Class CasesOp

Provides outgoing messages for Cases(Boolean), given random arguments to the function.

Inheritance

Object

CasesOp

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(Gate), "Cases", new Type[]{typeof(bool)})]
[Quality(QualityBand.Mature)]
public static class CasesOp

Methods

AverageLogFactor(IList<Bernoulli>, Bernoulli)

Evidence message for VMP.

Declaration

public static double AverageLogFactor(IList<Bernoulli> cases, Bernoulli b)

Parameters

Type	Name	Description
IList<Bernoulli>	cases	Incoming message from cases. Must be a proper distribution. If any element is uniform, the result will be uniform.
Bernoulli	b	Incoming message from b.

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	cases is not a proper distribution.

BAverageConditional(IList<Bernoulli>)

EP message to b.

Declaration

public static Bernoulli BAverageConditional(IList<Bernoulli> cases)

Parameters

Type	Name	Description
IList<Bernoulli>	cases	Incoming message from cases. Must be a proper distribution. If any element is uniform, the result will be uniform.

Returns

Type	Description
Bernoulli	The outgoing EP message to the b argument.

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	cases is not a proper distribution.

BAverageLogarithm(IList<Bernoulli>)

VMP message to b.

Declaration

public static Bernoulli BAverageLogarithm(IList<Bernoulli> cases)

Parameters

Type	Name	Description
IList<Bernoulli>	cases	Incoming message from cases. Must be a proper distribution. If any element is uniform, the result will be uniform.

Returns

Type	Description
Bernoulli	The outgoing VMP message to the b argument.

Remarks

The outgoing message is the factor viewed as a function of b with cases integrated out. The formula is sum_cases p(cases) factor(cases,b).

Exceptions

Type	Condition
ImproperMessageException	cases is not a proper distribution.

CasesAverageConditional<BernoulliList>(Bernoulli, BernoulliList)

EP message to cases.

Declaration

public static BernoulliList CasesAverageConditional<BernoulliList>(Bernoulli b, BernoulliList result)
    where BernoulliList : IList<Bernoulli>

Parameters

Type	Name	Description
Bernoulli	b	Incoming message from b.
BernoulliList	result	Modified to contain the outgoing message.

Returns

Type	Description
BernoulliList	result

Type Parameters

Name	Description
BernoulliList	The type of the outgoing message.

Remarks

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

CasesAverageConditionalInit()

Declaration

public static DistributionStructArray<Bernoulli, bool> CasesAverageConditionalInit()

Returns

Type	Description
DistributionStructArray<Bernoulli, Boolean>

Remarks

CasesAverageLogarithm<BernoulliList>(Bernoulli, BernoulliList)

VMP message to cases.

Declaration

public static BernoulliList CasesAverageLogarithm<BernoulliList>(Bernoulli b, BernoulliList result)
    where BernoulliList : IList<Bernoulli>

Parameters

Type	Name	Description
Bernoulli	b	Incoming message from b.
BernoulliList	result	Modified to contain the outgoing message.

Returns

Type	Description
BernoulliList	result

Type Parameters

Name	Description
BernoulliList	The type of the outgoing message.

Remarks

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

CasesAverageLogarithmInit()

Declaration

public static DistributionStructArray<Bernoulli, bool> CasesAverageLogarithmInit()

Returns

Type	Description
DistributionStructArray<Bernoulli, Boolean>

Remarks

CasesDeriv<DistributionType>(DistributionType)

Declaration

public static DistributionType CasesDeriv<DistributionType>(DistributionType result)
    where DistributionType : SettableToUniform

Parameters

Type	Name	Description
DistributionType	result

Returns

Type	Description
DistributionType

Type Parameters

Name	Description
DistributionType

LogEvidenceRatio(IList<Bernoulli>, Bernoulli)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(IList<Bernoulli> cases, Bernoulli b)

Parameters

Type	Name	Description
IList<Bernoulli>	cases	Incoming message from cases.
Bernoulli	b	Incoming message from b.

Returns

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

Remarks

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

LogEvidenceRatio(IList<Bernoulli>, Boolean)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(IList<Bernoulli> cases, bool b)

Parameters

Type	Name	Description
IList<Bernoulli>	cases	Incoming message from cases.
Boolean	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(sum_(cases) p(cases) factor(cases,b) / sum_cases p(cases) messageTo(cases)). Adding up these values across all factors and variables gives the log-evidence estimate for EP.