class_docstr: Unit test class for testing scikit-learn converter.
docstr: Set up the unit test by loading the dataset and training a model.
docstr_tok: ["Set","up","the","unit","test","by","loading","the","dataset","and","training","a","model","."]
code: def setUpClass(self):
      """
      Set up the unit test by loading the dataset and training a model.
      """
      scikit_data = [[0], [1], [2], [4], [3], [2], [4], [5], [6], [7]]
      scikit_data_multiple_cols = [
          [0, 1],
          [1, 0],
          [2, 2],
          [3, 3],
          [4, 4],
      ]
      scikit_model = OneHotEncoder()
      scikit_model.fit(scikit_data)
  
      # Save the data and the model
      self.scikit_data = np.asarray(scikit_data, dtype="d")
      self.scikit_data_multiple_cols = np.asarray(
          scikit_data_multiple_cols, dtype="d"
      )
      self.scikit_model = scikit_model
  
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 1 for calling the OneHotEncoderScikitTest obj's underlying member method code with example usage: obj.setUpClass() without return types