optuna.multi_objective.study.create_study¶
- optuna.multi_objective.study.create_study(directions: List[str], study_name: Optional[str] = None, storage: Union[None, str, optuna.storages._base.BaseStorage] = None, sampler: Optional[optuna.multi_objective.samplers._base.BaseMultiObjectiveSampler] = None, load_if_exists: bool = False) optuna.multi_objective.study.MultiObjectiveStudy [source]¶
Create a new
MultiObjectiveStudy
.- Parameters
directions – Optimization direction for each objective value. Set
minimize
for minimization andmaximize
for maximization.study_name – Study’s name. If this argument is set to None, a unique name is generated automatically.
storage –
Database URL. If this argument is set to None, in-memory storage is used, and the
Study
will not be persistent.Note
When a database URL is passed, Optuna internally uses SQLAlchemy to handle the database. Please refer to SQLAlchemy’s document for further details. If you want to specify non-default options to SQLAlchemy Engine, you can instantiate
RDBStorage
with your desired options and pass it to thestorage
argument instead of a URL.sampler – A sampler object that implements background algorithm for value suggestion. If
None
is specified,NSGAIIMultiObjectiveSampler
is used as the default. See alsosamplers
.load_if_exists – Flag to control the behavior to handle a conflict of study names. In the case where a study named
study_name
already exists in thestorage
, aDuplicatedStudyError
is raised ifload_if_exists
is set toFalse
. Otherwise, the creation of the study is skipped, and the existing one is returned.
- Returns
A
MultiObjectiveStudy
object.
Note
Added in v1.4.0 as an experimental feature. The interface may change in newer versions without prior notice. See https://github.com/optuna/optuna/releases/tag/v1.4.0.