Convenience function that constructs an active learning OptimizerAL
via optimizer_active_learning(), runs it on a bbotk instance, and (optionally)
logs metrics via CallbackMetricsTracker.
Usage
optimize_active(
objective,
search_space = NULL,
n_evals = NULL,
terminator = NULL,
metrics_tracker = NULL,
forecast_tracker = NULL,
forecast_terminator = NULL,
callbacks = NULL,
optimizer = NULL,
...
)Arguments
- objective
(bbotk::Objective)
Objective to evaluate. Typically has a single codomain target tagged"learn".- search_space
(
NULL| paradox::ParamSet)
Optional restricted search space. IfNULL, the search space is derived fromobjective$domain(same logic as bbotk'sOptimInstanceBatch).- n_evals
(
NULL|integer(1))
Convenience evaluation budget used only ifterminatorisNULL.- terminator
(
NULL| bbotk::Terminator)
Terminator for the outer active learning loop. IfNULL, atrm("evals", n_evals = n_evals)is constructed.- metrics_tracker
(
NULL| MetricsTracker)
Optional metrics tracker. If provided, a CallbackMetricsTracker is attached to the instance.- forecast_tracker
(
NULL|ForecastTracker)
Optional forecast tracker. If provided,CallbackForecastTrackeris attached after CallbackMetricsTracker. Requiresmetrics_tracker.- forecast_terminator
(
NULL| bbotk::Terminator)
Optional forecast-based terminator. If supplied, it is combined with the base terminator viatrm("combo", ..., any = TRUE).- callbacks
(
NULL|list()of bbotk::CallbackBatch)
Additional user callbacks. These are appended after internal callbacks.- optimizer
(
NULL| bbotk::OptimizerBatch)
Explicit optimizer to use. IfNULL, constructs one viaoptimizer_active_learning(). Supply an optimizer fromoptimizer_pool_al()to use paper-style active learning methods.- ...
Passed to
optimizer_active_learning()whenoptimizerisNULL.
Value
list() with:
instance: SearchInstanceoptimizer: configured optimizermetrics_tracker: the passed tracker (orNULL)