original_docstring:  Discard method to remove all samples from the training set that are
              not in the border of their class.
  
              The border is determined by a minimum distance from the center of
              the class and a maximum distance.
  
              :param retraining_required: flag if retraining is
                      required (the new point is a potential sv or a removed
                      one was a sv)
          
docstring: Discard method to remove all samples from the training set that are
  not in the border of their class.
  
  The border is determined by a minimum distance from the center of
  the class and a maximum distance.
docstring_tokens: Discard method to remove all samples from the training set that are not in the border of their class . The border is determined by a minimum distance from the center of the class and a maximum distance .
code: def remove_no_border_points(self, retraining_required):
          """ Discard method to remove all samples from the training set that are
              not in the border of their class.
  
              The border is determined by a minimum distance from the center of
              the class and a maximum distance.
  
              :param retraining_required: flag if retraining is
                      required (the new point is a potential sv or a removed
                      one was a sv)
          """
          raise NotImplementedError(
              "The node %s does not implement a border point handling." \
              % self.__class__.__name__)
code_tokens: def remove_no_border_points ( self , retraining_required ) : raise NotImplementedError ( "The node %s does not implement a border point handling." % self . __class__ . __name__ )
short_docstring: Discard method to remove all samples from the training set that are
  not in the border of their class.
short_docstring_tokens: Discard method to remove all samples from the training set that are not in the border of their class .
comment: """ Discard method to remove all samples from the training set that are
              not in the border of their class.
  
              The border is determined by a minimum distance from the center of
              the class and a maximum distance.
  
              :param retraining_required: flag if retraining is
                      required (the new point is a potential sv or a removed
                      one was a sv)
          """