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kddml.Core.DataMining.Clustering.CITY_BLOCK Class Reference

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

kddml.Core.DataMining.Clustering.CentroidBasedComparisonMeasure kddml.Core.DataMining.Clustering.ComparisonMeasure List of all members.

Public Member Functions

 CITY_BLOCK (AttributeComparisonMeasure[] attribute_comparison, double[] weights)
 CITY_BLOCK (ClusterDescription cluster_description)
boolean isSimilarityMeasure ()
String getFunctionName ()

Protected Member Functions

double evaluate (double[] x)

Detailed Description

The city block function is an outer function, used to compare two records X, Y, where: The city block distance is defined as:

D = sum (Wi*c(Xi,Yi)).

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.CITY_BLOCK.CITY_BLOCK AttributeComparisonMeasure[]  attribute_comparison,
double[]  weights
 

Constructor given the list of comparison measures. Used for centroid-based clustering only.

Parameters:
attribute_comparison AttributeComparisonMeasure[] the comparison measure for each attribute.
weights double[] the field weight for each attribute. Can be null.

kddml.Core.DataMining.Clustering.CITY_BLOCK.CITY_BLOCK ClusterDescription  cluster_description  ) 
 

Constructor given the centroid description. Used both for centroid-based clustering and distribution-based clustering.

Parameters:
cluster_description ClusterDescription


Member Function Documentation

boolean kddml.Core.DataMining.Clustering.CITY_BLOCK.isSimilarityMeasure  )  [virtual]
 

Returns true if the comparison measure is a similarity function, in which the value returned by the compare method is optimal for greater values. Returns false if the comparison measure is a distance measure, in which the value returned by the compare method is optimal if it is 0.

Returns:
boolean false

Implements kddml.Core.DataMining.Clustering.CentroidBasedComparisonMeasure.

double kddml.Core.DataMining.Clustering.CITY_BLOCK.evaluate double[]  x  )  [protected, virtual]
 

Evaluates the comparison measure given the comparison values for each single attribute (i.e., the values returned by each single inner function).

Parameters:
x double[]
Returns:
double

Implements kddml.Core.DataMining.Clustering.CentroidBasedComparisonMeasure.

String kddml.Core.DataMining.Clustering.CITY_BLOCK.getFunctionName  )  [virtual]
 

Returns the function name as in PMML.

Returns:
String

Implements kddml.Core.DataMining.Clustering.ComparisonMeasure.


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