Modification of the GP_Hedge algorithm where the bandit gains are random outcomes (like Thompson sampling). More...

Inheritance diagram for bayesopt::GP_Hedge_Random:

Collaboration diagram for bayesopt::GP_Hedge_Random:

Public Member Functions
std::string	name ()

Public Member Functions inherited from bayesopt::GP_Hedge
void	init (NonParametricProcess *proc)

double	operator() (const vectord &x)

bool	requireComparison ()

void	initialCriteria ()

bool	rotateCriteria ()

void	pushResult (const vectord &prevResult)

std::string	getBestCriteria (vectord &best)

Public Member Functions inherited from bayesopt::CombinedCriteria
void	pushCriteria (Criteria *crit)

void	setParameters (const vectord &theta)

size_t	nParameters ()

Public Member Functions inherited from bayesopt::Criteria
double	evaluate (const vectord &x)

virtual void	reset ()

void	setRandomEngine (randEngine &eng)

virtual void	update (const vectord &x)

Protected Member Functions
virtual double	computeLoss (const vectord &query)

Protected Member Functions inherited from bayesopt::GP_Hedge
int	update_hedge ()

Additional Inherited Members
Protected Attributes inherited from bayesopt::GP_Hedge
vectord	loss_

vectord	gain_

vectord	prob_

vectord	cumprob_

Criteria *	mCurrentCriterium

std::vector< vectord >	mBestLists

size_t	mIndex

Protected Attributes inherited from bayesopt::CombinedCriteria
boost::ptr_vector< Criteria >	mCriteriaList

Protected Attributes inherited from bayesopt::Criteria
NonParametricProcess *	mProc

randEngine *	mtRandom

Detailed Description

Modification of the GP_Hedge algorithm where the bandit gains are random outcomes (like Thompson sampling).

Definition at line 75 of file criteria_hedge.hpp.

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

Public Member Functions