Class DoubleMinusEvidenceOp

Provides outgoing messages for Difference(Double, Double), given random arguments to the function.

Inheritance

Object

DoubleMinusEvidenceOp

Inherited Members

Object.Equals(Object)

Object.Equals(Object, Object)

Object.GetHashCode()

Object.GetType()

Object.MemberwiseClone()

Object.ReferenceEquals(Object, Object)

Object.ToString()

Namespace: Microsoft.ML.Probabilistic.Factors

Assembly: Microsoft.ML.Probabilistic.dll

Syntax

[FactorMethod(typeof(Factor), "Difference", new Type[]{typeof(double), typeof(double)})]
[Quality(QualityBand.Stable)]
public static class DoubleMinusEvidenceOp

Methods

LogEvidenceRatio(Gaussian)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(Gaussian difference)

Parameters

Type	Name	Description
Gaussian	difference	Incoming message from difference.

Returns

Type	Description
Double	Logarithm of the factor's contribution the EP model evidence.

Remarks

The formula for the result is log(sum_(difference) p(difference) factor(difference,a,b) / sum_difference p(difference) messageTo(difference)). Adding up these values across all factors and variables gives the log-evidence estimate for EP.

LogEvidenceRatio(Double, Gaussian, Gaussian)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(double difference, Gaussian a, Gaussian to_a)

Parameters

Type	Name	Description
Double	difference	Constant value for difference.
Gaussian	a	Incoming message from a.
Gaussian	to_a	Outgoing message to a.

Returns

Type	Description
Double	Logarithm of the factor's contribution the EP model evidence.

Remarks

The formula for the result is log(sum_(a) p(a) factor(difference,a,b)). Adding up these values across all factors and variables gives the log-evidence estimate for EP.

LogEvidenceRatio(Double, Double, Gaussian, Gaussian)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(double difference, double a, Gaussian b, Gaussian to_b)

Parameters

Type	Name	Description
Double	difference	Constant value for difference.
Double	a	Constant value for a.
Gaussian	b	Incoming message from b.
Gaussian	to_b	Outgoing message to b.

Returns

Type	Description
Double	Logarithm of the factor's contribution the EP model evidence.

Remarks

The formula for the result is log(sum_(b) p(b) factor(difference,a,b)). Adding up these values across all factors and variables gives the log-evidence estimate for EP.

LogEvidenceRatio(Double, Double, Double)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(double difference, double a, double b)

Parameters

Type	Name	Description
Double	difference	Constant value for difference.
Double	a	Constant value for a.
Double	b	Constant value for b.

Returns

Type	Description
Double	Logarithm of the factor's contribution the EP model evidence.

Remarks

The formula for the result is log(factor(difference,a,b)). Adding up these values across all factors and variables gives the log-evidence estimate for EP.