optuna.study.create_study¶
-
optuna.study.
create_study
(storage: Union[str, optuna.storages._base.BaseStorage, None] = None, sampler: Optional[samplers.BaseSampler] = None, pruner: Optional[optuna.pruners._base.BasePruner] = None, study_name: Optional[str] = None, direction: str = 'minimize', load_if_exists: bool = False) → optuna.study.Study[source]¶ Create a new
Study
.Example
import optuna def objective(trial): x = trial.suggest_uniform("x", 0, 10) return x ** 2 study = optuna.create_study() study.optimize(objective, n_trials=3)
- Parameters
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,TPESampler
is used as the default. See alsosamplers
.pruner – A pruner object that decides early stopping of unpromising trials. If
None
is specified,MedianPruner
is used as the default. See alsopruners
.study_name – Study’s name. If this argument is set to None, a unique name is generated automatically.
direction – Direction of optimization. Set
minimize
for minimization andmaximize
for maximization.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
Study
object.- Raises
ValueError – If
direction
is neither ‘minimize’ nor ‘maximize’.
See also
optuna.create_study()
is an alias ofoptuna.study.create_study()
.