importance module provides functionality for evaluating hyperparameter importances based on completed trials in a given study. The utility function
get_param_importances() takes a
Study and optional evaluator as two of its inputs. The evaluator must derive from
BaseImportanceEvaluator, and is initialized as a
FanovaImportanceEvaluator by default when not passed in. Users implementing custom evaluators should refer to either
MeanDecreaseImpurityImportanceEvaluator as a guide, paying close attention to the format of the return value from the Evaluator’s
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.
Evaluate parameter importances based on completed trials in the given study.
fANOVA importance evaluator.
Mean Decrease Impurity (MDI) parameter importance evaluator.