class_docstr: Base class for interfacing tbats forecasting algorithms.
class_docstr_tok: ["Base","class","for","interfacing","tbats","forecasting","algorithms","."]
docstr: Forecast time series at future horizon.
  
  Parameters
  ----------
  fh : int, list, np.array or ForecastingHorizon
      Forecasting horizon
  X : (default=None)
      NOT USED BY TBATS
  
  Returns
  -------
  y_pred : pd.Series
      Point predictions
docstr_tok: ["Forecast","time","series","at","future","horizon",".","Parameters","--","--","--","--","--","fh",":","int",",","list",",","np.array","or","ForecastingHorizon","Forecasting","horizon","X",":","(","default=None",")","NOT","USED","BY","TBATS","Returns","--","--","--","-","y_pred",":","pd.Series","Point","predictions"]
code: def _predict(self, fh, X):
      """Forecast time series at future horizon.
  
      Parameters
      ----------
      fh : int, list, np.array or ForecastingHorizon
          Forecasting horizon
      X : (default=None)
          NOT USED BY TBATS
  
      Returns
      -------
      y_pred : pd.Series
          Point predictions
      """
      return self._tbats_forecast(fh)
  
file_path: sktime/sktime/forecasting/base/adapters/_tbats.py
imports: import numpy
  import pandas
  from sktime.forecasting.base import BaseForecaster
  from sktime.utils.validation import check_n_jobs
  from sktime.utils.validation.forecasting import check_sp
label_desc: Use image node_id 6 for calling the _TbatsAdapter obj's underlying member method code with example usage: obj._predict(fh, X) and returns: self