class_docstr: Base class for interfacing prophet and neuralprophet.
class_docstr_tok: ["Base","class","for","interfacing","prophet","and","neuralprophet","."]
docstr: Get fitted parameters.
  
  Returns
  -------
  fitted_params : dict
  
  References
  ----------
  https://facebook.github.io/prophet/docs/additional_topics.html
docstr_tok: ["Get","fitted","parameters",".","Returns","--","--","--","-","fitted_params",":","dict","References","--","--","--","--","--","https",":","\/\/facebook.github.io\/prophet\/docs\/additional_topics.html"]
code: def _get_fitted_params(self):
      """Get fitted parameters.
  
      Returns
      -------
      fitted_params : dict
  
      References
      ----------
      https://facebook.github.io/prophet/docs/additional_topics.html
      """
      fitted_params = {}
      for name in ["k", "m", "sigma_obs"]:
          fitted_params[name] = self._forecaster.params[name][0][0]
      for name in ["delta", "beta"]:
          fitted_params[name] = self._forecaster.params[name][0]
      return fitted_params
  
imports: import os
  import pandas
  from sktime.forecasting.base import BaseForecaster
label_desc: Use image node_id 9 for calling the _ProphetAdapter obj's underlying member method code with example usage: obj._get_fitted_params() and returns: fitted_params