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kddml.Core.DataMining.Clustering.ClusterDescription Class Reference

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

kddml.Core.DataMining.Clustering.ClusterDescriptionManager List of all members.

Public Member Functions

 ClusterDescription (DataStatisticsManager stat, AttributeComparisonMeasure[] func, boolean is_centroid_based) throws ClusteringModelException
 ClusterDescription (boolean is_centroid_based)
Enumeration getFields ()
ClusteringFieldManager getField (String name)
int getNumberOfFields ()
void addField (ClusteringFieldManager field)
boolean isCentroidBased ()
String toString ()

Detailed Description

A cluster model basically consists of a set of clusters. For each cluster a center vector can be given. In center-based models a cluster is defined by a vector of center coordinates. Some distance measure is used to determine the nearest center, that is the nearest cluster for a given input record. For distribution-based models, the clusters are defined by their statistics. Some similarity measure is used to determine the best matching cluster for a given record. The center vectors then only approximate the clusters. The ClusterDescription contains the fields as used in center vectors. The fields which are used in the center vectors are normalized, in particular this allows to map categorical input fields to numeric values in center vectors. Other features depend on the type of the cluster field. For each discrete field, the list of categories is reported. For each continuous field, the normalization matrix is given.

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


Constructor & Destructor Documentation

kddml.Core.DataMining.Clustering.ClusterDescription.ClusterDescription DataStatisticsManager  stat,
AttributeComparisonMeasure[]  func,
boolean  is_centroid_based
throws ClusteringModelException
 

Constructor.

Parameters:
stat DataStatisticsManager data statistics on which build the clustering. Cannot be null.
func AttributeComparisonMeasure[] the attribute comparison measures for each clustering fields. Can be null only for a distribution-based clustering that use a distribution-based comparison measure.
is_centroid_based boolean
Exceptions:
ClusteringModelException if the attribute comparison measures and the data statistics do not match.

kddml.Core.DataMining.Clustering.ClusterDescription.ClusterDescription boolean  is_centroid_based  ) 
 

Empty constructor that build a ClusterDescription with no fields.

Parameters:
is_centroid_based boolean true if the clustering is centroid-based.


Member Function Documentation

Enumeration kddml.Core.DataMining.Clustering.ClusterDescription.getFields  ) 
 

Returns an enumeration of all fields.

Returns:
Enumeration return an enumeration of ClusteringField objects.

Implements kddml.Core.DataMining.Clustering.ClusterDescriptionManager.

ClusteringFieldManager kddml.Core.DataMining.Clustering.ClusterDescription.getField String  name  ) 
 

Returns a clustering fields with a specified name. Returns null if the field do not exist.

Parameters:
name String
Returns:
ClusteringFieldManager the clustering field. Can be null.

Implements kddml.Core.DataMining.Clustering.ClusterDescriptionManager.

int kddml.Core.DataMining.Clustering.ClusterDescription.getNumberOfFields  ) 
 

Returns the number of fields.

Returns:
int

Implements kddml.Core.DataMining.Clustering.ClusterDescriptionManager.

void kddml.Core.DataMining.Clustering.ClusterDescription.addField ClusteringFieldManager  field  ) 
 

Adds a new fields to this enumeration.

Parameters:
field ClusteringFieldManager

Implements kddml.Core.DataMining.Clustering.ClusterDescriptionManager.

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

Returns true if the clustering is centroid-based. Returns false otherwise.

Returns:
boolean

Implements kddml.Core.DataMining.Clustering.ClusterDescriptionManager.

String kddml.Core.DataMining.Clustering.ClusterDescription.toString  ) 
 

Returns a representation of this object as string.

Returns:
String


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