class_docstr: Class for explaining metric values in JSON format.
  
  These briefly explain what a metric is and/or how it is calculated unless
  it is obvious (e.g. accuracy) and print the value.
  
  This class contains JSON explanations for all metric values regardless of
  which subclass they appear in. This will raise an error if the metric does
  not apply (e.g. calling `true_positive_rate` if
  `type(metric) == DatasetMetric`).
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code: def sensitivity(self, privileged=None):
      return self.true_positive_rate(privileged=privileged)
  
imports: from collections import OrderedDict
  import json
  from aif360.explainers import MetricTextExplainer
  from aif360.metrics import BinaryLabelDatasetMetric
label_desc: Use image node_id 50 for calling the MetricJSONExplainer obj's underlying member method code with example usage: obj.sensitivity(privileged) and returns: self