Class BetaOp

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

Inheritance

Object

BetaOp

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(Beta), "Sample", new Type[]{typeof(double), typeof(double)})]
[Quality(QualityBand.Stable)]
public static class BetaOp

Methods

AverageLogFactor(Beta, Double, Double, Beta)

Evidence message for VMP.

Declaration

public static double AverageLogFactor(Beta sample, double trueCount, double falseCount, Beta to_sample)

Parameters

Type	Name	Description
Beta	sample	Incoming message from sample.
Double	trueCount	Constant value for trueCount.
Double	falseCount	Constant value for falseCount.
Beta	to_sample	Outgoing message to sample.

Returns

Type	Description
Double	Average of the factor's log-value across the given argument distributions.

Remarks

The formula for the result is sum_(sample) p(sample) log(factor(sample,trueCount,falseCount)). Adding up these values across all factors and variables gives the log-evidence estimate for VMP.

AverageLogFactor(Double, Gamma, Double)

Evidence message for VMP.

Declaration

public static double AverageLogFactor(double sample, Gamma trueCount, double falseCount)

Parameters

Type	Name	Description
Double	sample	Constant value for sample.
Gamma	trueCount	Incoming message from trueCount.
Double	falseCount	Constant value for falseCount.

Returns

Type	Description
Double	Average of the factor's log-value across the given argument distributions.

Remarks

The formula for the result is sum_(trueCount) p(trueCount) log(factor(sample,trueCount,falseCount)). Adding up these values across all factors and variables gives the log-evidence estimate for VMP.

AverageLogFactor(Double, Double, Gamma)

Evidence message for VMP.

Declaration

public static double AverageLogFactor(double sample, double trueCount, Gamma falseCount)

Parameters

Type	Name	Description
Double	sample	Constant value for sample.
Double	trueCount	Constant value for trueCount.
Gamma	falseCount	Incoming message from falseCount.

Returns

Type	Description
Double	Average of the factor's log-value across the given argument distributions.

Remarks

The formula for the result is sum_(falseCount) p(falseCount) log(factor(sample,trueCount,falseCount)). Adding up these values across all factors and variables gives the log-evidence estimate for VMP.

AverageLogFactor(Double, Double, Double)

Evidence message for VMP.

Declaration

public static double AverageLogFactor(double sample, double trueCount, double falseCount)

Parameters

Type	Name	Description
Double	sample	Constant value for sample.
Double	trueCount	Constant value for trueCount.
Double	falseCount	Constant value for falseCount.

Returns

Type	Description
Double	Average of the factor's log-value across the given argument distributions.

Remarks

The formula for the result is log(factor(sample,trueCount,falseCount)). Adding up these values across all factors and variables gives the log-evidence estimate for VMP.

FalseCountAverageConditional(Double, Double)

EP message to falseCount.

Declaration

public static Gamma FalseCountAverageConditional(double sample, double trueCount)

Parameters

Type	Name	Description
Double	sample	Constant value for sample.
Double	trueCount	Constant value for trueCount.

Returns

Type	Description
Gamma	The outgoing EP message to the falseCount argument.

Remarks

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

FalseCountAverageLogarithm(Double, Double)

VMP message to falseCount.

Declaration

public static Gamma FalseCountAverageLogarithm(double sample, double trueCount)

Parameters

Type	Name	Description
Double	sample	Constant value for sample.
Double	trueCount	Constant value for trueCount.

Returns

Type	Description
Gamma	The outgoing VMP message to the falseCount argument.

Remarks

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

LogAverageFactor(Beta, Double, Double, Beta)

Evidence message for EP.

Declaration

public static double LogAverageFactor(Beta sample, double trueCount, double falseCount, Beta to_sample)

Parameters

Type	Name	Description
Beta	sample	Incoming message from sample.
Double	trueCount	Constant value for trueCount.
Double	falseCount	Constant value for falseCount.
Beta	to_sample	Outgoing message to sample.

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) p(sample) factor(sample,trueCount,falseCount)).

LogAverageFactor(Double, Double, Double)

Evidence message for EP.

Declaration

public static double LogAverageFactor(double sample, double trueCount, double falseCount)

Parameters

Type	Name	Description
Double	sample	Constant value for sample.
Double	trueCount	Constant value for trueCount.
Double	falseCount	Constant value for falseCount.

Returns

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

Remarks

The formula for the result is log(factor(sample,trueCount,falseCount)).

LogEvidenceRatio(Beta, Double, Double)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(Beta sample, double trueCount, double falseCount)

Parameters

Type	Name	Description
Beta	sample	Incoming message from sample.
Double	trueCount	Constant value for trueCount.
Double	falseCount	Constant value for falseCount.

Returns

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

Remarks

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

LogEvidenceRatio(Double, Gamma, Double)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(double sample, Gamma trueCount, double falseCount)

Parameters

Type	Name	Description
Double	sample	Constant value for sample.
Gamma	trueCount	Incoming message from trueCount.
Double	falseCount	Constant value for falseCount.

Returns

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

Remarks

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

LogEvidenceRatio(Double, Double, Gamma)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(double sample, double trueCount, Gamma falseCount)

Parameters

Type	Name	Description
Double	sample	Constant value for sample.
Double	trueCount	Constant value for trueCount.
Gamma	falseCount	Incoming message from falseCount.

Returns

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

Remarks

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

LogEvidenceRatio(Double, Double, Double)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(double sample, double trueCount, double falseCount)

Parameters

Type	Name	Description
Double	sample	Constant value for sample.
Double	trueCount	Constant value for trueCount.
Double	falseCount	Constant value for falseCount.

Returns

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

Remarks

The formula for the result is log(factor(sample,trueCount,falseCount)). Adding up these values across all factors and variables gives the log-evidence estimate for EP.

SampleAverageConditional(Double, Double)

EP message to sample.

Declaration

public static Beta SampleAverageConditional(double trueCount, double falseCount)

Parameters

Type	Name	Description
Double	trueCount	Constant value for trueCount.
Double	falseCount	Constant value for falseCount.

Returns

Type	Description
Beta	The outgoing EP message to the sample argument.

Remarks

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

SampleAverageLogarithm(Double, Double)

VMP message to sample.

Declaration

public static Beta SampleAverageLogarithm(double trueCount, double falseCount)

Parameters

Type	Name	Description
Double	trueCount	Constant value for trueCount.
Double	falseCount	Constant value for falseCount.

Returns

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

Remarks

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

TrueCountAverageConditional(Double, Double)

EP message to trueCount.

Declaration

public static Gamma TrueCountAverageConditional(double sample, double falseCount)

Parameters

Type	Name	Description
Double	sample	Constant value for sample.
Double	falseCount	Constant value for falseCount.

Returns

Type	Description
Gamma	The outgoing EP message to the trueCount argument.

Remarks

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

TrueCountAverageLogarithm(Double, Double)

VMP message to trueCount.

Declaration

public static Gamma TrueCountAverageLogarithm(double sample, double falseCount)

Parameters

Type	Name	Description
Double	sample	Constant value for sample.
Double	falseCount	Constant value for falseCount.

Returns

Type	Description
Gamma	The outgoing VMP message to the trueCount argument.

Remarks

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