Abstract acquisition function class.
Based on the predictions of a Surrogate, the acquisition function encodes the preference to evaluate a new point.
See also
Other Acquisition Function:
mlr_acqfunctions
,
mlr_acqfunctions_aei
,
mlr_acqfunctions_cb
,
mlr_acqfunctions_ehvi
,
mlr_acqfunctions_ehvigh
,
mlr_acqfunctions_ei
,
mlr_acqfunctions_eips
,
mlr_acqfunctions_mean
,
mlr_acqfunctions_multi
,
mlr_acqfunctions_pi
,
mlr_acqfunctions_sd
,
mlr_acqfunctions_smsego
,
mlr_acqfunctions_stochastic_cb
,
mlr_acqfunctions_stochastic_ei
Super class
bbotk::Objective
-> AcqFunction
Active bindings
direction
(
"same"
|"minimize"
|"maximize"
)
Optimization direction of the acquisition function relative to the direction of the objective function of the bbotk::OptimInstance. Must be"same"
,"minimize"
, or"maximize"
.surrogate_max_to_min
(
-1
|1
)
Multiplicative factor to correct for minimization or maximization of the acquisition function.label
(
character(1)
)
Label for this object.man
(
character(1)
)
String in the format[pkg]::[topic]
pointing to a manual page for this object.archive
(bbotk::Archive)
Points to the bbotk::Archive of the surrogate.fun
(
function
)
Points to the private acquisition function to be implemented by subclasses.surrogate
(Surrogate)
Surrogate.requires_predict_type_se
(
logical(1)
)
Whether the acquisition function requires the surrogate to have"se"
as$predict_type
.packages
(
character()
)
Set of required packages.
Methods
Method new()
Creates a new instance of this R6 class.
Note that the surrogate can be initialized lazy and can later be set via the active binding $surrogate
.
Usage
AcqFunction$new(
id,
constants = ParamSet$new(),
surrogate,
requires_predict_type_se,
direction,
packages = NULL,
label = NA_character_,
man = NA_character_
)
Arguments
id
(
character(1)
).constants
(paradox::ParamSet). Changeable constants or parameters.
surrogate
(
NULL
| Surrogate). Surrogate whose predictions are used in the acquisition function.requires_predict_type_se
(
logical(1)
)
Whether the acquisition function requires the surrogate to have"se"
as$predict_type
.direction
(
"same"
|"minimize"
|"maximize"
). Optimization direction of the acquisition function relative to the direction of the objective function of the bbotk::OptimInstance. Must be"same"
,"minimize"
, or"maximize"
.packages
(
character()
)
Set of required packages. A warning is signaled prior to construction if at least one of the packages is not installed, but loaded (not attached) later on-demand viarequireNamespace()
.label
(
character(1)
)
Label for this object.man
(
character(1)
)
String in the format[pkg]::[topic]
pointing to a manual page for this object.
Method eval_many()
Evaluates multiple input values on the objective function.
Arguments
xss
(
list()
)
A list of lists that contains multiple x values, e.g.list(list(x1 = 1, x2 = 2), list(x1 = 3, x2 = 4))
.
Method eval_dt()
Evaluates multiple input values on the objective function
Arguments
xdt
(
data.table::data.table()
)
One point per row, e.g.data.table(x1 = c(1, 3), x2 = c(2, 4))
.