bayesopt::OptimisticSampling Class Reference
Optimistic sampling. More...
#include <criteria_thompson.hpp>
Inheritance diagram for bayesopt::OptimisticSampling:
Collaboration diagram for bayesopt::OptimisticSampling:
Public Member Functions | |
| void | setParameters (const vectord ¶ms) |
| 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
Optimistic sampling.
A simple variation of Thompson sampling that picks only samples that are better than the best outcome so far.
Definition at line 57 of file criteria_thompson.hpp.
The documentation for this class was generated from the following file:
