BayesOpt
Class Index
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a
Criteria
(
bayesopt
)
HierarchicalGaussianProcess
(
bayesopt
)
mean_parameters
RBOptimizableWrapper
(
bayesopt
)
CriteriaFactory
(
bayesopt
)
i
MeanFactory
(
bayesopt
)
RGBOptimizable
(
bayesopt
)
AnnealedExpectedImprovement
(
bayesopt
)
CUnique
(
bayesopt::utils
)
MeanModel
(
bayesopt
)
RGBOptimizableWrapper
(
bayesopt
)
AnnealedLowerConfindenceBound
(
bayesopt
)
d
InputDistance
(
bayesopt
)
MeanParameters
(
bayesopt
)
RQIso
(
bayesopt
)
ARDkernel
(
bayesopt
)
ISOkernel
(
bayesopt
)
MutualInformation
(
bayesopt
)
s
AtomicFunction
(
bayesopt
)
Dataset
(
bayesopt
)
k
n
AtomicKernel
(
bayesopt
)
DiscreteModel
(
bayesopt
)
SEArd
(
bayesopt
)
b
DisplayProblem1D
(
bayesopt::utils
)
Kernel
(
bayesopt
)
NLOPT_Optimization
(
bayesopt
)
SEIso
(
bayesopt
)
DisplayProblem2D
(
bayesopt::utils
)
kernel_parameters
NonParametricProcess
(
bayesopt
)
StudentTDistribution
(
bayesopt
)
BayesOptBase
(
bayesopt
)
e
KernelFactory
(
bayesopt
)
o
StudentTProcessJeffreys
(
bayesopt
)
BayesOptCategorical
(bayesoptmodule)
KernelModel
(
bayesopt
)
StudentTProcessNIG
(
bayesopt
)
BayesOptContinuous
(bayesoptmodule)
EmpiricalBayes
(
bayesopt
)
KernelParameters
(
bayesopt
)
OneFunction
(
bayesopt
)
SumCriteria
(
bayesopt
)
BayesOptDiscrete
(bayesoptmodule)
ExampleCamelback
KernelProd
(
bayesopt
)
OptimisticSampling
(
bayesopt
)
SumFunction
(
bayesopt
)
BayesOptProcess
(demo_multiprocess)
ExampleDisc
KernelRegressor
(
bayesopt
)
Output2FILE
SystemCallsBranin
BayesOptTest
(demo_distance)
ExampleHartmann6
KernelSum
(
bayesopt
)
p
t
BayesOptTest
(demo_quad)
ExampleOneD
l
BiasedExpectedImprovement
(
bayesopt
)
ExampleQuadratic
Parameters
(
bayesopt
)
TemplateWritter
bopt_params
ExpectedImprovement
(
bayesopt
)
LinearFunction
(
bayesopt
)
ParametricFunction
(
bayesopt
)
ThompsonSampling
(
bayesopt
)
BOptState
(
bayesopt
)
ExpectedReturn
(
bayesopt
)
LinearPlusConstantFunction
(
bayesopt
)
ParamLoader
(
bayesopt::utils
)
u
BoundingBox
(
bayesopt::utils
)
f
LinKernel
(
bayesopt
)
Polynomial
(
bayesopt
)
BraninNormalized
LinKernelARD
(
bayesopt
)
Polynomial2
(
bayesopt
)
user_function_data
c
FILELog
Log
Polynomial3
(
bayesopt
)
x
FileParser
(
bayesopt::utils
)
LowerConfidenceBound
(
bayesopt
)
Polynomial4
(
bayesopt
)
CContinuousModel
g
m
Polynomial5
(
bayesopt
)
XMLCallsBranin
CDiscreteModel
Polynomial6
(
bayesopt
)
z
CombinedCriteria
(
bayesopt
)
GaussianDistribution
(
bayesopt
)
MaternARD1
(
bayesopt
)
Polynomial7
(
bayesopt
)
CombinedFunction
(
bayesopt
)
GaussianProcess
(
bayesopt
)
MaternARD3
(
bayesopt
)
PosteriorFixed
(
bayesopt
)
ZeroFunction
(
bayesopt
)
CombinedKernel
(
bayesopt
)
GaussianProcessML
(
bayesopt
)
MaternARD5
(
bayesopt
)
PosteriorModel
(
bayesopt
)
ConditionalBayesProcess
(
bayesopt
)
GaussianProcessNormal
(
bayesopt
)
MaternIso1
(
bayesopt
)
ProbabilityDistribution
(
bayesopt
)
ConstantFunction
(
bayesopt
)
GP_Hedge
(
bayesopt
)
MaternIso3
(
bayesopt
)
ProbabilityOfImprovement
(
bayesopt
)
ConstKernel
(
bayesopt
)
GP_Hedge_Random
(
bayesopt
)
MaternIso5
(
bayesopt
)
ProdCriteria
(
bayesopt
)
ContinuousModel
(
bayesopt
)
GreedyAOptimality
(
bayesopt
)
MCMCModel
(
bayesopt
)
r
CritCallback
(
bayesopt
)
h
MCMCSampler
(
bayesopt
)
RBOptimizable
(
bayesopt
)
HammingKernel
(
bayesopt
)
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k
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