code: def init_missing(self, n_missing):
      w = 1.0
      self.n_missing = n_missing
      if n_missing == 0:
          return
      self.sum_missing[0 : self.n_outputs, 0 : self.max_n_classes] = 0
      self.weighted_n_missing = 0.0
      for p in range(self.end - n_missing, self.end):
          i = self.sample_indices[p]
          if self.sample_weight is not None:
              w = self.sample_weight[i]
  
          for k in range(self.n_outputs):
              c = int(self.y[i, k])
              self.sum_missing[k, c] += w
  
          self.weighted_n_missing += w
  
imports: from abc import ABC, abstractmethod
  import ivy
label_desc: Use image node_id 5 for calling the ClassificationCriterion obj's underlying member method code with example usage: obj.init_missing(n_missing) without return types