Class VariableOp

Provides outgoing messages for the following factors:

• Variable<T>(T, out T)
• VariableInit<T>(T, T, out T)

, given random arguments to the function.

Inheritance

Object

VariableOp

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(Clone), "Variable<>", new Type[]{}, Default = true)]
[FactorMethod(typeof(Clone), "VariableInit<>", new Type[]{}, Default = true)]
[Quality(QualityBand.Preview)]
public static class VariableOp

Methods

DefAverageConditional<T>(T)

EP message to def.

Declaration

public static T DefAverageConditional<T>(T use)

Parameters

Type	Name	Description
T	use	Incoming message from use.

Returns

Type	Description
T	The outgoing EP message to the def argument.

Type Parameters

Name	Description
T	The type of the marginal of the variable.

Remarks

The outgoing message is a distribution matching the moments of def as the random arguments are varied. The formula is proj[p(def) sum_(use) p(use) factor(use,def,marginal)]/p(def).

LogEvidenceRatio<T>(T)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio<T>(T use)

Parameters

Type	Name	Description
T	use	Incoming message from use.

Returns

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

Type Parameters

Name	Description
T

Remarks

The formula for the result is log(sum_(use) p(use) factor(use,def,marginal) / sum_use p(use) messageTo(use)). Adding up these values across all factors and variables gives the log-evidence estimate for EP.

MarginalAverageConditional<T>(T, T, T)

EP message to marginal.

Declaration

[SkipIfAllUniform]
public static T MarginalAverageConditional<T>(T use, T def, T result)
    where T : SettableToProduct<T>, SettableTo<T>

Parameters

Type	Name	Description
T	use	Incoming message from use.
T	def	Incoming message from def.
T	result	Modified to contain the outgoing message.

Returns

Type	Description
T	result

Type Parameters

Name	Description
T	The type of the marginal of the variable.

Remarks

The outgoing message is a distribution matching the moments of marginal as the random arguments are varied. The formula is proj[p(marginal) sum_(use,def) p(use,def) factor(use,def,marginal)]/p(marginal).

MarginalAverageConditionalInit<T>(T)

Declaration

public static T MarginalAverageConditionalInit<T>(T def)
    where T : ICloneable

Parameters

Type	Name	Description
T	def	Incoming message from def.

Returns

Type	Description
T

Type Parameters

Name	Description
T	The type of the marginal of the variable.

Remarks

UseAverageConditional<T>(T)

EP message to use.

Declaration

public static T UseAverageConditional<T>(T Def)

Parameters

Type	Name	Description
T	Def	Incoming message from def.

Returns

Type	Description
T	The outgoing EP message to the use argument.

Type Parameters

Name	Description
T	The type of the marginal of the variable.

Remarks

The outgoing message is a distribution matching the moments of use as the random arguments are varied. The formula is proj[p(use) sum_(def) p(def) factor(use,def,marginal)]/p(use).