class_docstr: The SLUF1 metric mediates between the WordF1 and CharF1,            computed as the sum of the confusion matrices.
  For more information, please see `SLURP: A Spoken Language Understanding            Resource Package` by Bastianelli, Vanzo,
  Swietojanski, and Rieser.
class_docstr_tok: ["The","SLUF1","metric","mediates","between","the","WordF1","and","CharF1",",","computed","as","the","sum","of","the","confusion","matrices",".","For","more","information",",","please","see","`","SLURP",":","A","Spoken","Language","Understanding","Resource","Package","`","by","Bastianelli",",","Vanzo",",","Swietojanski",",","and","Rieser","."]
docstr: This method accumulates TPs, FPs, and FNs given the results dictionary                output by another metric.
  
  :param results: The dictionary output by another metric.
docstr_tok: ["This","method","accumulates","TPs",",","FPs",",","and","FNs","given","the","results","dictionary","output","by","another","metric",".",":","param","results",":","The","dictionary","output","by","another","metric","."]
code: def __call__(self, results: Dict[str, Tuple[float, ...]]) -> None:
      """
          This method accumulates TPs, FPs, and FNs given the results dictionary\
                  output by another metric.
  
          :param results: The dictionary output by another metric.
          """
      for label in results:
          if label != "overall":
              self._true_positives[label] += results[label][3]
              self._false_positives[label] += results[label][4]
              self._false_negatives[label] += results[label][5]
  
imports: from collections import defaultdict
  from copy import copy
  from typing import Dict, List, Set, Tuple
  from .distance import Distance
label_desc: Use image node_id 1 for calling the SLUF1 obj's underlying member method code with example usage: obj.__call__(results) without return types