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

SQL Table Name: %DeepSee_extensions_utils.LDA

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

Property Inventory (Including Private)

Method Inventory (Including Private)

Properties (Including Private)

property Confusion [ MultiDimensional ];
Property methods: ConfusionDisplayToLogical(), ConfusionGet(), ConfusionIsValid(), ConfusionLogicalToDisplay(), ConfusionLogicalToOdbc(), ConfusionNormalize(), ConfusionSet()
property Dim as %Integer;
Property methods: DimDisplayToLogical(), DimGet(), DimGetStored(), DimIsValid(), DimLogicalToDisplay(), DimNormalize(), DimSet()
property GroupMean as %Double [ MultiDimensional ];
Property methods: GroupMeanDisplayToLogical(), GroupMeanGet(), GroupMeanIsValid(), GroupMeanLogicalToDisplay(), GroupMeanNormalize(), GroupMeanOdbcToLogical(), GroupMeanSet()
property Groups [ MultiDimensional ];
Property methods: GroupsDisplayToLogical(), GroupsGet(), GroupsIsValid(), GroupsLogicalToDisplay(), GroupsLogicalToOdbc(), GroupsNormalize(), GroupsSet()
property NGroups as %Integer;
Property methods: NGroupsDisplayToLogical(), NGroupsGet(), NGroupsGetStored(), NGroupsIsValid(), NGroupsLogicalToDisplay(), NGroupsNormalize(), NGroupsSet()
property Name as %String (MAXLEN = 256) [ Required ];
Property methods: NameDisplayToLogical(), NameGet(), NameGetStored(), NameIdxCheck(), NameIdxCheckUnique(), NameIdxDelete(), NameIdxExists(), NameIdxOpen(), NameIdxSQLCheckUnique(), NameIdxSQLExists(), NameIdxSQLFindPKeyByConstraint(), NameIdxSQLFindRowIDByConstraint(), NameIsValid(), NameLogicalToDisplay(), NameLogicalToOdbc(), NameNormalize(), NameSet()
property PooledInverseCovariance as %Double [ MultiDimensional ];
Property methods: PooledInverseCovarianceDisplayToLogical(), PooledInverseCovarianceGet(), PooledInverseCovarianceIsValid(), PooledInverseCovarianceLogicalToDisplay(), PooledInverseCovarianceNormalize(), PooledInverseCovarianceOdbcToLogical(), PooledInverseCovarianceSet()
property Probability as %Double [ MultiDimensional ];
Property methods: ProbabilityDisplayToLogical(), ProbabilityGet(), ProbabilityIsValid(), ProbabilityLogicalToDisplay(), ProbabilityNormalize(), ProbabilityOdbcToLogical(), ProbabilitySet()
property UseMahalanobisDistance as %Boolean [ InitialExpression = 0 ];
Property methods: UseMahalanobisDistanceDisplayToLogical(), UseMahalanobisDistanceGet(), UseMahalanobisDistanceGetStored(), UseMahalanobisDistanceIsValid(), UseMahalanobisDistanceLogicalToDisplay(), UseMahalanobisDistanceNormalize(), UseMahalanobisDistanceSet()

Methods (Including Private)

private method %OnNew(name As %String) as %Status
This callback method is invoked by the %New() method to provide notification that a new instance of an object is being created.

If this method returns an error then the object will not be created.

It is passed the arguments provided in the %New call. When customizing this method, override the arguments with whatever variables and types you expect to receive from %New(). For example, if you're going to call %New, passing 2 arguments, %OnNew's signature could be:

Method %OnNew(dob as %Date = "", name as %Name = "") as %Status If instead of returning a %Status code this returns an oref and this oref is a subclass of the current class then this oref will be the one returned to the caller of %New method.

private method %OnOpen() as %Status
This callback method is invoked by the %Open() method to provide notification that the object specified by oid is being opened.

If this method returns an error then the object will not be opened.

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
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