h2o-py/h2o/model/model_base.py
def cross_validation_predictions(self):
        """
        Obtain the (out-of-sample) holdout predictions of all cross-validation models on their holdout data.

        Note that the predictions are expanded to the full number of rows of the training data, with 0 fill-in.

        :returns: list of H2OFrame objects.
        """
        preds = self._model_json["output"]["cross_validation_predictions"]
        if preds is None: return None
        m = []
        for p in preds: m.append(h2o.get_frame(p["name"]))
        return m
def cross_validation_predictions(self):
        """
        Obtain the (out-of-sample) holdout predictions of all cross-validation models on their holdout data.

        Note that the predictions are expanded to the full number of rows of the training data, with 0 fill-in.

        :returns: list of H2OFrame objects.
        """
        preds = self._model_json["output"]["cross_validation_predictions"]
        if preds is None: return None
        m = []
        for p in preds: m.append(h2o.get_frame(p["name"]))
        return m
Obtain the (out-of-sample) holdout predictions of all cross-validation models on their holdout data.

        Note that the predictions are expanded to the full number of rows of the training data, with 0 fill-in.

        :returns: list of H2OFrame objects.