Class %DeepSee.extensions.clusters.CalinskiHarabasz

class %DeepSee.extensions.clusters.CalinskiHarabasz extends %RegisteredObject

This class calculates Calinski-Harabasz index. Calinski-Harabasz use the Variance Ratio Criterion which is analogous to F-Statistics to estimate the number of clusters a given data naturally falls into. They minimize Within Cluster/Group Sum of Squares and maximize Between Cluster/Group Sum of Squares.

Validity indices are used in Cluster Validation and determination of the optimal number of clusters.

Inventory

Parameters	Properties	Methods	Queries	Indices	ForeignKeys	Triggers
	3	7

Summary

Properties
Model	SubsetKey	normalize

Methods
%AddToSaveSet	%ClassIsLatestVersion	%ClassName	%ConstructClone
%DispatchClassMethod	%DispatchGetModified	%DispatchGetProperty	%DispatchMethod
%DispatchSetModified	%DispatchSetMultidimProperty	%DispatchSetProperty	%Extends
%GetParameter	%IsA	%IsModified	%New
%NormalizeObject	%ObjectModified	%OriginalNamespace	%PackageName
%RemoveFromSaveSet	%SerializeObject	%SetModified	%ValidateObject
GetSubsetCentroids	calculate	calculateForSample	traceB
traceBSubset	traceW	traceWSubset

Properties

• property Model as AbstractModel;

• property SubsetKey as %Integer;

• property normalize as %Boolean [ InitialExpression = 1 ];

Methods

• method GetSubsetCentroids(Output zz)

• method calculate(Output sc As %Status) as %Double

• method calculateForSample(SampleSize As %Integer, Output sc As %Status) as %Double

• method traceB() as %Double

• method traceBSubset(zz) as %Double

• method traceW() as %Double

• method traceWSubset(zz) as %Double

Class Reference IRIS for UNIX 2024.1.2
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