Greedy A-Optimality criterion. More...

#include <criteria_a_opt.hpp>

Inheritance diagram for bayesopt::GreedyAOptimality:

Collaboration diagram for bayesopt::GreedyAOptimality:

Public Member Functions
void	setParameters (const vectord &params)

size_t	nParameters ()

double	operator() (const vectord &x)

std::string	name ()

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

double	evaluate (const vectord &x)

virtual void	reset ()

void	setRandomEngine (randEngine &eng)

virtual void	pushCriteria (Criteria *crit)

virtual bool	requireComparison ()

virtual void	initialCriteria ()

virtual void	update (const vectord &x)

virtual bool	rotateCriteria ()

virtual void	pushResult (const vectord &prevResult)

virtual std::string	getBestCriteria (vectord &best)

Additional Inherited Members
Protected Attributes inherited from bayesopt::Criteria
NonParametricProcess *	mProc

randEngine *	mtRandom

Detailed Description

Greedy A-Optimality criterion.

Used for learning the function, not to minimize. Some authors name it I-optimality because it minimizes the error on the prediction, not on the parameters.

Definition at line 41 of file criteria_a_opt.hpp.

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

criteria_a_opt.hpp

Public Member Functions

Additional Inherited Members

Detailed Description