org.apache.mahout.clustering.kmeans
Class Cluster

java.lang.Object
  extended by org.apache.mahout.clustering.AbstractCluster
      extended by org.apache.mahout.clustering.DistanceMeasureCluster
          extended by org.apache.mahout.clustering.kmeans.Cluster
All Implemented Interfaces:
org.apache.hadoop.io.Writable, Cluster, Model<VectorWritable>
Direct Known Subclasses:
MeanShiftCanopy, SoftCluster

public class Cluster
extends DistanceMeasureCluster


Field Summary
 
Fields inherited from class org.apache.mahout.clustering.DistanceMeasureCluster
measure
 
Fields inherited from interface org.apache.mahout.clustering.Cluster
CLUSTERED_POINTS_DIR, CLUSTERS_DIR, INITIAL_CLUSTERS_DIR
 
Constructor Summary
Cluster()
          For (de)serialization as a Writable
Cluster(Vector center, int clusterId, DistanceMeasure measure)
          Construct a new cluster with the given point as its center
 
Method Summary
 java.lang.String asFormatString()
           
 boolean computeConvergence(DistanceMeasure measure, double convergenceDelta)
          Return if the cluster is converged by comparing its center and centroid.
static java.lang.String formatCluster(Cluster cluster)
          Format the cluster for output
 java.lang.String getIdentifier()
           
 boolean isConverged()
           
 void readFields(java.io.DataInput in)
           
protected  void setConverged(boolean converged)
           
 java.lang.String toString()
           
 void write(java.io.DataOutput out)
           
 
Methods inherited from class org.apache.mahout.clustering.DistanceMeasureCluster
getMeasure, pdf, sampleFromPosterior, setMeasure
 
Methods inherited from class org.apache.mahout.clustering.AbstractCluster
asFormatString, asJsonString, computeCentroid, computeParameters, count, formatVector, getCenter, getId, getNumPoints, getObservations, getRadius, getS0, getS1, getS2, observe, observe, observe, observe, setCenter, setId, setNumPoints, setRadius
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
 

Constructor Detail

Cluster

public Cluster()
For (de)serialization as a Writable


Cluster

public Cluster(Vector center,
               int clusterId,
               DistanceMeasure measure)
Construct a new cluster with the given point as its center

Parameters:
center - the Vector center
clusterId - the int cluster id
measure - a DistanceMeasure
Method Detail

formatCluster

public static java.lang.String formatCluster(Cluster cluster)
Format the cluster for output

Parameters:
cluster - the Cluster
Returns:
the String representation of the Cluster

asFormatString

public java.lang.String asFormatString()

write

public void write(java.io.DataOutput out)
           throws java.io.IOException
Specified by:
write in interface org.apache.hadoop.io.Writable
Overrides:
write in class DistanceMeasureCluster
Throws:
java.io.IOException

readFields

public void readFields(java.io.DataInput in)
                throws java.io.IOException
Specified by:
readFields in interface org.apache.hadoop.io.Writable
Overrides:
readFields in class DistanceMeasureCluster
Throws:
java.io.IOException

toString

public java.lang.String toString()
Overrides:
toString in class java.lang.Object

getIdentifier

public java.lang.String getIdentifier()
Overrides:
getIdentifier in class DistanceMeasureCluster

computeConvergence

public boolean computeConvergence(DistanceMeasure measure,
                                  double convergenceDelta)
Return if the cluster is converged by comparing its center and centroid.

Parameters:
measure - The distance measure to use for cluster-point comparisons.
convergenceDelta - the convergence delta to use for stopping.
Returns:
if the cluster is converged

isConverged

public boolean isConverged()

setConverged

protected void setConverged(boolean converged)


Copyright © 2008-2010 The Apache Software Foundation. All Rights Reserved.