Class LogisticOp_JJ96

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

Inheritance

Object

LogisticOp_JJ96

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(MMath), "Logistic", new Type[]{typeof(double)})]
[Quality(QualityBand.Preview)]
public class LogisticOp_JJ96

Remarks

Uses the Jaakkola and Jordan (1996) bound.

Methods

AverageLogFactor(Beta, Gaussian, Beta)

Evidence message for VMP.

Declaration

public static double AverageLogFactor(Beta logistic, Gaussian x, Beta to_logistic)

Parameters

Type	Name	Description
Beta	logistic	Incoming message from logistic.
Gaussian	x	Incoming message from x. Must be a proper distribution. If uniform, the result will be uniform.
Beta	to_logistic	Previous outgoing message to logistic.

Returns

Type	Description
Double	Zero.

Remarks

In Variational Message Passing, the evidence contribution of a deterministic factor is zero. Adding up these values across all factors and variables gives the log-evidence estimate for VMP.

Exceptions

Type	Condition
ImproperMessageException	x is not a proper distribution.

LogisticAverageLogarithm(Gaussian)

VMP message to logistic.

Declaration

public static Beta LogisticAverageLogarithm(Gaussian x)

Parameters

Type	Name	Description
Gaussian	x	Incoming message from x. Must be a proper distribution. If uniform, the result will be uniform.

Returns

Type	Description
Beta	The outgoing VMP message to the logistic argument.

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	x is not a proper distribution.

XAverageLogarithm(Beta, Gaussian, Gaussian)

VMP message to x.

Declaration

public static Gaussian XAverageLogarithm(Beta logistic, Gaussian x, Gaussian result)

Parameters

Type	Name	Description
Beta	logistic	Incoming message from logistic. Must be a proper distribution. If uniform, the result will be uniform.
Gaussian	x	Incoming message from x. Must be a proper distribution. If uniform, the result will be uniform.
Gaussian	result	Modified to contain the outgoing message.

Returns

Type	Description
Gaussian	result

Remarks

The outgoing message is the factor viewed as a function of x with logistic integrated out. The formula is sum_logistic p(logistic) factor(logistic,x).

Exceptions

Type	Condition
ImproperMessageException	logistic is not a proper distribution.
ImproperMessageException	x is not a proper distribution.