Bernoulli Structure

Infer.NET Documentation

Microsoft Research, Cambridge

Represents a distribution on a binary variable.

Namespace:�MicrosoftResearch.Infer.Distributions
Assembly:�Infer.Runtime (in Infer.Runtime.dll) Version: 2.5.30417.0 (2.5.30417.0)

Syntax

C++

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[SerializableAttribute]
[Quality(QualityBand.Mature)]
public�struct�Bernoulli : IDistribution<bool>, 
	ICloneable, HasPoint<bool>, Diffable, CanGetLogProb<bool>, 
	SettableTo<Bernoulli>, SettableToProduct<Bernoulli>, SettableToProduct<Bernoulli, Bernoulli>, 
	SettableToUniform, SettableToRatio<Bernoulli>, SettableToRatio<Bernoulli, Bernoulli>, 
	SettableToPower<Bernoulli>, SettableToWeightedSum<Bernoulli>, Sampleable<bool>, 
	CanGetMean<double>, CanSetMean<double>, CanGetVariance<double>, 
	CanGetLogAverageOf<Bernoulli>, CanGetLogAverageOfPower<Bernoulli>, CanGetAverageLog<Bernoulli>, 
	CanGetLogNormalizer

[SerializableAttribute]
[Quality(QualityBand.Mature)]
public�struct�Bernoulli : IDistribution<bool>, 
	ICloneable, HasPoint<bool>, Diffable, CanGetLogProb<bool>, 
	SettableTo<Bernoulli>, SettableToProduct<Bernoulli>, SettableToProduct<Bernoulli, Bernoulli>, 
	SettableToUniform, SettableToRatio<Bernoulli>, SettableToRatio<Bernoulli, Bernoulli>, 
	SettableToPower<Bernoulli>, SettableToWeightedSum<Bernoulli>, Sampleable<bool>, 
	CanGetMean<double>, CanSetMean<double>, CanGetVariance<double>, 
	CanGetLogAverageOf<Bernoulli>, CanGetLogAverageOfPower<Bernoulli>, CanGetAverageLog<Bernoulli>, 
	CanGetLogNormalizer

[<SealedAttribute>]
[<SerializableAttribute>]
[<Quality(QualityBand.Mature)>]
type�Bernoulli =  
    struct�
��������interface�IDistribution<bool>
        interface�ICloneable�
��������interface�HasPoint<bool>
        interface�Diffable�
��������interface�CanGetLogProb<bool>
        interface�SettableTo<Bernoulli>
        interface�SettableToProduct<Bernoulli>
        interface�SettableToProduct<Bernoulli, Bernoulli>
        interface�SettableToUniform�
��������interface�SettableToRatio<Bernoulli>
        interface�SettableToRatio<Bernoulli, Bernoulli>
        interface�SettableToPower<Bernoulli>
        interface�SettableToWeightedSum<Bernoulli>
        interface�Sampleable<bool>
        interface�CanGetMean<float>
        interface�CanSetMean<float>
        interface�CanGetVariance<float>
        interface�CanGetLogAverageOf<Bernoulli>
        interface�CanGetLogAverageOfPower<Bernoulli>
        interface�CanGetAverageLog<Bernoulli>
        interface�CanGetLogNormalizer�
����end

[<SealedAttribute>]
[<SerializableAttribute>]
[<Quality(QualityBand.Mature)>]
type�Bernoulli =  
    struct�
��������interface�IDistribution<bool>
        interface�ICloneable�
��������interface�HasPoint<bool>
        interface�Diffable�
��������interface�CanGetLogProb<bool>
        interface�SettableTo<Bernoulli>
        interface�SettableToProduct<Bernoulli>
        interface�SettableToProduct<Bernoulli, Bernoulli>
        interface�SettableToUniform�
��������interface�SettableToRatio<Bernoulli>
        interface�SettableToRatio<Bernoulli, Bernoulli>
        interface�SettableToPower<Bernoulli>
        interface�SettableToWeightedSum<Bernoulli>
        interface�Sampleable<bool>
        interface�CanGetMean<float>
        interface�CanSetMean<float>
        interface�CanGetVariance<float>
        interface�CanGetLogAverageOf<Bernoulli>
        interface�CanGetLogAverageOfPower<Bernoulli>
        interface�CanGetAverageLog<Bernoulli>
        interface�CanGetLogNormalizer�
����end

