modifier and Type | Class and Description |
|---|---|
static class |
KMeansPlusPlusClusterer.EmptyClusterStrategy
Deprecated.
Strategies to use for replacing an empty cluster.
|
| Constructor and Description |
|---|
KMeansPlusPlusClusterer(Random random)
Deprecated.
Build a clusterer.
|
KMeansPlusPlusClusterer(Random random,
KMeansPlusPlusClusterer.EmptyClusterStrategy emptyStrategy)
Deprecated.
Build a clusterer.
|
| Modifier and Type | Method and Description |
|---|---|
List<Cluster<T>> |
cluster(Collection<T> points,
int k,
int maxIterations)
Deprecated.
Runs the K-means++ clustering algorithm.
|
List<Cluster<T>> |
cluster(Collection<T> points,
int k,
int numTrials,
int maxIterationsPerTrial)
Deprecated.
Runs the K-means++ clustering algorithm.
|
public KMeansPlusPlusClusterer(Random random)
The default strategy for handling empty clusters that may appear during algorithm iterations is to split the cluster with largest distance variance.
random - random generator to use for choosing initial centerspublic KMeansPlusPlusClusterer(Random random, KMeansPlusPlusClusterer.EmptyClusterStrategy emptyStrategy)
random - random generator to use for choosing initial centersemptyStrategy - strategy to use for handling empty clusters that
may appear during algorithm iterationspublic List<Cluster<T>> cluster(Collection<T> points, int k, int numTrials, int maxIterationsPerTrial) throws MathIllegalArgumentException, ConvergenceException
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 usedMathIllegalArgumentException - 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 the
emptyStrategy is set to ERRORpublic List<Cluster<T>> cluster(Collection<T> points, int k, int maxIterations) throws MathIllegalArgumentException, ConvergenceException
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 usedMathIllegalArgumentException - 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 the
emptyStrategy is set to ERRORCopyright © 2003–2016 The Apache Software Foundation. All rights reserved.