class_docstr: Unit test class for testing scikit-learn converter.
code: def test_conversion_one_column_of_several(self):
      if _SKLEARN_VERSION >= StrictVersion("0.22"):
          scikit_model = OneHotEncoder()
      else:
          scikit_model = OneHotEncoder(categorical_features=[0])
  
      scikit_model.fit(copy(self.scikit_data_multiple_cols))
      spec = sklearn.convert(
          scikit_model, ["feature_1", "feature_2"], "out"
      ).get_spec()
  
      test_data = [
          {"feature_1": row[0], "feature_2": row[1]}
          for row in self.scikit_data_multiple_cols
      ]
      scikit_output = [
          {"out": row}
          for row in scikit_model.transform(
              self.scikit_data_multiple_cols
          ).toarray()
      ]
      metrics = evaluate_transformer(spec, test_data, scikit_output)
  
      self.assertIsNotNone(spec)
      self.assertIsNotNone(spec.description)
      self.assertEqual(metrics["num_errors"], 0)
  
file_path: coremltools/coremltools/test/sklearn_tests/test_one_hot_encoder.py
imports: import unittest
  from copy import copy
  from distutils.version import StrictVersion
  import numpy
  from coremltools._deps import _HAS_SKLEARN, _SKLEARN_VERSION
  from coremltools.models.utils import _is_macos, _macos_version, evaluate_transformer
label_desc: Use image node_id 4 for calling the OneHotEncoderScikitTest obj's underlying member method code with example usage: obj.test_conversion_one_column_of_several() without return types