class_docstr: Unit test class for testing scikit-learn converter.
code: def test_conversion_many_columns(self):
      scikit_model = OneHotEncoder()
      scikit_model.fit(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.assertEquals(metrics["num_errors"], 0)
  
file_path: turicreate/src/external/coremltools_wrap/coremltools/coremltools/test/sklearn_tests/test_one_hot_encoder.py
imports: from copy import copy
  import unittest
  import numpy
  from coremltools._deps import _HAS_SKLEARN
  from coremltools.models.utils import evaluate_transformer, _macos_version, _is_macos
label_desc: Use image node_id 3 for calling the OneHotEncoderScikitTest obj's underlying member method code with example usage: obj.test_conversion_many_columns() without return types