%DeepSee.extensions.clusters.CalinskiHarabasz
class %DeepSee.extensions.clusters.CalinskiHarabasz extends %Library.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.
Property Inventory
Method Inventory
- GetSubsetCentroids()
- calculate()
- calculateForSample()
- traceB()
- traceBSubset()
- traceW()
- traceWSubset()
Properties
property Model as AbstractModel;
Property methods: ModelGet(), ModelGetSwizzled(), ModelIsValid(), ModelNewObject(), ModelSet()
property SubsetKey as %Integer;
Property methods: SubsetKeyDisplayToLogical(), SubsetKeyGet(), SubsetKeyIsValid(), SubsetKeyLogicalToDisplay(), SubsetKeyNormalize(), SubsetKeySet()
property normalize as %Boolean [ InitialExpression = 1 ];
Property methods: normalizeDisplayToLogical(), normalizeGet(), normalizeIsValid(), normalizeLogicalToDisplay(), normalizeNormalize(), normalizeSet()
Methods
method GetSubsetCentroids(Output zz)
method traceB() as %Double
method traceBSubset(zz) as %Double
method traceW() as %Double
method traceWSubset(zz) as %Double
Inherited Members
Inherited 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()