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## weka.clusterers
Class DensityBasedClusterer

    java.lang.Object
      weka.clusterers.Clusterer
          weka.clusterers.DensityBasedClusterer

All Implemented Interfaces:
  java.io.Serializable, java.lang.Cloneable

Direct Known Subclasses:
  EM, MakeDensityBasedClusterer

    public abstract class DensityBasedClusterer

extends Clusterer

Abstract clustering model that produces (for each test instance) an estimate of the membership in each cluster (ie. a probability distribution).

Version:
  $Revision: 1.4 $
Author:
  Mark Hall (mhall@cs.waikato.ac.nz), Eibe Frank (eibe@cs.waikato.ac.nz)
See Also:
  Serialized Form

Constructor Summary
`DensityBasedClusterer()`

Method Summary
`abstract double[]` | `clusterPriors()` Returns the prior probability of each cluster.
`double[]` | `distributionForInstance(Instance instance)` Returns the cluster probability distribution for an instance.
`double` | `logDensityForInstance(Instance instance)` Computes the density for a given instance.
`abstract double[]` | `logDensityPerClusterForInstance(Instance instance)` Computes the log of the conditional density (per cluster) for a given instance.
`double[]` | `logJointDensitiesForInstance(Instance inst)` Returns the logs of the joint densities for a given instance.
`static DensityBasedClusterer[]` | `makeCopies(DensityBasedClusterer model, int num)` Creates copies of the current clusterer.

Methods inherited from class weka.clusterers.Clusterer
`buildClusterer, clusterInstance, forName, makeCopies, numberOfClusters`

Methods inherited from class java.lang.Object
`equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Constructor Detail

### DensityBasedClusterer

    public DensityBasedClusterer()

Method Detail

### clusterPriors

    public abstract double[] clusterPriors()
                                    throws java.lang.Exception

  Returns the prior probability of each cluster.

  Returns:
    the prior probability for each cluster
  Throws:
    `java.lang.Exception` - if priors could not be returned successfully

### logDensityPerClusterForInstance

    public abstract double[] logDensityPerClusterForInstance(Instance instance)
                                                      throws java.lang.Exception

  Computes the log of the conditional density (per cluster) for a given instance.

  Parameters:
    `instance` - the instance to compute the density for
  Returns:
    the density.
  Throws:
    `java.lang.Exception` - if the density could not be computed successfully

### logDensityForInstance

    public double logDensityForInstance(Instance instance)
                                 throws java.lang.Exception

  Computes the density for a given instance.

  Parameters:
    `instance` - the instance to compute the density for
  Returns:
    the density.
  Throws:
    `java.lang.Exception` - if the density could not be computed successfully

### distributionForInstance

    public double[] distributionForInstance(Instance instance)
                                     throws java.lang.Exception

  Returns the cluster probability distribution for an instance.

  Overrides:
    `distributionForInstance` in class `Clusterer`
  Parameters:
    `instance` - the instance to be clustered
  Returns:
    the probability distribution
  Throws:
    `java.lang.Exception` - if distribution could not be computed successfully

### logJointDensitiesForInstance

    public double[] logJointDensitiesForInstance(Instance inst)
                                          throws java.lang.Exception

  Returns the logs of the joint densities for a given instance.

  Parameters:
    `inst` - the instance
  Returns:
    the array of values
  Throws:
    `java.lang.Exception` - if values could not be computed

### makeCopies

    public static DensityBasedClusterer[] makeCopies(DensityBasedClusterer model,
                                                     int num)
                                              throws java.lang.Exception

  Creates copies of the current clusterer. Note that this method now uses Serialization to perform a deep copy, so the Clusterer object must be fully Serializable. Any currently built model will now be copied as well.

  Parameters:
    `model` - an example clusterer to copy
    `num` - the number of clusterer copies to create.
  Returns:
    an array of clusterers.
  Throws:
    `java.lang.Exception` - if an error occurs

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