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kddml.Core.DataMining.Clustering.ContinuousClusteringField Class Reference

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

kddml.Core.DataMining.Clustering.ClusteringField kddml.Core.DataMining.Clustering.ContinuousClusteringFieldManager kddml.Core.DataMining.Clustering.ClusteringFieldManager kddml.Core.DataMining.Clustering.ClusteringFieldManager List of all members.

Public Member Functions

 ContinuousClusteringField (String name, AttributeComparisonMeasure func, NumericalStatisticManager stat)
 ContinuousClusteringField (String name, AttributeComparisonMeasure func)
double normalize (double value) throws ClusteringModelException
double denormalize (double value) throws ClusteringModelException
int getNumberOfPoints ()
boolean isContinuous ()
String toString ()

Detailed Description

A continuous clustering field. This field is normalized.

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.ContinuousClusteringField.ContinuousClusteringField String  name,
AttributeComparisonMeasure  func,
NumericalStatisticManager  stat
 

Constructor given the attribute statistics.

Parameters:
name String the field name as in MiningSchema.
func AttributeComparisonMeasure the attribute comparison measure. Can be null, for example when a distribution-based function is used.
stat NumericalStatisticManager

kddml.Core.DataMining.Clustering.ContinuousClusteringField.ContinuousClusteringField String  name,
AttributeComparisonMeasure  func
 

Empty constructor. Build a new continuous clustering field with an empty normalization matrix.

Parameters:
name String
func AttributeComparisonMeasure


Member Function Documentation

double kddml.Core.DataMining.Clustering.ContinuousClusteringField.normalize double  value  )  throws ClusteringModelException
 

Normalizes the input value using the normalization matrix.

Parameters:
value double
Exceptions:
ClusteringModelException if the normalization matrix is empty.
Returns:
double a value between 0 and 1.

Implements kddml.Core.DataMining.Clustering.ContinuousClusteringFieldManager.

double kddml.Core.DataMining.Clustering.ContinuousClusteringField.denormalize double  value  )  throws ClusteringModelException
 

De-normalizes the input value using the normalization matrix.

Parameters:
value double a value between 0 and 1.
Exceptions:
ClusteringModelException if the normalization matrix is empty.
Returns:
double

Implements kddml.Core.DataMining.Clustering.ContinuousClusteringFieldManager.

int kddml.Core.DataMining.Clustering.ContinuousClusteringField.getNumberOfPoints  ) 
 

Returns the number of points used for the normalization.

Returns:
int

Implements kddml.Core.DataMining.Clustering.ContinuousClusteringFieldManager.

boolean kddml.Core.DataMining.Clustering.ContinuousClusteringField.isContinuous  )  [virtual]
 

Returns true if the field is continuous. Returns false if it is discrete.

Returns:
boolean true.

Implements kddml.Core.DataMining.Clustering.ClusteringFieldManager.

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

Returns a representation of this object as string.

Returns:
String

Reimplemented from kddml.Core.DataMining.Clustering.ClusteringField.


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