optuna.importance

The 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 FanovaImportanceEvaluator, MeanDecreaseImpurityImportanceEvaluator, or PedAnovaImportanceEvaluator as a guide, paying close attention to the format of the return value from the Evaluator’s evaluate function.

Note

Although the default importance evaluator in Optuna is FanovaImportanceEvaluator, Optuna Dashboard uses a light-weight evaluator, i.e., PedAnovaImportanceEvaluator, for runtime performance purposes, yielding a different result.

get_param_importances	Evaluate parameter importances based on completed trials in the given study.
FanovaImportanceEvaluator	fANOVA importance evaluator.
MeanDecreaseImpurityImportanceEvaluator	Mean Decrease Impurity (MDI) parameter importance evaluator.
PedAnovaImportanceEvaluator	PED-ANOVA importance evaluator.