class_docstr: Compute precision, recall, F-measure for each class            of a general multi-class problem.
class_docstr_tok: ["Compute","precision",",","recall",",","F-measure","for","each","class","of","a","general","multi-class","problem","."]
docstr: This method accumulates TPs, FPs, and FNs for each label
  :param gold: The gold label.
  :param prediction: The predicted label.
docstr_tok: ["This","method","accumulates","TPs",",","FPs",",","and","FNs","for","each","label",":","param","gold",":","The","gold","label",".",":","param","prediction",":","The","predicted","label","."]
code: def __call__(self, gold: str, prediction: str) -> None:
      """
      This method accumulates TPs, FPs, and FNs for each label
      :param gold: The gold label.
      :param prediction: The predicted label.
      """
      if prediction == gold:
          self._true_positives[prediction] += 1
      else:
          self._false_positives[prediction] += 1
          self._false_negatives[gold] += 1
  
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 FMeasure obj's underlying member method code with example usage: obj.__call__(gold, prediction) without return types