Flexible Bayesian Optimization

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Documentation for package ‘mlr3mbo’ version 0.2.4

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

mlr3mbo-package	mlr3mbo: Flexible Bayesian Optimization
acqf	Syntactic Sugar Acquisition Function Construction
AcqFunction	Acquisition Function Base Class
AcqFunctionAEI	Acquisition Function Augmented Expected Improvement
AcqFunctionCB	Acquisition Function Confidence Bound
AcqFunctionEHVI	Acquisition Function Expected Hypervolume Improvement
AcqFunctionEHVIGH	Acquisition Function Expected Hypervolume Improvement via Gauss-Hermite Quadrature
AcqFunctionEI	Acquisition Function Expected Improvement
AcqFunctionEIPS	Acquisition Function Expected Improvement Per Second
AcqFunctionMean	Acquisition Function Mean
AcqFunctionPI	Acquisition Function Probability of Improvement
AcqFunctionSD	Acquisition Function Standard Deviation
AcqFunctionSmsEgo	Acquisition Function SMS-EGO
acqo	Syntactic Sugar Acquisition Function Optimizer Construction
AcqOptimizer	Acquisition Function Optimizer
bayesopt_ego	Sequential Single-Objective Bayesian Optimization
bayesopt_emo	Sequential Multi-Objective Bayesian Optimization
bayesopt_mpcl	Single-Objective Bayesian Optimization via Multipoint Constant Liar
bayesopt_parego	Multi-Objective Bayesian Optimization via ParEGO
bayesopt_smsego	Sequential Multi-Objective Bayesian Optimization via SMS-EGO
default_acqfunction	Default Acquisition Function
default_acqoptimizer	Default Acquisition Function Optimizer
default_gp	Default Gaussian Process
default_loop_function	Default Loop Function
default_result_assigner	Default Result Assigner
default_rf	Default Random Forest
default_surrogate	Default Surrogate
loop_function	Loop Functions for Bayesian Optimization
mbo_defaults	Defaults for OptimizerMbo
mlr3mbo	mlr3mbo: Flexible Bayesian Optimization
mlr_acqfunctions	Dictionary of Acquisition Functions
mlr_acqfunctions_aei	Acquisition Function Augmented Expected Improvement
mlr_acqfunctions_cb	Acquisition Function Confidence Bound
mlr_acqfunctions_ehvi	Acquisition Function Expected Hypervolume Improvement
mlr_acqfunctions_ehvigh	Acquisition Function Expected Hypervolume Improvement via Gauss-Hermite Quadrature
mlr_acqfunctions_ei	Acquisition Function Expected Improvement
mlr_acqfunctions_eips	Acquisition Function Expected Improvement Per Second
mlr_acqfunctions_mean	Acquisition Function Mean
mlr_acqfunctions_pi	Acquisition Function Probability of Improvement
mlr_acqfunctions_sd	Acquisition Function Standard Deviation
mlr_acqfunctions_smsego	Acquisition Function SMS-EGO
mlr_loop_functions	Dictionary of Loop Functions
mlr_loop_functions_ego	Sequential Single-Objective Bayesian Optimization
mlr_loop_functions_emo	Sequential Multi-Objective Bayesian Optimization
mlr_loop_functions_mpcl	Single-Objective Bayesian Optimization via Multipoint Constant Liar
mlr_loop_functions_parego	Multi-Objective Bayesian Optimization via ParEGO
mlr_loop_functions_smsego	Sequential Multi-Objective Bayesian Optimization via SMS-EGO
mlr_optimizers_mbo	Model Based Optimization
mlr_result_assigners	Dictionary of Result Assigners
mlr_result_assigners_archive	Result Assigner Based on the Archive
mlr_result_assigners_surrogate	Result Assigner Based on a Surrogate Mean Prediction
mlr_tuners_mbo	TunerBatch using Model Based Optimization
OptimizerMbo	Model Based Optimization
ras	Syntactic Sugar Result Assigner Construction
ResultAssigner	Result Assigner Base Class
ResultAssignerArchive	Result Assigner Based on the Archive
ResultAssignerSurrogate	Result Assigner Based on a Surrogate Mean Prediction
srlrn	Syntactic Sugar Surrogate Construction
Surrogate	Surrogate Model
SurrogateLearner	Surrogate Model Containing a Single Learner
SurrogateLearnerCollection	Surrogate Model Containing Multiple Learners
TunerMbo	TunerBatch using Model Based Optimization