Class BernoulliIntegerSubsetFromBeta

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

Inheritance

Object

BernoulliIntegerSubsetFromBeta

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(BernoulliIntegerSubset), "Sample", new Type[]{typeof(ISparseList<double>)})]
[Quality(QualityBand.Preview)]
public class BernoulliIntegerSubsetFromBeta

Methods

AverageLogFactor(BernoulliIntegerSubset, ISparseList<Double>)

Evidence message for VMP.

Declaration

public static double AverageLogFactor(BernoulliIntegerSubset sample, ISparseList<double> probTrue)

Parameters

Type	Name	Description
BernoulliIntegerSubset	sample	Incoming message from sample.
ISparseList<Double>	probTrue	Constant value for probTrue.

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,probTrue)). Adding up these values across all factors and variables gives the log-evidence estimate for VMP.

AverageLogFactor(BernoulliIntegerSubset, SparseBetaList)

Evidence message for VMP.

Declaration

public static double AverageLogFactor(BernoulliIntegerSubset sample, SparseBetaList probTrue)

Parameters

Type	Name	Description
BernoulliIntegerSubset	sample	Incoming message from sample.
SparseBetaList	probTrue	Incoming message from probTrue. Must be a proper distribution. If any element is uniform, the result will be uniform.

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,probTrue) p(sample,probTrue) log(factor(sample,probTrue)). Adding up these values across all factors and variables gives the log-evidence estimate for VMP.

Exceptions

Type	Condition
ImproperMessageException	probTrue is not a proper distribution.

AverageLogFactor(IList<Int32>, ISparseList<Double>)

Evidence message for VMP.

Declaration

public static double AverageLogFactor(IList<int> sample, ISparseList<double> probTrue)

Parameters

Type	Name	Description
IList<Int32>	sample	Constant value for sample.
ISparseList<Double>	probTrue	Constant value for probTrue.

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,probTrue)). Adding up these values across all factors and variables gives the log-evidence estimate for VMP.

AverageLogFactor(IList<Int32>, SparseBetaList)

Evidence message for VMP.

Declaration

public static double AverageLogFactor(IList<int> sample, SparseBetaList probTrue)

Parameters

Type	Name	Description
IList<Int32>	sample	Constant value for sample.
SparseBetaList	probTrue	Incoming message from probTrue. Must be a proper distribution. If any element is uniform, the result will be uniform.

Returns

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

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	probTrue is not a proper distribution.

LogAverageFactor(BernoulliIntegerSubset, BernoulliIntegerSubset)

Evidence message for EP.

Declaration

public static double LogAverageFactor(BernoulliIntegerSubset sample, BernoulliIntegerSubset to_sample)

Parameters

Type	Name	Description
BernoulliIntegerSubset	sample	Incoming message from sample.
BernoulliIntegerSubset	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,probTrue)).

LogAverageFactor(IList<Int32>, ISparseList<Double>)

Evidence message for EP.

Declaration

public static double LogAverageFactor(IList<int> sample, ISparseList<double> probTrue)

Parameters

Type	Name	Description
IList<Int32>	sample	Constant value for sample.
ISparseList<Double>	probTrue	Constant value for probTrue.

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,probTrue)).

LogAverageFactor(IList<Int32>, SparseBetaList)

Evidence message for EP.

Declaration

public static double LogAverageFactor(IList<int> sample, SparseBetaList probTrue)

Parameters

Type	Name	Description
IList<Int32>	sample	Constant value for sample.
SparseBetaList	probTrue	Incoming message from probTrue.

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_(probTrue) p(probTrue) factor(sample,probTrue)).

LogEvidenceRatio(BernoulliIntegerSubset, ISparseList<Double>)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(BernoulliIntegerSubset sample, ISparseList<double> probTrue)

Parameters

Type	Name	Description
BernoulliIntegerSubset	sample	Incoming message from sample.
ISparseList<Double>	probTrue	Constant value for probTrue.

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,probTrue) / sum_sample p(sample) messageTo(sample)). Adding up these values across all factors and variables gives the log-evidence estimate for EP.

LogEvidenceRatio(BernoulliIntegerSubset, SparseBetaList)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(BernoulliIntegerSubset sample, SparseBetaList probTrue)

Parameters

Type	Name	Description
BernoulliIntegerSubset	sample	Incoming message from sample.
SparseBetaList	probTrue	Incoming message from probTrue.

Returns

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

Remarks

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

LogEvidenceRatio(IList<Int32>, ISparseList<Double>)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(IList<int> sample, ISparseList<double> probTrue)

Parameters

Type	Name	Description
IList<Int32>	sample	Constant value for sample.
ISparseList<Double>	probTrue	Constant value for probTrue.

Returns

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

Remarks

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

LogEvidenceRatio(IList<Int32>, SparseBetaList)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(IList<int> sample, SparseBetaList probTrue)

Parameters

Type	Name	Description
IList<Int32>	sample	Constant value for sample.
SparseBetaList	probTrue	Incoming message from probTrue.

Returns

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

Remarks

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

ProbTrueAverageConditional(BernoulliIntegerSubset, SparseBetaList, SparseBetaList)

EP message to probTrue.

