docstr: Updates the model.
  
  Parameters
  ----------
  y
      In the literature this is called the endogenous variable.
  x
      Optional additional features to learn from. In the literature these are called the
      exogenous variables.
docstr_tok: ["Updates","the","model",".","Parameters","--","--","--","--","--","y","In","the","literature","this","is","called","the","endogenous","variable",".","x","Optional","additional","features","to","learn","from",".","In","the","literature","these","are","called","the","exogenous","variables","."]
code: def learn_one(self, y: float, x: dict | None = None) -> Forecaster:
      """Updates the model.
  
      Parameters
      ----------
      y
          In the literature this is called the endogenous variable.
      x
          Optional additional features to learn from. In the literature these are called the
          exogenous variables.
  
      """
      raise NotImplementedError
  
file_path: river/river/time_series/base.py
imports: from __future__ import annotations
  import abc
  from river import base
label_desc: Use image node_id 2 for calling the Forecaster obj's underlying member method code with example usage: obj.learn_one(y, x) without return types