Configuration parameters. More...
#include <parameters.h>
Collaboration diagram for bopt_params:
Public Attributes | |
| size_t | n_iterations |
| Maximum BayesOpt evaluations (budget) | |
| size_t | n_inner_iterations |
| Maximum inner optimizer evaluations. | |
| size_t | n_init_samples |
| Number of samples before optimization. | |
| size_t | n_iter_relearn |
| Number of samples before relearn kernel. | |
| size_t | init_method |
| Sampling method for initial set 1-LHS, 2-Sobol (if available), other value-uniformly distributed. | |
| int | random_seed |
| >=0 -> Fixed seed, <0 -> Time based (variable). More... | |
| int | verbose_level |
| Neg-Error,0-Warning,1-Info,2-Debug -> stdout 3-Error,4-Warning,5-Info,>5-Debug -> logfile. | |
| char * | log_filename |
| Log file path (if applicable) | |
| size_t | load_save_flag |
| 1-Load data,2-Save data, 3-Load and save data. More... | |
| char * | load_filename |
| Init data file path (if applicable) | |
| char * | save_filename |
| Sava data file path (if applicable) | |
| char * | surr_name |
| Name of the surrogate function. | |
| double | sigma_s |
| Signal variance (if known). More... | |
| double | noise |
| Variance of observation noise (and nugget) | |
| double | alpha |
| Inverse Gamma prior for signal var. More... | |
| double | beta |
| Inverse Gamma prior for signal var. More... | |
| score_type | sc_type |
| Score type for kernel hyperparameters (ML,MAP,etc) | |
| learning_type | l_type |
| Type of learning for the kernel params. | |
| int | l_all |
| Learn all hyperparameters or only kernel. | |
| double | epsilon |
| For epsilon-greedy exploration. | |
| size_t | force_jump |
| If >0, and the difference between two consecutive observations is pure noise, for n consecutive steps, force a random jump. More... | |
| kernel_parameters | kernel |
| Kernel parameters. | |
| mean_parameters | mean |
| Mean (parametric function) parameters. | |
| char * | crit_name |
| Name of the criterion. | |
| double | crit_params [128] |
| Criterion hyperparameters (if needed) | |
| size_t | n_crit_params |
| Number of criterion hyperparameters. | |
Detailed Description
Configuration parameters.
- See also
- Reference Manual for a full description of the parameters
Definition at line 83 of file parameters.h.
Member Data Documentation
◆ alpha
| double bopt_params::alpha |
Inverse Gamma prior for signal var.
Used in StudentTProcessNIG
Definition at line 108 of file parameters.h.
◆ beta
| double bopt_params::beta |
Inverse Gamma prior for signal var.
Used in StudentTProcessNIG
Definition at line 110 of file parameters.h.
◆ force_jump
| size_t bopt_params::force_jump |
If >0, and the difference between two consecutive observations is pure noise, for n consecutive steps, force a random jump.
Avoid getting stuck if model is bad and there is few data, however, it might reduce the accuracy.
Definition at line 118 of file parameters.h.
◆ load_save_flag
| size_t bopt_params::load_save_flag |
1-Load data,2-Save data, 3-Load and save data.
Definition at line 98 of file parameters.h.
◆ random_seed
| int bopt_params::random_seed |
>=0 -> Fixed seed, <0 -> Time based (variable).
Definition at line 92 of file parameters.h.
◆ sigma_s
| double bopt_params::sigma_s |
Signal variance (if known).
Used in GaussianProcess and GaussianProcessNormal
Definition at line 104 of file parameters.h.
The documentation for this struct was generated from the following file:
