code: def test_learning_curve(self):
      digits = datasets.load_digits()
      df = pdml.ModelFrame(digits)
  
      result = df.model_selection.learning_curve(
          df.naive_bayes.GaussianNB()
      )
      expected = ms.learning_curve(
          nb.GaussianNB(), digits.data, digits.target
      )
  
      self.assertEqual(len(result), 3)
      self.assert_numpy_array_almost_equal(result[0], expected[0])
      self.assert_numpy_array_almost_equal(result[1], expected[1])
      self.assert_numpy_array_almost_equal(result[2], expected[2])
  
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 1 for calling the TestModelValidation obj's underlying member method code with example usage: obj.test_learning_curve() without return types