BayesOpt
bayesopt::ThompsonSampling Class Reference

Thompson sampling. Picks a random sample of the surrogate model. More...

#include <criteria_thompson.hpp>

+ Inheritance diagram for bayesopt::ThompsonSampling:
+ Collaboration diagram for bayesopt::ThompsonSampling:

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
NonParametricProcessmProc
 
randEngine * mtRandom
 

Detailed Description

Thompson sampling. Picks a random sample of the surrogate model.

Definition at line 37 of file criteria_thompson.hpp.


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