diff --git a/docs/source/reference/importance.rst b/docs/source/reference/importance.rst index a90eef51bb..468f5df8a3 100644 --- a/docs/source/reference/importance.rst +++ b/docs/source/reference/importance.rst @@ -5,6 +5,12 @@ optuna.importance The :mod:`~optuna.importance` module provides functionality for evaluating hyperparameter importances based on completed trials in a given study. The utility function :func:`~optuna.importance.get_param_importances` takes a :class:`~optuna.study.Study` and optional evaluator as two of its inputs. The evaluator must derive from :class:`~optuna.importance.BaseImportanceEvaluator`, and is initialized as a :class:`~optuna.importance.FanovaImportanceEvaluator` by default when not passed in. Users implementing custom evaluators should refer to either :class:`~optuna.importance.FanovaImportanceEvaluator` or :class:`~optuna.importance.MeanDecreaseImpurityImportanceEvaluator` as a guide, paying close attention to the format of the return value from the Evaluator's ``evaluate`` function. +.. note:: + + :class:`~optuna.importance.FanovaImportanceEvaluator` takes over 1 minute when given a study that contains 1000+ trials. + We published `optuna-fast-fanova `_ library, + that is a Cython accelerated fANOVA implementation. By using it, you can get hyperparameter + importances within a few seconds. .. autosummary:: :toctree: generated/ diff --git a/optuna/importance/__init__.py b/optuna/importance/__init__.py index 5542568d7b..2314ef9329 100644 --- a/optuna/importance/__init__.py +++ b/optuna/importance/__init__.py @@ -63,6 +63,14 @@ def get_param_importances( assessment on. Defaults to :class:`~optuna.importance.FanovaImportanceEvaluator`. + + .. note:: + :class:`~optuna.importance.FanovaImportanceEvaluator` takes over 1 minute + when given a study that contains 1000+ trials. We published + `optuna-fast-fanova `_ library, + that is a Cython accelerated fANOVA implementation. + By using it, you can get hyperparameter importances within a few seconds. + params: A list of names of parameters to assess. If :obj:`None`, all parameters that are present in all of the completed trials are diff --git a/optuna/visualization/_param_importances.py b/optuna/visualization/_param_importances.py index 3b383e448f..04b4bf526b 100644 --- a/optuna/visualization/_param_importances.py +++ b/optuna/visualization/_param_importances.py @@ -113,6 +113,14 @@ def objective(trial): assessment on. Defaults to :class:`~optuna.importance.FanovaImportanceEvaluator`. + + .. note:: + :class:`~optuna.importance.FanovaImportanceEvaluator` takes over 1 minute + when given a study that contains 1000+ trials. We published + `optuna-fast-fanova `_ library, + that is a Cython accelerated fANOVA implementation. + By using it, you can get hyperparameter importances within a few seconds. + params: A list of names of parameters to assess. If :obj:`None`, all parameters that are present in all of the completed trials are