Package weka.clusterers

Interface DensityBasedClusterer

All Superinterfaces:
Clusterer
All Known Implementing Classes:
AbstractDensityBasedClusterer, EM, MakeDensityBasedClusterer, RandomizableDensityBasedClusterer
public interface DensityBasedClusterer extends Clusterer
Interface for clusterers that can estimate the density for a given instance. Implementations will typically extend AbstractDensityBasedClusterer.
Version:
$Revision: 9379 $
Author:
Mark Hall (mhall@cs.waikato.ac.nz), Eibe Frank (eibe@cs.waikato.ac.nz)

  • Method Details

    • clusterPriors

      double[] clusterPriors() throws Exception
      Returns the prior probability of each cluster.
      Returns:
      the prior probability for each cluster
      Throws:
      Exception - if priors could not be returned successfully

    • logDensityPerClusterForInstance

      double[] logDensityPerClusterForInstance(Instance instance) throws Exception
      Computes the log of the conditional density (per cluster) for a given instance.
      Parameters:
      instance - the instance to compute the density for
      Returns:
      an array containing the estimated densities
      Throws:
      Exception - if the density could not be computed successfully

    • logDensityForInstance

      double logDensityForInstance(Instance instance) throws Exception
      Computes the density for a given instance.
      Parameters:
      instance - the instance to compute the density for
      Returns:
      the density.
      Throws:
      Exception - if the density could not be computed successfully

    • logJointDensitiesForInstance

      double[] logJointDensitiesForInstance(Instance inst) throws Exception
      Returns the logs of the joint densities for a given instance.
      Parameters:
      inst - the instance
      Returns:
      the array of values
      Throws:
      Exception - if values could not be computed

    • distributionForInstance

      double[] distributionForInstance(Instance instance) throws Exception
      Returns the cluster probability distribution for an instance.
      Specified by:
      distributionForInstance in interface Clusterer
      Parameters:
      instance - the instance to be clustered
      Returns:
      the probability distribution
      Throws:
      Exception - if computation fails