class_docstr: Adapter for using `hcrystalball` forecasters in sktime.
  
  Adapter class - wraps any forecaster from `hcrystalball`
  and allows using it as an `sktime` `BaseForecaster`.
  
  Parameters
  ----------
  model : The HCrystalBall forecasting model to use.
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docstr: Make forecasts for the given forecast horizon.
  
  Parameters
  ----------
  fh : int, list or np.array
      The forecast horizon with the steps ahead to predict
  X : pd.DataFrame, optional (default=None)
      Exogenous variables (ignored)
  
  Returns
  -------
  y_pred : pd.Series
      Point predictions for the forecast
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code: def _predict(self, fh=None, X=None):
      """Make forecasts for the given forecast horizon.
  
      Parameters
      ----------
      fh : int, list or np.array
          The forecast horizon with the steps ahead to predict
      X : pd.DataFrame, optional (default=None)
          Exogenous variables (ignored)
  
      Returns
      -------
      y_pred : pd.Series
          Point predictions for the forecast
      """
      X_pred = _get_X_pred(X, index=fh.to_absolute_index(self.cutoff))
      y_pred = self.model_.predict(X=X_pred)
      return _adapt_y_pred(y_pred)
  
file_path: sktime/sktime/forecasting/adapters/_hcrystalball.py
imports: import pandas
  from sklearn.base import clone
  from sktime.forecasting.base import BaseForecaster
  from sktime.utils.validation._dependencies import _check_soft_dependencies
label_desc: Use image node_id 3 for calling the HCrystalBallAdapter obj's underlying member method code with example usage: obj._predict(fh, X) and returns: _adapt_y_pred