class_docstr: Jaccard score.
  
  Parameters
  ----------
  cm
      This parameter allows sharing the same confusion matrix between multiple metrics. Sharing
      a confusion matrix reduces the amount of storage and computation time.
  pos_val
      Value to treat as "positive".
  
  Examples
  --------
  
  >>> from river import metrics
  
  >>> y_true = [False, True, True]
  >>> y_pred = [True, True, True]
  
  >>> metric = metrics.Jaccard()
  
  >>> for yt, yp in zip(y_true, y_pred):
  ...     metric.update(yt, yp)
  ...     print(metric)
  Jaccard: 0.00%
  Jaccard: 50.00%
  Jaccard: 66.67%
  
  References
  ----------
  [^1]: [Jaccard index](https://www.wikiwand.com/en/Jaccard_index)
code: def get(self):
      tp = self.cm.true_positives(self.pos_val)
      fp = self.cm.false_positives(self.pos_val)
      fn = self.cm.false_negatives(self.pos_val)
      try:
          return tp / (tp + fp + fn)
      except ZeroDivisionError:
          return 0.0
  
file_path: river/river/metrics/jaccard.py
imports: from __future__ import annotations
  from river import metrics
label_desc: Use image node_id 1 for calling the Jaccard obj's underlying member method code with example usage: obj.get() and returns: unknown, int