Declaration

public static SparseBetaList ProbTrueAverageConditional(BernoulliIntegerSubset sample, SparseBetaList probTrue, SparseBetaList result)

Parameters

Type	Name	Description
BernoulliIntegerSubset	sample	Incoming message from sample. Must be a proper distribution. If any element is uniform, the result will be uniform.
SparseBetaList	probTrue	Incoming message from probTrue.
SparseBetaList	result	Modified to contain the outgoing message.

Returns

Type	Description
SparseBetaList	result

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	sample is not a proper distribution.

ProbTrueAverageConditional(IList<Int32>, SparseBetaList)

EP message to probTrue.

Declaration

public static SparseBetaList ProbTrueAverageConditional(IList<int> sample, SparseBetaList result)

Parameters

Type	Name	Description
IList<Int32>	sample	Constant value for sample.
SparseBetaList	result	Modified to contain the outgoing message.

Returns

Type	Description
SparseBetaList	result

Remarks

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

ProbTrueAverageLogarithm(BernoulliIntegerSubset, SparseBetaList)

VMP message to probTrue.

Declaration

public static SparseBetaList ProbTrueAverageLogarithm(BernoulliIntegerSubset sample, SparseBetaList result)

Parameters

Type	Name	Description
BernoulliIntegerSubset	sample	Incoming message from sample.
SparseBetaList	result	Modified to contain the outgoing message.

Returns

Type	Description
SparseBetaList	result

Remarks

The outgoing message is the exponential of the average log-factor value, where the average is over all arguments except probTrue. The formula is exp(sum_(sample) p(sample) log(factor(sample,probTrue))).

ProbTrueAverageLogarithm(IList<Int32>, SparseBetaList)

VMP message to probTrue.

Declaration

public static SparseBetaList ProbTrueAverageLogarithm(IList<int> sample, SparseBetaList result)

Parameters

Type	Name	Description
IList<Int32>	sample	Constant value for sample.
SparseBetaList	result	Modified to contain the outgoing message.

Returns

Type	Description
SparseBetaList	result

Remarks

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

ProbTrueConditional(IList<Int32>, SparseBetaList)

Gibbs message to probTrue.

Declaration

public static SparseBetaList ProbTrueConditional(IList<int> sample, SparseBetaList result)

Parameters

Type	Name	Description
IList<Int32>	sample	Constant value for sample.
SparseBetaList	result	Modified to contain the outgoing message.

Returns

Type	Description
SparseBetaList	result

Remarks

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

SampleAverageConditional(ISparseList<Double>, BernoulliIntegerSubset)

EP message to sample.

Declaration

public static BernoulliIntegerSubset SampleAverageConditional(ISparseList<double> probTrue, BernoulliIntegerSubset result)

Parameters

Type	Name	Description
ISparseList<Double>	probTrue	Constant value for probTrue.
BernoulliIntegerSubset	result	Modified to contain the outgoing message.

Returns

Type	Description
BernoulliIntegerSubset	result

Remarks

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

SampleAverageConditional(SparseBetaList, BernoulliIntegerSubset)

EP message to sample.

Declaration

public static BernoulliIntegerSubset SampleAverageConditional(SparseBetaList probTrue, BernoulliIntegerSubset result)

Parameters

Type	Name	Description
SparseBetaList	probTrue	Incoming message from probTrue. Must be a proper distribution. If any element is uniform, the result will be uniform.
BernoulliIntegerSubset	result	Modified to contain the outgoing message.

Returns

Type	Description
BernoulliIntegerSubset	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_(probTrue) p(probTrue) factor(sample,probTrue)]/p(sample).

Exceptions

Type	Condition
ImproperMessageException	probTrue is not a proper distribution.

SampleAverageLogarithm(ISparseList<Double>, BernoulliIntegerSubset)

VMP message to sample.

Declaration

public static BernoulliIntegerSubset SampleAverageLogarithm(ISparseList<double> probTrue, BernoulliIntegerSubset result)

Parameters

Type	Name	Description
ISparseList<Double>	probTrue	Constant value for probTrue.
BernoulliIntegerSubset	result	Modified to contain the outgoing message.

Returns

Type	Description
BernoulliIntegerSubset	result

Remarks

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

SampleAverageLogarithm(SparseBetaList, BernoulliIntegerSubset)

VMP message to sample.

Declaration

public static BernoulliIntegerSubset SampleAverageLogarithm(SparseBetaList probTrue, BernoulliIntegerSubset result)

Parameters

Type	Name	Description
SparseBetaList	probTrue	Incoming message from probTrue. Must be a proper distribution. If any element is uniform, the result will be uniform.
BernoulliIntegerSubset	result	Modified to contain the outgoing message.

Returns

Type	Description
BernoulliIntegerSubset	result

Remarks

The outgoing message is the exponential of the average log-factor value, where the average is over all arguments except sample. The formula is exp(sum_(probTrue) p(probTrue) log(factor(sample,probTrue))).

Exceptions

Type	Condition
ImproperMessageException	probTrue is not a proper distribution.

SampleConditional(ISparseList<Double>, BernoulliIntegerSubset)

Gibbs message to sample.

Declaration

public static BernoulliIntegerSubset SampleConditional(ISparseList<double> probTrue, BernoulliIntegerSubset result)

Parameters

Type	Name	Description
ISparseList<Double>	probTrue	Constant value for probTrue.
BernoulliIntegerSubset	result	Modified to contain the outgoing message.

Returns

Type	Description
BernoulliIntegerSubset	result

Remarks

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