code: def test_missing_data(self):
      e1 = MaximumLikelihoodEstimator(
          self.m1, self.d2, state_names={"C": [0, 1]}
      )
      cpds1 = [
          TabularCPD("A", 2, [[0.5], [0.5]]),
          TabularCPD("B", 2, [[2.0 / 3], [1.0 / 3]]),
          TabularCPD(
              "C",
              2,
              [[0, 0.5, 0.5, 0.5], [1, 0.5, 0.5, 0.5]],
              evidence=["A", "B"],
              evidence_card=[2, 2],
          ),
      ]
      self.assertEqual(e1.estimate_cpd("A"), cpds1[0])
      self.assertEqual(e1.estimate_cpd("B"), cpds1[1])
      self.assertEqual(e1.estimate_cpd("C"), cpds1[2])
      self.assertEqual(len(e1.get_parameters(n_jobs=1)), 3)
  
imports: import unittest
  import numpy
  import pandas
  from joblib.externals.loky import get_reusable_executor
  from pgmpy import config
  from pgmpy.estimators import MaximumLikelihoodEstimator
  from pgmpy.factors.discrete import TabularCPD
  from pgmpy.models import BayesianNetwork
label_desc: Use image node_id 9 for calling the TestMLETorch obj's underlying member method code with example usage: obj.test_missing_data() without return types