class_docstr: Maintains a confusion matrix for a given classification problem.
  
  The ConfusionMeter constructs a confusion matrix for a multi-class
  classification problems. It does not support multi-label, multi-class problems:
  for such problems, please use MultiLabelConfusionMeter.
  
  :param k (int): number of classes in the classification problem
  :param normalized (boolean): Determines whether or not the confusion matrix is normalized or not
code: def __init__(self, k, normalized=False):
      super(ConfusionMeter, self).__init__()
      self.conf = np.ndarray((k, k), dtype=np.int32)
      self.normalized = normalized
      self.k = k
      self.reset()
  
imports: from .None import meter
  import numpy
label_desc: Use image node_id 1 to create a new ConfusionMeter object from inherited base classes: meter with example: obj = ConfusionMeter(k, normalized)