def __init__(self):
        """Naive Mean Model

        This model has no parameter, and always predicts the
        mean value of the training series.

        Examples
        --------
        >>> from darts.datasets import AirPassengersDataset
        >>> from darts.models import NaiveMean
        >>> series = AirPassengersDataset().load()
        >>> model = NaiveMean()
        >>> model.fit(series)
        >>> pred = model.predict(6)
        >>> pred.values()
        array([[280.29861111],
              [280.29861111],
              [280.29861111],
              [280.29861111],
              [280.29861111],
              [280.29861111]])
        """
        super().__init__()
        self.mean_val = None
Naive Mean Model

        This model has no parameter, and always predicts the
        mean value of the training series.

        Examples
        --------
        >>> from darts.datasets import AirPassengersDataset
        >>> from darts.models import NaiveMean
        >>> series = AirPassengersDataset().load()
        >>> model = NaiveMean()
        >>> model.fit(series)
        >>> pred = model.predict(6)
        >>> pred.values()
        array([[280.29861111],
              [280.29861111],
              [280.29861111],
              [280.29861111],
              [280.29861111],
              [280.29861111]])
        
darts/models/forecasting/baselines.py