code: def test_validation_curve(self):
      digits = datasets.load_digits()
      df = pdml.ModelFrame(digits)
  
      param_range = np.logspace(-2, -1, 2)
  
      svc = df.svm.SVC(random_state=self.random_state)
      result = df.model_selection.validation_curve(
          svc, "gamma", param_range
      )
      expected = ms.validation_curve(
          svm.SVC(random_state=self.random_state),
          digits.data,
          digits.target,
          "gamma",
          param_range,
      )
  
      self.assertEqual(len(result), 2)
      self.assert_numpy_array_almost_equal(result[0], expected[0])
      self.assert_numpy_array_almost_equal(result[1], expected[1])
  
imports: import sklearn.datasets
  import sklearn.svm
  import sklearn.naive_bayes
  import numpy
  import pandas
  import pandas_ml
  import pandas_ml.util.testing
label_desc: Use image node_id 2 for calling the TestModelValidation obj's underlying member method code with example usage: obj.test_validation_curve() without return types