class_docstr: Unit test class for testing scikit-learn converter.
code: def test_boston_OHE(self):
      data = load_boston()
  
      for categorical_features in [[3], [8], [3, 8], [8, 3]]:
          model = OneHotEncoder(
              categorical_features=categorical_features, sparse=False
          )
          model.fit(data.data, data.target)
  
          # Convert the model
          spec = sklearn.convert(
              model, data.feature_names, "out"
          ).get_spec()
  
          input_data = [
              dict(zip(data.feature_names, row)) for row in data.data
          ]
          output_data = [
              {"out": row} for row in model.transform(data.data)
          ]
  
          result = evaluate_transformer(spec, input_data, output_data)
  
          assert result["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 5 for calling the OneHotEncoderScikitTest obj's underlying member method code with example usage: obj.test_boston_OHE() without return types