[SerializableAttribute]
[Quality(QualityBand::Mature)]
public�value class�Bernoulli : IDistribution<bool>, 
	ICloneable, HasPoint<bool>, Diffable, CanGetLogProb<bool>, 
	SettableTo<Bernoulli>, SettableToProduct<Bernoulli>, SettableToProduct<Bernoulli, Bernoulli>, 
	SettableToUniform, SettableToRatio<Bernoulli>, SettableToRatio<Bernoulli, Bernoulli>, 
	SettableToPower<Bernoulli>, SettableToWeightedSum<Bernoulli>, Sampleable<bool>, 
	CanGetMean<double>, CanSetMean<double>, CanGetVariance<double>, 
	CanGetLogAverageOf<Bernoulli>, CanGetLogAverageOfPower<Bernoulli>, CanGetAverageLog<Bernoulli>, 
	CanGetLogNormalizer

[SerializableAttribute]
[Quality(QualityBand::Mature)]
public�value class�Bernoulli : IDistribution<bool>, 
	ICloneable, HasPoint<bool>, Diffable, CanGetLogProb<bool>, 
	SettableTo<Bernoulli>, SettableToProduct<Bernoulli>, SettableToProduct<Bernoulli, Bernoulli>, 
	SettableToUniform, SettableToRatio<Bernoulli>, SettableToRatio<Bernoulli, Bernoulli>, 
	SettableToPower<Bernoulli>, SettableToWeightedSum<Bernoulli>, Sampleable<bool>, 
	CanGetMean<double>, CanSetMean<double>, CanGetVariance<double>, 
	CanGetLogAverageOf<Bernoulli>, CanGetLogAverageOfPower<Bernoulli>, CanGetAverageLog<Bernoulli>, 
	CanGetLogNormalizer

<SerializableAttribute> _
<Quality(QualityBand.Mature)> _
Public�Structure�Bernoulli _
	Implements�IDistribution(Of�Boolean), ICloneable,  _
	HasPoint(Of�Boolean), Diffable, CanGetLogProb(Of�Boolean),  _
	SettableTo(Of�Bernoulli), SettableToProduct(Of�Bernoulli), SettableToProduct(Of�Bernoulli, Bernoulli),  _
	SettableToUniform, SettableToRatio(Of�Bernoulli), SettableToRatio(Of�Bernoulli, Bernoulli),  _
	SettableToPower(Of�Bernoulli), SettableToWeightedSum(Of�Bernoulli), Sampleable(Of�Boolean),  _
	CanGetMean(Of�Double), CanSetMean(Of�Double), CanGetVariance(Of�Double),  _
	CanGetLogAverageOf(Of�Bernoulli), CanGetLogAverageOfPower(Of�Bernoulli), CanGetAverageLog(Of�Bernoulli),  _
	CanGetLogNormalizer

<SerializableAttribute> _
<Quality(QualityBand.Mature)> _
Public�Structure�Bernoulli _
	Implements�IDistribution(Of�Boolean), ICloneable,  _
	HasPoint(Of�Boolean), Diffable, CanGetLogProb(Of�Boolean),  _
	SettableTo(Of�Bernoulli), SettableToProduct(Of�Bernoulli), SettableToProduct(Of�Bernoulli, Bernoulli),  _
	SettableToUniform, SettableToRatio(Of�Bernoulli), SettableToRatio(Of�Bernoulli, Bernoulli),  _
	SettableToPower(Of�Bernoulli), SettableToWeightedSum(Of�Bernoulli), Sampleable(Of�Boolean),  _
	CanGetMean(Of�Double), CanSetMean(Of�Double), CanGetVariance(Of�Double),  _
	CanGetLogAverageOf(Of�Bernoulli), CanGetLogAverageOfPower(Of�Bernoulli), CanGetAverageLog(Of�Bernoulli),  _
	CanGetLogNormalizer

Remarks

The most common way to use the distribution is to get and set its ProbTrue property. The distribution is represented by a single number, the log odds: log p(x=true)/p(x=false). If this is 0, then the distribution is uniform. If this is infinity, then the distribution is a point mass on x=true. If this is -infinity, then the distribution is a point mass on x=false. In terms of the log odds, p(x=true) = 1/(1+exp(-logOdds)).