class_docstr: Base class for all forecasters in skforecast. All forecasters should specify
  all the parameters that can be set at the class level in their ``__init__``.     
docstr: Predict n steps ahead.
  
  Parameters
  ----------
  steps : int
      Number of future steps predicted.
  last_window : pandas Series, default `None`
      Series values used to create the predictors (lags) needed in the 
      first iteration of the prediction (t + 1).
      If `last_window = None`, the values stored in `self.last_window` are
      used to calculate the initial predictors, and the predictions start
      right after training data.
  exog : pandas Series, pandas DataFrame, default `None`
      Exogenous variable/s included as predictor/s.
  
  Returns
  -------
  predictions : pandas Series
      Predicted values.
code: def predict(
      self,
      steps: int,
      last_window: Optional[pd.Series] = None,
      exog: Optional[Union[pd.Series, pd.DataFrame]] = None,
  ) -> pd.Series:
      """
      Predict n steps ahead.
  
      Parameters
      ----------
      steps : int
          Number of future steps predicted.
      last_window : pandas Series, default `None`
          Series values used to create the predictors (lags) needed in the
          first iteration of the prediction (t + 1).
          If `last_window = None`, the values stored in `self.last_window` are
          used to calculate the initial predictors, and the predictions start
          right after training data.
      exog : pandas Series, pandas DataFrame, default `None`
          Exogenous variable/s included as predictor/s.
  
      Returns
      -------
      predictions : pandas Series
          Predicted values.
  
      """
  
      pass
  
file_path: skforecast/skforecast/ForecasterBase/ForecasterBase.py
imports: from abc import ABC, abstractmethod
  from typing import Union, Dict, List, Tuple, Any, Optional
  import logging
  import pandas
label_desc: Use image node_id 3 for calling the ForecasterBase obj's underlying member method code with example usage: obj.predict(steps, last_window, exog) without return types