0bab786d05391d24fd101f3aed71e6f4b3f14b55,lynxes/core/global_interpretation/feature_importance.py,FeatureImportance,feature_importance,#FeatureImportance#Any#Any#,25

Before Change

            // evaluated entropy of scaled changes.
            changes_in_predictions = new_predictions - original_predictions
            importance = np.mean(np.std(changes_in_predictions, axis=0))
            importances[feature_id] = importance

            // reset copy
            copy_of_data_set[feature_id] = self.data_set[feature_id]

After Change

                                         "Please submit an issue here:"
                                         "https://github.com/datascienceinc/model-interpretation/issues"))

        importances = divide_zerosafe(importances, (np.ones(importances.shape[0]) * importances.sum()))
        return importances


    def plot_feature_importance(self, predict_fn, filter_classes=None, ax=None):

Instances