def transform()

in eland/ml/transformers/sklearn.py [0:0]

• 22 lines of code
• 6 McCabe index (conditional complexity)

    def transform(self) -> Ensemble:
        check_is_fitted(self._model, ["estimators_"])
        estimators = self._model.estimators_
        ensemble_classes = None
        if self._classification_labels:
            ensemble_classes = self._classification_labels
        if isinstance(self._model, RandomForestClassifier):
            check_is_fitted(self._model, ["classes_"])
            if ensemble_classes is None:
                ensemble_classes = [str(c) for c in self._model.classes_]
        ensemble_models: Sequence[Tree] = [
            SKLearnDecisionTreeTransformer(m, self._feature_names).transform()
            for m in estimators
        ]
        return Ensemble(
            self._feature_names,
            ensemble_models,
            self.build_aggregator_output(),
            target_type=self.determine_target_type(),
            classification_labels=ensemble_classes,
            classification_weights=self._classification_weights,
        )