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kddml.Core.DataMining.Clustering.ClusterManager Interface Reference

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

kddml.Core.DataMining.Clustering.CentroidBasedClusterManager kddml.Core.DataMining.Clustering.Cluster kddml.Core.DataMining.Clustering.DistributionBasedClusterManager kddml.Core.DataMining.Clustering.CentroidBasedCluster kddml.Core.DataMining.Clustering.CentroidBasedCluster kddml.Core.DataMining.Clustering.DistributionBasedCluster kddml.Core.DataMining.Clustering.DistributionBasedCluster List of all members.

Public Member Functions

int getClusterId ()
String getName ()
Integer getSize ()
void setSize (int num_elements)
void setCovariancesMatrix (CategoryMatrixManager matrix)
CategoryMatrixManager getCovariancesMatrix ()
ClusterStatisticManager getClusterStatistic ()
abstract Object getSeedAsInstance () throws ClusteringModelException
abstract double[] getSeedCoordinate () throws ClusteringModelException
boolean isDistributionBased ()
boolean isCentroidBased ()
void setClusterStatistic (ClusterStatisticManager statistics)

Detailed Description

A manager interface for Cluster.

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

int kddml.Core.DataMining.Clustering.ClusterManager.getClusterId  ) 
 

Returns the cluster id.

Returns:
int

Implemented in kddml.Core.DataMining.Clustering.Cluster.

String kddml.Core.DataMining.Clustering.ClusterManager.getName  ) 
 

Returns the name of the cluster designated by the clustering algorithm.

Returns:
String

Implemented in kddml.Core.DataMining.Clustering.Cluster.

Integer kddml.Core.DataMining.Clustering.ClusterManager.getSize  ) 
 

Returns the number of cases in the portion of the training data assigned to the cluster during the model build. This is a non-negative value. It can be null.

Returns:
Integer

Implemented in kddml.Core.DataMining.Clustering.Cluster.

void kddml.Core.DataMining.Clustering.ClusterManager.setSize int  num_elements  ) 
 

Sets the number of cases in the portion of the training data assigned to the cluster during the model build. This must be a non-negative value.

Parameters:
num_elements int

Implemented in kddml.Core.DataMining.Clustering.Cluster.

void kddml.Core.DataMining.Clustering.ClusterManager.setCovariancesMatrix CategoryMatrixManager  matrix  ) 
 

Sets the covariance matrix.

Parameters:
matrix CategoryMatrix

Implemented in kddml.Core.DataMining.Clustering.Cluster.

CategoryMatrixManager kddml.Core.DataMining.Clustering.ClusterManager.getCovariancesMatrix  ) 
 

Returns the covariances matrix provided for this cluster. Returns null if no covariances matrix is avaible.

Returns:
CategoryMatrixManager the convariance matrix. Can be null.

Implemented in kddml.Core.DataMining.Clustering.Cluster.

ClusterStatisticManager kddml.Core.DataMining.Clustering.ClusterManager.getClusterStatistic  ) 
 

Returns the cluster distribution. Can be null, for example for center-based clustering.

Returns:
ClusterStatisticManager

Implemented in kddml.Core.DataMining.Clustering.Cluster.

abstract Object kddml.Core.DataMining.Clustering.ClusterManager.getSeedAsInstance  )  throws ClusteringModelException [pure virtual]
 

Returns the representative cluster seed as instance. This depends on the type of clustering.

Exceptions:
ClusteringModelException 
Returns:
Object

Implemented in kddml.Core.DataMining.Clustering.CentroidBasedCluster, and kddml.Core.DataMining.Clustering.DistributionBasedCluster.

abstract double [] kddml.Core.DataMining.Clustering.ClusterManager.getSeedCoordinate  )  throws ClusteringModelException [pure virtual]
 

Returns the seed coordinate as array of normalized doubles in respect on the ClusterDescription fields.

Exceptions:
ClusteringModelException 
Returns:
double[]

Implemented in kddml.Core.DataMining.Clustering.CentroidBasedCluster, and kddml.Core.DataMining.Clustering.DistributionBasedCluster.

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

Returns true if the clustering is distribution-based.

Returns:
boolean

Implemented in kddml.Core.DataMining.Clustering.CentroidBasedCluster, and kddml.Core.DataMining.Clustering.DistributionBasedCluster.

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

Returns true if the clustering is center-based.

Returns:
boolean

Implemented in kddml.Core.DataMining.Clustering.CentroidBasedCluster, and kddml.Core.DataMining.Clustering.DistributionBasedCluster.

void kddml.Core.DataMining.Clustering.ClusterManager.setClusterStatistic ClusterStatisticManager  statistics  ) 
 

Sets the cluster statistics. This field is optional for center-based clustering and it is required for distribution-based clustering.

Parameters:
statistics ClusterStatisticManager

Implemented in kddml.Core.DataMining.Clustering.Cluster.


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