Class %DeepSee.extensions.utils.LDA

persistent class %DeepSee.extensions.utils.LDA extends %Library.Persistent, %DeepSee.extensions.BlackBox

This code serves for calculating a linear discriminant analysis (LDA)

Parameters	Properties	Methods	Queries	Indices	ForeignKeys	Triggers
	9	13		1

Summary

Properties
Confusion	Dim	GroupMean	Groups
NGroups	Name	PooledInverseCovariance	Probability
UseMahalanobisDistance

Methods
%%OIDGet	%AddToSaveSet	%AddToSyncSet	%BMEBuilt
%BuildIndices	%CheckUnique	%ClassIsLatestVersion	%ClassName
%ComposeOid	%ConstructClone	%Delete	%DeleteExtent
%DeleteId	%DispatchClassMethod	%DispatchGetModified	%DispatchGetProperty
%DispatchMethod	%DispatchSetModified	%DispatchSetMultidimProperty	%DispatchSetProperty
%Exists	%ExistsId	%Extends	%GUID
%GUIDSet	%GetLock	%GetParameter	%GetSwizzleObject
%Id	%InsertBatch	%IsA	%IsModified
%KillExtent	%KillExtentData	%LoadFromMemory	%LockExtent
%LockId	%New	%NormalizeObject	%ObjectModified
%Oid	%OnBeforeAddToSync	%OnDetermineClass	%Open
%OpenId	%OriginalNamespace	%PackageName	%PhysicalAddress
%PurgeIndices	%Reload	%RemoveFromSaveSet	%ResolveConcurrencyConflict
%RollBack	%Save	%SaveDirect	%SaveIndices
%SerializeObject	%SetModified	%SortBegin	%SortEnd
%SyncObjectIn	%SyncTransport	%UnlockExtent	%UnlockId
%ValidateObject	Create	GetClassDef	GetDF
GetDataLocation	GetMahalanobisDistance	GetMajorContributors	Test
getConfusionMatrixForTestSet	getCovector	getSensitivity	getSpecificity
predict	printConfusionMatrix

Properties

• property Confusion [ MultiDimensional ];

• property Dim as %Integer;

• property GroupMean as %Double [ MultiDimensional ];

• property Groups [ MultiDimensional ];

• property NGroups as %Integer;

• property Name as %String(MAXLEN=256);

• property PooledInverseCovariance as %Double [ MultiDimensional ];

• property Probability as %Double [ MultiDimensional ];

• property UseMahalanobisDistance as %Boolean [ InitialExpression = 0 ];

Methods

• method Create(N As %Integer, M As %Integer, ByRef data As %Double, ByRef groups As %Integer, p As %Boolean) as %Status

• method GetDF(ByRef x, Output fv, verobse As %Boolean = 1) as %Status

• method GetMahalanobisDistance(ByRef x, Output fv, verobse As %Boolean = 0) as %Status

• method GetMajorContributors(targetPos As %String, targetNeg As %String, margin As %Double, Output listPos As %List, Output listNeg As %List) as %Status

• classmethod Test()

• method getConfusionMatrixForTestSet(rs As %ResultSet, i1 As %Integer, dim As %Integer, Output C, Output r As %Double) as %Status

getConfusionMatrixForTest

• method getCovector(target As %String, Output V) as %Status

• method getSensitivity(g, Output sc As %Status, ByRef confusion="") as %Double

• method getSpecificity(g, Output sc As %Status, ByRef confusion="") as %Double

• method predict(ByRef x, Output sc As %Status, Output maxf As %Double, Output f) as %String

• method printConfusionMatrix(ByRef confusion="") as %Status

Indices

• index (NameIdx on Name) [PrimaryKey,Unique];


[BASEXML] > [%DeepSee] > [extensions] > [utils] > [LDA]		Private Storage