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kddml.Core.DataMining.Clustering.ClusteringField Class Reference

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

kddml.Core.DataMining.Clustering.ClusteringFieldManager kddml.Core.DataMining.Clustering.ContinuousClusteringField kddml.Core.DataMining.Clustering.DiscreteClusteringField List of all members.

Public Member Functions

 ClusteringField (String name, AttributeComparisonMeasure func)
String getFieldName ()
void setFieldWeight (double weight)
Double getFieldWeight ()
void setSimilarityScale (double sim)
Double getSimilarityScale ()
String toString ()
AttributeComparisonMeasure getFieldComparisonFunction ()

Detailed Description

This class represents a single clustering field, as used in the ClusterDescription. A ClusteringField consists of four major parts:
  1. the name that refere a mining schema field;
  2. a field weight that is the importance factor for the field. This field weight is used in the comparison functions in order to compute the comparison measure. The default value is 1.0;
  3. the similarity scale that is the distance such that similarity becomes 0.5.
  4. the attribute comparison measure that is a function of taking two field values and a similarityScale to define similarity/distance. It can be null, for example when a distribution-based function is used.
Other features depend on the type of clustering field. For continuous clustering fields a normalization matrix is given. For discrete clustering fields, a list of categories is given.

Author:
Andrea Romei.


Constructor & Destructor Documentation

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

Constructor with the field name and the attribute comparison measure.

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


Member Function Documentation

String kddml.Core.DataMining.Clustering.ClusteringField.getFieldName  ) 
 

Returns the field name as in MiningSchema.

Returns:
String

Implements kddml.Core.DataMining.Clustering.ClusteringFieldManager.

void kddml.Core.DataMining.Clustering.ClusteringField.setFieldWeight double  weight  ) 
 

Sets the field weight.

Parameters:
weight double

Implements kddml.Core.DataMining.Clustering.ClusteringFieldManager.

Double kddml.Core.DataMining.Clustering.ClusteringField.getFieldWeight  ) 
 

Returns the field weight or null if no field weight is used.

Returns:
Double can be null.

Implements kddml.Core.DataMining.Clustering.ClusteringFieldManager.

void kddml.Core.DataMining.Clustering.ClusteringField.setSimilarityScale double  sim  ) 
 

Sets the similarity scale.

Parameters:
sim double a value between 0 and 1.

Implements kddml.Core.DataMining.Clustering.ClusteringFieldManager.

Double kddml.Core.DataMining.Clustering.ClusteringField.getSimilarityScale  ) 
 

Returns the similarity scale of null if no similarity scale is used.

Returns:
Double a value between 0 and 1 or null.

Implements kddml.Core.DataMining.Clustering.ClusteringFieldManager.

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

Returns a representation of this field as string.

Returns:
String

Reimplemented in kddml.Core.DataMining.Clustering.ContinuousClusteringField, and kddml.Core.DataMining.Clustering.DiscreteClusteringField.

AttributeComparisonMeasure kddml.Core.DataMining.Clustering.ClusteringField.getFieldComparisonFunction  ) 
 

Returns the attribute comparison measure or null if no attribute comparison measure is used.

Returns:
AttributeComparisonMeasure can be null.

Implements kddml.Core.DataMining.Clustering.ClusteringFieldManager.


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