code: def _update(self, data, *args, **kwargs):
          
          if data is not None:
              data = np.asarray(data).flatten()
              data = np.append(data.flatten(), self.y)
          else:
              data = self.y
          self.__init__(data, *args, **kwargs)
docs: The only thing that *should* happen in this function is
          1. input sanitization for pandas
          2. classification/reclassification.
  
          Using their __init__ methods, all classifiers can re-classify given
          different input parameters or additional data.
  
          If you've got a cleverer updating equation than the intial estimation
          equation, remove the call to self.__init__ below and replace it with
          the updating function.