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 a dict. If True, the returned object will be an collections.OrderedDict 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]