optuna.samplers.intersection_search_space
- optuna.samplers.intersection_search_space(study, ordered_dict=False, include_pruned=False)[source]
Return the intersection search space of the
Study
.Intersection search space contains the intersection of parameter distributions that have been suggested in the completed trials of the study so far. If there are multiple parameters that have the same name but different distributions, neither is included in the resulting search space (i.e., the parameters with dynamic value ranges are excluded).
Note
IntersectionSearchSpace
provides the same functionality with a much faster way. Please consider using it if you want to reduce execution time as much as possible.- Parameters:
study (Study) – A study with completed trials.
ordered_dict (bool) – A boolean flag determining the return type. If
False
, the returned object will be adict
. IfTrue
, the returned object will be adict
sorted by keys, i.e. parameter names.include_pruned (bool) – Whether pruned trials should be included in the search space.
- Returns:
A dictionary containing the parameter names and parameter’s distributions.
- Return type:
Dict[str, BaseDistribution]
Warning
Deprecated in v3.2.0. This feature will be removed in the future. The removal of this feature is currently scheduled for v4.0.0, but this schedule is subject to change. See https://github.com/optuna/optuna/releases/tag/v3.2.0.
Please use optuna.search_space.intersection_search_space instead.