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'MeanDecreaseImpurityImportanceEvaluator aE Mean Decrease Impurity (MDI) parameter importance evaluator.
This evaluator fits fits a random forest regression model that predicts the objective values
of :class:`~optuna.trial.TrialState.COMPLETE` trials given their parameter configurations.
Feature importances are then computed using MDI.
.. note::
This evaluator requires the `sklearn `__ Python package
and is based on `sklearn.ensemble.RandomForestClassifier.feature_importances_
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Args:
n_trees:
Number of trees in the random forest.
max_depth:
The maximum depth of each tree in the random forest.
seed:
Seed for the random forest.
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