class_docstr: Unit test class for testing scikit-learn converter.
class_docstr_tok: ["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.
      """
      from sklearn.datasets import load_boston
  
      scikit_data = load_boston()
      scikit_model = GradientBoostingClassifier(random_state=1)
      target = scikit_data["target"] > scikit_data["target"].mean()
      scikit_model.fit(scikit_data["data"], target)
  
      # Save the data and the model
      self.scikit_data = scikit_data
      self.scikit_model = scikit_model
  
imports: import unittest
  import tempfile
  import json
  from sklearn.ensemble import GradientBoostingClassifier
  from coremltools.converters import sklearn
  from coremltools.proto import Model_pb2
  from coremltools.proto import FeatureTypes_pb2
  from coremltools._deps import _HAS_XGBOOST
  from coremltools._deps import _HAS_SKLEARN
label_desc: Use image node_id 1 for calling the GradientBoostingBinaryClassifierScikitTest obj's underlying member method code with example usage: obj.setUpClass() without return types