class_docstr: MrSEQL = Multiple Representations Sequence Learning classification model.
  
  Direct Interface to MrSEQLClassifier from mrseql.
  Note: mrseql itself is copyleft (GPL3). This interface is permissive license (BSD3).
  
  MrSEQL is an efficient time series classifier utilizing symbolic representations of
  time series, using SAX and SFA features.
  
  Parameters
  ----------
  seql_mode : str, either 'clf' or 'fs' (default).
      In the 'clf' mode, Mr-SEQL is an ensemble of SEQL models, while in the 'fs'
      mode Mr-SEQL, trains a logistic regression model with features extracted
      by SEQL from symbolic representations of time series.
  symrep : str, or list or tuple of string, strings being 'sax' or 'sfa'.
      default = "sax", i.e., only SAX features, no SFA features.
      The symbolic representations to be used to transform the input time series.
  custom_config : dict, optional, default=None
      Customized parameters for the symbolic transformation.
      If defined, symrep will be ignored.
      (no documentation of this parameter is provided in the original mrseql code)
  
  References
  ----------
  .. [1] Thach Le Nguyen, Severin Gsponer, Iulia Ilie, Martin O'Reilly,
     Georgiana Ifrim.
     "Interpretable Time Series Classification Using Linear Models and
     Multi-resolution Multi-domain Symbolic Representations",
     Data Mining and Knowledge Discovery, 2019.
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docstr: Get fitted parameters.
  
  private _get_fitted_params, called from get_fitted_params
  
  State required:
      Requires state to be "fitted".
  
  Returns
  -------
  fitted_params : dict with str keys
      fitted parameters, keyed by names of fitted parameter
docstr_tok: ["Get","fitted","parameters",".","private","_get_fitted_params",",","called","from","get_fitted_params","State","required",":","Requires","state","to","be","``","fitted","''",".","Returns","--","--","--","-","fitted_params",":","dict","with","str","keys","fitted","parameters",",","keyed","by","names","of","fitted","parameter"]
code: def _get_fitted_params(self):
      """Get fitted parameters.
  
      private _get_fitted_params, called from get_fitted_params
  
      State required:
          Requires state to be "fitted".
  
      Returns
      -------
      fitted_params : dict with str keys
          fitted parameters, keyed by names of fitted parameter
      """
      return {}
  
imports: from sktime.classification._delegate import _DelegatedClassifier
label_desc: Use image node_id 2 for calling the MrSEQL obj's underlying member method code with example usage: obj._get_fitted_params() and returns: dict