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java.lang.Object | +--weka.clusterers.Clusterer | +--weka.clusterers.DensityBasedClusterer
Abstract clustering model that produces (for each test instance) an estimate of the membership in each cluster (ie. a probability distribution).
Constructor Summary | |
DensityBasedClusterer()
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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. |
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 |
public DensityBasedClusterer()
Method Detail |
public abstract double[] clusterPriors() throws java.lang.Exception
java.lang.Exception
- if priors could not be
returned successfullypublic abstract double[] logDensityPerClusterForInstance(Instance instance) throws java.lang.Exception
instance
- the instance to compute the density for
java.lang.Exception
- if the density could not be computed
successfullypublic double logDensityForInstance(Instance instance) throws java.lang.Exception
instance
- the instance to compute the density for
java.lang.Exception
- if the density could not be computed successfullypublic double[] distributionForInstance(Instance instance) throws java.lang.Exception
distributionForInstance
in class Clusterer
instance
- the instance to be clustered
java.lang.Exception
- if distribution could not be
computed successfully
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Copyright (c) 2003 David Lindsay, Computer Learning Research Centre, Dept. Computer Science, Royal Holloway, University of London