class_docstr: Mother class for all multi-output classification metrics.
  
  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.
class_docstr_tok: ["Mother","class","for","all","multi-output","classification","metrics",".","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","."]
docstr: Revert the metric.
docstr_tok: ["Revert","the","metric","."]
code: def revert(
      self,
      y_true: dict[str | int, base.typing.ClfTarget],
      y_pred: dict[str | int, base.typing.ClfTarget]
      | dict[str | int, dict[base.typing.ClfTarget, float]],
      w=1.0,
  ):
      """Revert the metric."""
      self.cm.revert(y_true, y_pred, w)
  
imports: from __future__ import annotations
  import abc
  from river import base, utils
  from river.metrics.base import Metric
  from .confusion import MultiLabelConfusionMatrix
label_desc: Use image node_id 3 for calling the MultiOutputClassificationMetric obj's underlying member method code with example usage: obj.revert(y_true, y_pred, w) without return types