Inheritance diagram for kddml.Core.DataMining.Clustering.EM_DISTANCE:
Public Member Functions | |
EM_DISTANCE (double[] cluster_priors) | |
double[] | getDistributionProbability (Cluster[] clusters, Instance instance) throws ClusteringModelException |
String | getFunctionName () |
Protected Member Functions | |
Element | toXML () |
Package Attributes | |
double[] | priors |
Static Package Attributes | |
static final double | log2 = Math.log(2) |
static final double | m_normConst = Math.log(Math.sqrt(2 * Math.PI)) |
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 prior probability for each cluster.
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Given an input instance, returns a distribution probability in which the i-esim array location contains the probability that the instance belongs to the cluster i.
Implements kddml.Core.DataMining.Clustering.DistributionBasedComparisonMeasure. |
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Returns the function name as in PMML.
Implements kddml.Core.DataMining.Clustering.ComparisonMeasure. |
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Returns a representation of this function as PMML element.
Implements kddml.Core.DataMining.Clustering.ComparisonMeasure. |
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The natural logarithm of 2. |
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Constant for normal distribution. |
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Priors probability. |