f8a388ad9a6d3480991d2564b5276ecd25a704bc,optuna/importance/_sklearn.py,RandomForestFeatureImportanceEvaluator,get_param_importance,#RandomForestFeatureImportanceEvaluator#Any#,30

Before Change

        param_importances = OrderedDict()
        param_names = list(search_space.keys())
        for i in feature_importances.argsort():
            param_importances[param_names[i]] = feature_importances[i]

        return param_importances

After Change

        feature_importances = regr.feature_importances_

        feature_importances_reduced = np.zeros((len(search_space),), dtype=np.float32)
        np.add.at(
            feature_importances_reduced, transformed_cols_to_original_cols, feature_importances)

        param_importances = OrderedDict()
        param_names = list(search_space.keys())
        for i in np.asarray(feature_importances_reduced).argsort():

Instances