Inheritance diagram for kddml.Core.DataMining.Clustering.CentroidBasedComparisonMeasure:
Public Member Functions | |
CentroidBasedComparisonMeasure (AttributeComparisonMeasure[] attribute_comparison, double[] weights) | |
CentroidBasedComparisonMeasure (ClusterDescription cluster_description) | |
abstract boolean | isSimilarityMeasure () |
double | compare (ClusterManager cluster, Instance instance) throws ClusteringModelException |
boolean | isCentroidBased () |
AttributeComparisonMeasure[] | getAttributeComparisonMeasure () |
Protected Member Functions | |
abstract double | evaluate (double[] x) |
Element | toXML () |
Title: KDDML
Description: Knowledge Discovery in Database Environment
Copyright: Copyright (c) 2003-2005
Company: Universita' di Pisa - Dipartimento di Informatica
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Constructor given the list of comparison measures. Used for centroid-based clustering only.
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Constructor given the centroid description. Used both for centroid-based clustering and distribution-based clustering.
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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.
Implemented in kddml.Core.DataMining.Clustering.BINARY_SIMILARITY, kddml.Core.DataMining.Clustering.CHEBYCHEV, kddml.Core.DataMining.Clustering.CITY_BLOCK, kddml.Core.DataMining.Clustering.EUCLIDEAN, kddml.Core.DataMining.Clustering.JACCARD, kddml.Core.DataMining.Clustering.MINKOWSKI, kddml.Core.DataMining.Clustering.SIMPLE_MATCHING, kddml.Core.DataMining.Clustering.SQUARED_EUCLIDEAN, and kddml.Core.DataMining.Clustering.TANIMOTO. |
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Compares an input istance with the seed of the cluster. The seed depends on the type of clustering. If the clustering is center-based, the seed is the centroid as instance. If the clustering is distribution-based, the seed is calculated on the statistics associated to the cluster. In particular, for numeric attributes, the mean of cluster instances is used as seed. For discrete attribute, the most probable category is reported as seed.
Reimplemented in kddml.Core.DataMining.Clustering.SIMPLE_MATCHING. |
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Evaluates the comparison measure given the comparison values for each single attribute (i.e., the values returned by each single inner function). This method is implemented in sub-classes.
Implemented in kddml.Core.DataMining.Clustering.BINARY_SIMILARITY, kddml.Core.DataMining.Clustering.CHEBYCHEV, kddml.Core.DataMining.Clustering.CITY_BLOCK, kddml.Core.DataMining.Clustering.EUCLIDEAN, kddml.Core.DataMining.Clustering.JACCARD, kddml.Core.DataMining.Clustering.MINKOWSKI, kddml.Core.DataMining.Clustering.SIMPLE_MATCHING, kddml.Core.DataMining.Clustering.SQUARED_EUCLIDEAN, and kddml.Core.DataMining.Clustering.TANIMOTO. |
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Returns true if the function is related to a centroid-based clustering. Returns true if the function is related to a distribution-based clustering.
Implements kddml.Core.DataMining.Clustering.ComparisonMeasure. |
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Returns the comparison measure for each attribute.
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Returns a representation of this function as PMML element.
Implements kddml.Core.DataMining.Clustering.ComparisonMeasure. |