bayesopt::ProbabilityDistribution Class Reference

Inheritance diagram for bayesopt::ProbabilityDistribution:

Public Member Functions
	ProbabilityDistribution (randEngine &eng)
virtual double	pdf (double x)=0
	Probability density function. More...
virtual double	negativeExpectedImprovement (double min, size_t g)=0
	Expected Improvement algorithm for minimization. More...
virtual double	lowerConfidenceBound (double beta=1)=0
	Lower confindence bound. More...
virtual double	negativeProbabilityOfImprovement (double yMin, double epsilon)=0
	Probability of improvement algorithm for minimization. More...
virtual double	sample_query ()=0
	Sample outcome acording to the marginal distribution at the query point. More...
virtual double	getMean ()=0
virtual double	getStd ()=0

Protected Attributes
randEngine &	mtRandom

Detailed Description

Definition at line 35 of file prob_distribution.hpp.

Member Function Documentation

lowerConfidenceBound()

virtual double bayesopt::ProbabilityDistribution::lowerConfidenceBound ( double  beta = 1 )

pure virtual

Lower confindence bound.

Can be seen as the inverse of the Upper confidence bound

Parameters

beta	std coefficient (used for annealing)

Returns

value of the lower confidence bound

Implemented in bayesopt::StudentTDistribution, and bayesopt::GaussianDistribution.

negativeExpectedImprovement()

virtual double bayesopt::ProbabilityDistribution::negativeExpectedImprovement ( double  min, size_t  g  )

pure virtual

Expected Improvement algorithm for minimization.

Parameters

min	minimum value found so far
g	exponent (used for annealing)

Returns

negative value of the expected improvement

Implemented in bayesopt::StudentTDistribution, and bayesopt::GaussianDistribution.

negativeProbabilityOfImprovement()

virtual double bayesopt::ProbabilityDistribution::negativeProbabilityOfImprovement ( double  yMin, double  epsilon  )

pure virtual

Probability of improvement algorithm for minimization.

Parameters

min	minimum value found so far
epsilon	minimum improvement margin

Returns

negative value of the probability of improvement

Implemented in bayesopt::StudentTDistribution, and bayesopt::GaussianDistribution.

pdf()

virtual double bayesopt::ProbabilityDistribution::pdf ( double  x )

pure virtual

Probability density function.

Parameters

x	query point

Returns

probability

Implemented in bayesopt::StudentTDistribution, and bayesopt::GaussianDistribution.

sample_query()

virtual double bayesopt::ProbabilityDistribution::sample_query ( )

pure virtual

Sample outcome acording to the marginal distribution at the query point.

Parameters

eng	boost.random engine

Returns

outcome

Implemented in bayesopt::StudentTDistribution, and bayesopt::GaussianDistribution.

---

The documentation for this class was generated from the following file:

• prob_distribution.hpp