h2o-py/h2o/model/model_base.py
def residual_degrees_of_freedom(self, train=False, valid=False, xval=False):
        """
        Retreive the residual degress of freedom if this model has the attribute, or None otherwise.

        :param bool train: Get the residual dof for the training set. If both train and valid are False, then train
            is selected by default.
        :param bool valid: Get the residual dof for the validation set. If both train and valid are True, then train
            is selected by default.

        :returns: Return the residual dof, or None if it is not present.
        """
        if xval: raise H2OValueError("Cross-validation metrics are not available.")
        if not train and not valid: train = True
        if train and valid:         train = True
        if train:
            return self._model_json["output"]["training_metrics"].residual_degrees_of_freedom()
        else:
            return self._model_json["output"]["validation_metrics"].residual_degrees_of_freedom()
def residual_degrees_of_freedom(self, train=False, valid=False, xval=False):
        if xval: raise H2OValueError("Cross-validation metrics are not available.")
        if not train and not valid: train = True
        if train and valid:         train = True
        if train:
            return self._model_json["output"]["training_metrics"].residual_degrees_of_freedom()
        else:
            return self._model_json["output"]["validation_metrics"].residual_degrees_of_freedom()
def residual_degrees_of_freedom ( self , train = False , valid = False , xval = False ) : if xval : raise H2OValueError ( "Cross-validation metrics are not available." ) if not train and not valid : train = True if train and valid : train = True if train : return self . _model_json [ "output" ] [ "training_metrics" ] . residual_degrees_of_freedom ( ) else : return self . _model_json [ "output" ] [ "validation_metrics" ] . residual_degrees_of_freedom ( )
Retreive the residual degress of freedom if this model has the attribute, or None otherwise.

        :param bool train: Get the residual dof for the training set. If both train and valid are False, then train
            is selected by default.
        :param bool valid: Get the residual dof for the validation set. If both train and valid are True, then train
            is selected by default.

        :returns: Return the residual dof, or None if it is not present.
Retreive the residual degress of freedom if this model has the attribute or None otherwise .