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kddml.Core.DataMining.Clustering.ClusteringModelManager Interface Reference

Inheritance diagram for kddml.Core.DataMining.Clustering.ClusteringModelManager:

kddml.Core.DataMining.MiningModelManager kddml.Core.DataMining.Clustering.ClusteringModel List of all members.

Public Member Functions

void addCluster (ClusterManager cluster) throws ClusteringModelException
ComparisonMeasure getComparisonMeasure ()
ClusterDescriptionManager getClusterDescription ()
ClusterManager getCluster (int identifier) throws ClusteringModelException
Iterator getClusters ()
int getNumberOfClusters ()
boolean isCentroidBased ()
boolean isDistributionBased ()
int getMaxNumberOfClusters ()
ClusterManager getCluster (Object instance) throws ClusteringModelException
Object toInstances () throws ClusteringModelException

Detailed Description

A manager interface for ClusteringModel.

Title: KDDML

Description: Knowledge Discovery in Database Environment

Copyright: Copyright (c) 2003-2005

Company: Universita' di Pisa - Dipartimento di Informatica

Author:
Andrea Romei (romei@di.unipi.it)
Version:
2.0.16


Member Function Documentation

void kddml.Core.DataMining.Clustering.ClusteringModelManager.addCluster ClusterManager  cluster  )  throws ClusteringModelException
 

Adds a new cluster to the model, both for centroid-based and distribution-based clustering. Throws an exception if the number of clusters exceededs the maximum number of clusters allowed.

Parameters:
cluster ClusterManager
Exceptions:
ClusteringModelException 

Implemented in kddml.Core.DataMining.Clustering.ClusteringModel.

ComparisonMeasure kddml.Core.DataMining.Clustering.ClusteringModelManager.getComparisonMeasure  ) 
 

Returns the aggregate function used to compare two objects. This depends on the type of clustering. Cannot return null.

Returns:
ComparisonMeasure

Implemented in kddml.Core.DataMining.Clustering.ClusteringModel.

ClusterDescriptionManager kddml.Core.DataMining.Clustering.ClusteringModelManager.getClusterDescription  ) 
 

Returns the cluster description for this model. Cannor return null.

Returns:
ClusterDescriptionManager

Implemented in kddml.Core.DataMining.Clustering.ClusteringModel.

ClusterManager kddml.Core.DataMining.Clustering.ClusteringModelManager.getCluster int  identifier  )  throws ClusteringModelException
 

Returns the Cluster object in the model with the specified identifier. Throws an exception if the specified index do not exist in the clustering model.

Parameters:
identifier int a positive value representing the cluster index.
Exceptions:
ClusteringModelException 
Returns:
ClusterManager

Implemented in kddml.Core.DataMining.Clustering.ClusteringModel.

Iterator kddml.Core.DataMining.Clustering.ClusteringModelManager.getClusters  ) 
 

Returns an iterator of cluster objects.

Returns:
Iterator the set of cluster as ClusterManager.

Implemented in kddml.Core.DataMining.Clustering.ClusteringModel.

int kddml.Core.DataMining.Clustering.ClusteringModelManager.getNumberOfClusters  ) 
 

Returns the number of clusters in the model.

Returns:
int

Implemented in kddml.Core.DataMining.Clustering.ClusteringModel.

boolean kddml.Core.DataMining.Clustering.ClusteringModelManager.isCentroidBased  ) 
 

Returns true if the clustering is center-based.

Returns:
boolean

Implemented in kddml.Core.DataMining.Clustering.ClusteringModel.

boolean kddml.Core.DataMining.Clustering.ClusteringModelManager.isDistributionBased  ) 
 

Returns true if the clustering is distribution-based.

Returns:
boolean

Implemented in kddml.Core.DataMining.Clustering.ClusteringModel.

int kddml.Core.DataMining.Clustering.ClusteringModelManager.getMaxNumberOfClusters  ) 
 

Returns the maximum number of clusters that the model can contain.

Returns:
int

Implemented in kddml.Core.DataMining.Clustering.ClusteringModel.

ClusterManager kddml.Core.DataMining.Clustering.ClusteringModelManager.getCluster Object  instance  )  throws ClusteringModelException
 

Returns the cluster containing the input instance. This depends on the type of clustering and the comparison measure used.

Parameters:
instance Object
Exceptions:
ClusteringModelException 
Returns:
ClusterManager

Implemented in kddml.Core.DataMining.Clustering.ClusteringModel.

Object kddml.Core.DataMining.Clustering.ClusteringModelManager.toInstances  )  throws ClusteringModelException
 

Returns a representation of each single cluster as instance. This depends on the type of clustering. For center-based clustering, each cluster is represented by the centroid. In this case, it returns the centroid poind as instance. For distribution-based clustering, each cluster is represented by the statistics. In this case, the instace values depend on the type of attribute. For numeric attribute, the mean containing in the statistics is reported. For discrete attribute, the most probable category value is reported.

Exceptions:
ClusteringModelException if an error occurs.
Returns:
Object the set of instances. Each record represent a single cluster.

Implemented in kddml.Core.DataMining.Clustering.ClusteringModel.


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