org.apache.mahout.clustering.iterator
Class CanopyClusteringPolicy

java.lang.Object
  extended by org.apache.mahout.clustering.iterator.AbstractClusteringPolicy
      extended by org.apache.mahout.clustering.iterator.CanopyClusteringPolicy
All Implemented Interfaces:
org.apache.hadoop.io.Writable, ClusteringPolicy

public class CanopyClusteringPolicy
extends AbstractClusteringPolicy

This is a simple maximum likelihood clustering policy, suitable for k-means clustering


Constructor Summary
CanopyClusteringPolicy()
           
 
Method Summary
 void readFields(DataInput in)
           
 Vector select(Vector probabilities)
          Return a vector of weights for each of the models given those probabilities
 void write(DataOutput out)
           
 
Methods inherited from class org.apache.mahout.clustering.iterator.AbstractClusteringPolicy
classify, close, update
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

CanopyClusteringPolicy

public CanopyClusteringPolicy()
Method Detail

select

public Vector select(Vector probabilities)
Description copied from interface: ClusteringPolicy
Return a vector of weights for each of the models given those probabilities

Specified by:
select in interface ClusteringPolicy
Overrides:
select in class AbstractClusteringPolicy
Parameters:
probabilities - a Vector of pdfs
Returns:
a Vector of weights

write

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

readFields

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


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