Class DiscreteFromDiscreteOp

Provides outgoing messages for Discrete(Int32, Matrix), given random arguments to the function.

Inheritance

Object

DiscreteFromDiscreteOp

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(new string[]{"sample", "selector", "probs"}, typeof(Factor), "Discrete", new Type[]{typeof(int), typeof(Matrix)})]
[Quality(QualityBand.Experimental)]
public static class DiscreteFromDiscreteOp

Methods

LogAverageFactor(Discrete, Discrete, Matrix)

Evidence message for EP.

Declaration

public static double LogAverageFactor(Discrete sample, Discrete selector, Matrix probs)

Parameters

Type	Name	Description
Discrete	sample	Incoming message from `sample`.
Discrete	selector	Incoming message from `selector`.
Matrix	probs	Constant value for `probs`.

Returns

Type	Description
Double	Logarithm of the factor's average value across the given argument distributions.

Remarks

The formula for the result is log(sum_(sample,selector) p(sample,selector) factor(sample,selector,probs)).

LogEvidenceRatio(Discrete, Discrete, Matrix)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(Discrete sample, Discrete selector, Matrix probs)

Parameters

Type	Name	Description
Discrete	sample	Incoming message from `sample`.
Discrete	selector	Incoming message from `selector`.
Matrix	probs	Constant value for `probs`.

Returns

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

Remarks

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

SampleAverageConditional(Discrete, Matrix, Discrete)

EP message to sample.

Declaration

public static Discrete SampleAverageConditional(Discrete selector, Matrix probs, Discrete result)

Parameters

Type	Name	Description
Discrete	selector	Incoming message from `selector`.
Matrix	probs	Constant value for `probs`.
Discrete	result	Modified to contain the outgoing message.

Returns

Type	Description
Discrete	`result`

Remarks

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

SelectorAverageConditional(Discrete, Matrix, Discrete)

EP message to selector.

Declaration

public static Discrete SelectorAverageConditional(Discrete sample, Matrix probs, Discrete result)

Parameters

Type	Name	Description
Discrete	sample	Incoming message from `sample`.
Matrix	probs	Constant value for `probs`.
Discrete	result	Modified to contain the outgoing message.

Returns

Type	Description
Discrete	`result`

Remarks

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