class_docstr: Example:
      >>> #The dataset is split into data, validation_data
      >>> model = ProphetForecaster(changepoint_prior_scale=0.05, seasonality_mode='additive')
      >>> model.fit(data, validation_data)
      >>> predict_result = model.predict(horizon=24)
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docstr: Fit(Train) the forecaster.
  
  :param data: training data, a pandas dataframe with Td rows,
      and 2 columns, with column 'ds' indicating date and column 'y' indicating value
      and Td is the time dimension
  :param validation_data: evaluation data, should be the same type as data
  
  :return: the evaluation metric value
docstr_tok: ["Fit","(","Train",")","the","forecaster",".",":","param","data",":","training","data",",","a","pandas","dataframe","with","Td","rows",",","and","2","columns",",","with","column","'ds","'","indicating","date","and","column","'","y","'","indicating","value","and","Td","is","the","time","dimension",":","param","validation_data",":","evaluation","data",",","should","be","the","same","type","as","data",":","return",":","the","evaluation","metric","value"]
code: def fit(self, data, validation_data=None):
      """
      Fit(Train) the forecaster.
  
      :param data: training data, a pandas dataframe with Td rows,
          and 2 columns, with column 'ds' indicating date and column 'y' indicating value
          and Td is the time dimension
      :param validation_data: evaluation data, should be the same type as data
  
      :return: the evaluation metric value
      """
      self._check_data(data, validation_data)
      return self.internal.fit_eval(
          data=data,
          validation_data=validation_data,
          **self.model_config,
      )
  
file_path: BigDL/python/chronos/src/bigdl/chronos/forecaster/prophet_forecaster.py
imports: from bigdl.chronos.forecaster.abstract import Forecaster
  from bigdl.chronos.model.prophet import ProphetModel
label_desc: Use image node_id 2 for calling the ProphetForecaster obj's underlying member method code with example usage: obj.fit(data, validation_data) and returns: self