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Class weka.clusterers.DistributionClusterer
java.lang.Object
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+----weka.clusterers.Clusterer
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+----weka.clusterers.DistributionClusterer
- public abstract class DistributionClusterer
- 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: 1.7 $
- Author:
- Mark Hall (mhall@cs.waikato.ac.nz)
DistributionClusterer()
-
clusterInstance(Instance)
- Assigns an instance to a Cluster.
densityForInstance(Instance)
- Computes the density for a given instance.
distributionForInstance(Instance)
- Predicts the cluster memberships for a given instance.
DistributionClusterer
public DistributionClusterer()
densityForInstance
public abstract double densityForInstance(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 abstract double[] distributionForInstance(Instance instance) throws java.lang.Exception
Predicts the cluster memberships for a given instance.
- Parameters:
instance
- the instance to be assigned a cluster.
- Returns:
- an array containing the estimated membership
probabilities of the test instance in each cluster (this
should sum to at most 1)
- Throws:
- java.lang.Exception - if distribution could not be
computed successfully
clusterInstance
public int clusterInstance(Instance instance) throws java.lang.Exception
Assigns an instance to a Cluster.
- Parameters:
instance
- the instance to be classified
- Returns:
- the predicted most likely cluster for the instance.
- Throws:
- java.lang.Exception - if an error occurred during the prediction
- Overrides:
- clusterInstance in class Clusterer
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