Class List

Here are the classes, structs, unions and interfaces with brief descriptions:

[detail level 123]

►Nbayesopt	Namespace of the library interface
►Nutils	Extra utils: math functions, ublas helpers, etc
CBoundingBox	Defines a bounding box or axis-alligned bound constraints
CCUnique	Simple class to generate sequences of unique numbers
CDisplayProblem1D
CDisplayProblem2D
CFileParser
CParamLoader
CAnnealedExpectedImprovement	Expected improvement criterion using Schonlau annealing. [Schonlau98]
CAnnealedLowerConfindenceBound	Lower (upper) confidence bound using Srinivas annealing [Srinivas10]
CARDkernel	Abstract class for anisotropic kernel functors using ARD (Automatic Relevance Determination)
CAtomicFunction	Abstract class for an atomic kernel
CAtomicKernel	Abstract class for an atomic kernel
CBayesOptBase	Abstract module for Bayesian optimization
CBiasedExpectedImprovement	Expected improvement criterion modification by Lizotte
CBOptState	Class that represents the state of an optimization
CCombinedCriteria	Abstract class for combined criteria functions
CCombinedFunction	Abstract class for combined functions
CCombinedKernel	Abstract class for combined kernel
CConditionalBayesProcess	Empirical Bayesian NonParametric process
CConstantFunction	Constant function
CConstKernel	Constant kernel
CContinuousModel	Bayesian optimization for functions in continuous input spaces
CCritCallback
CCriteria	Abstract interface for criteria functors
CCriteriaFactory	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/
CDataset	Dataset model to deal with the vector (real) based datasets
CDiscreteModel	Bayesian optimization for functions in discrete spaces
CEmpiricalBayes	Bayesian optimization using different non-parametric processes as distributions over surrogate functions
CExpectedImprovement	Expected improvement criterion by Mockus [Mockus78]
CExpectedReturn	Expected return criterion
CGaussianDistribution
CGaussianProcess	Standard zero mean gaussian process with noisy observations
CGaussianProcessML	Gaussian process with ML parameters
CGaussianProcessNormal	Gaussian process with normal prior on the parameters
CGP_Hedge	GP_Hedge model as describen in Hoffman et al
CGP_Hedge_Random	Modification of the GP_Hedge algorithm where the bandit gains are random outcomes (like Thompson sampling)
CGreedyAOptimality	Greedy A-Optimality criterion
CHammingKernel	Kernel for categorical data
CHierarchicalGaussianProcess	Virtual class for hierarchical Gaussian processes
CInputDistance	Distance in input space
CISOkernel	Abstract class for isotropic kernel functors
CKernel	Interface for kernel functors
CKernelFactory	Factory model for kernel 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/
CKernelModel
CKernelParameters
CKernelProd	Product of two kernels
CKernelRegressor	Abstract class to implement non-parametric processes
CKernelSum	Sum of two kernels
CLinearFunction	Linear combination function
CLinearPlusConstantFunction	Linear combination plus constant function
CLinKernel	Linear kernel
CLinKernelARD	Linear kernel
CLowerConfidenceBound	Lower (upper) confidence bound criterion by [Cox and John, 1992]
CMaternARD1	Matern ARD kernel of 1st order
CMaternARD3	Matern ARD kernel of 3rd order
CMaternARD5	Matern ARD kernel of 5th order
CMaternIso1	Matern isotropic kernel of 1st order
CMaternIso3	Matern kernel of 3rd order
CMaternIso5	Matern isotropic kernel of 5th order
CMCMCModel	Posterior model of nonparametric processes/criteria based on MCMC samples
CMCMCSampler	Markov Chain Monte Carlo sampler
CMeanFactory	Factory model for parametric 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/
CMeanModel
CMeanParameters
CMutualInformation	Mutual Information bound criterion b [Contal et al., 2014]
CNLOPT_Optimization
CNonParametricProcess	Abstract class to implement Bayesian regressors
COneFunction	Constant one function
COptimisticSampling	Optimistic sampling
CParameters
CParametricFunction	Interface for mean functors
CPolynomial	Polynomial covariance function
CPolynomial2
CPolynomial3
CPolynomial4
CPolynomial5
CPolynomial6
CPolynomial7
CPosteriorFixed	Bayesian optimization using different non-parametric processes as distributions over surrogate functions
CPosteriorModel	Bayesian optimization using different non-parametric processes as distributions over surrogate functions
CProbabilityDistribution
CProbabilityOfImprovement	Probability of improvement criterion based on (Kushner)
CProdCriteria	Product of criterion functions
CRBOptimizable
CRBOptimizableWrapper
CRGBOptimizable
CRGBOptimizableWrapper
CRQIso	Rational quadratic (Student's t) kernel
CSEArd	Square exponential (Gaussian) kernel
CSEIso	Square exponential (Gaussian) kernel
CStudentTDistribution
CStudentTProcessJeffreys	Student T process with Jeffreys prior
CStudentTProcessNIG	Student's t process with Normal Inverse-Gamma hyperprior on mean and snigal variance parameters
CSumCriteria	Wrapper class for linear combination of criterion functions
CSumFunction	Sum of two kernels
CThompsonSampling	Thompson sampling. Picks a random sample of the surrogate model
CZeroFunction	Constant zero function
►Nbayesoptmodule
CBayesOptCategorical	Python Module for BayesOptCategorical
CBayesOptContinuous	Python Module for BayesOptContinuous
CBayesOptDiscrete	Python Module for BayesOptDiscrete
►Ndemo_distance
CBayesOptTest
►Ndemo_multiprocess
CBayesOptProcess
►Ndemo_quad
CBayesOptTest
Cbopt_params	Configuration parameters
CBraninNormalized
CCContinuousModel	Version of ContinuousModel for the C wrapper
CCDiscreteModel	Version of DiscreteModel for the C wrapper
CExampleCamelback
CExampleDisc
CExampleHartmann6
CExampleOneD
CExampleQuadratic
CFILELog
Ckernel_parameters	Kernel configuration parameters
CLog
Cmean_parameters
COutput2FILE
CSystemCallsBranin
CTemplateWritter
Cuser_function_data
CXMLCallsBranin