Class CutOp<T>

Inheritance

Object

CutOp<T>

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(Cut), "Backward<>", new Type[]{})]
[Quality(QualityBand.Preview)]
public static class CutOp<T>

Type Parameters

Name	Description
T	The type of the variable being copied.

Methods

BackwardAverageConditional(T)

EP message to backward.

Declaration

public static T BackwardAverageConditional(T Value)

Parameters

Type	Name	Description
T	Value	Incoming message from value.

Returns

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

Remarks

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

BackwardAverageConditional<TDist>(TDist)

EP message to backward.

Declaration

public static TDist BackwardAverageConditional<TDist>(TDist Value)
    where TDist : IDistribution<T>

Parameters

Type	Name	Description
TDist	Value	Incoming message from value.

Returns

Type	Description
TDist	The outgoing EP message to the backward argument.

Type Parameters

Name	Description
TDist	The type of the distribution over the variable being copied.

Remarks

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

BackwardAverageLogarithm(T)

VMP message to backward.

Declaration

public static T BackwardAverageLogarithm(T Value)

Parameters

Type	Name	Description
T	Value	Incoming message from value.

Returns

Type	Description
T	The outgoing VMP message to the backward argument.

Remarks

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

BackwardAverageLogarithm<TDist>(TDist)

VMP message to backward.

Declaration

public static TDist BackwardAverageLogarithm<TDist>(TDist Value)
    where TDist : IDistribution<T>

Parameters

Type	Name	Description
TDist	Value	Incoming message from value.

Returns

Type	Description
TDist	The outgoing VMP message to the backward argument.

Type Parameters

Name	Description
TDist	The type of the distribution over the variable being copied.

Remarks

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

ValueAverageConditional<TDist>(TDist)

EP message to value.

Declaration

public static TDist ValueAverageConditional<TDist>(TDist result)
    where TDist : IDistribution<T>

Parameters

Type	Name	Description
TDist	result	Modified to contain the outgoing message.

Returns

Type	Description
TDist	result

Type Parameters

Name	Description
TDist	The type of the distribution over the variable being copied.

Remarks

The outgoing message is the factor viewed as a function of value conditioned on the given values.

ValueAverageLogarithm<TDist>(TDist)

VMP message to value.

Declaration

public static TDist ValueAverageLogarithm<TDist>(TDist result)
    where TDist : IDistribution<T>

Parameters

Type	Name	Description
TDist	result	Modified to contain the outgoing message.

Returns

Type	Description
TDist	result

Type Parameters

Name	Description
TDist	The type of the distribution over the variable being copied.

Remarks

The outgoing message is the factor viewed as a function of value conditioned on the given values.