BayesOpt
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Set of criterium functions to select the next point during optimization/exploration. More...
Classes | |
class | bayesopt::GreedyAOptimality |
Greedy A-Optimality criterion. More... | |
class | bayesopt::CombinedCriteria |
Abstract class for combined criteria functions. More... | |
class | bayesopt::InputDistance |
Distance in input space. More... | |
class | bayesopt::ExpectedImprovement |
Expected improvement criterion by Mockus [Mockus78]. More... | |
class | bayesopt::BiasedExpectedImprovement |
Expected improvement criterion modification by Lizotte. More... | |
class | bayesopt::AnnealedExpectedImprovement |
Expected improvement criterion using Schonlau annealing. [Schonlau98]. More... | |
class | bayesopt::ExpectedReturn |
Expected return criterion. More... | |
class | bayesopt::GP_Hedge |
GP_Hedge model as describen in Hoffman et al. More... | |
class | bayesopt::GP_Hedge_Random |
Modification of the GP_Hedge algorithm where the bandit gains are random outcomes (like Thompson sampling). More... | |
class | bayesopt::LowerConfidenceBound |
Lower (upper) confidence bound criterion by [Cox and John, 1992]. More... | |
class | bayesopt::AnnealedLowerConfindenceBound |
Lower (upper) confidence bound using Srinivas annealing [Srinivas10]. More... | |
class | bayesopt::MutualInformation |
Mutual Information bound criterion b [Contal et al., 2014]. More... | |
class | bayesopt::ProbabilityOfImprovement |
Probability of improvement criterion based on (Kushner). More... | |
class | bayesopt::ProdCriteria |
Product of criterion functions. More... | |
class | bayesopt::SumCriteria |
Wrapper class for linear combination of criterion functions. More... | |
class | bayesopt::ThompsonSampling |
Thompson sampling. Picks a random sample of the surrogate model. More... | |
class | bayesopt::OptimisticSampling |
Optimistic sampling. More... | |
class | bayesopt::Criteria |
Abstract interface for criteria functors. More... | |
class | bayesopt::CriteriaFactory |
Factory model for criterion functions This factory is based on the libgp library by Manuel Blum https://bitbucket.org/mblum/libgp which follows the squeme of GPML by Rasmussen and Nickisch http://www.gaussianprocess.org/gpml/code/matlab/doc/. More... | |
Set of criterium functions to select the next point during optimization/exploration.