class_docstr: Unit test class for testing xgboost converter.
class_docstr_tok: ["Unit","test","class","for","testing","xgboost","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()
      self.xgb_model = xgboost.XGBClassifier()
      target = scikit_data["target"] > scikit_data["target"].mean()
      self.xgb_model.fit(scikit_data["data"], target)
  
      # Save the data and the model
      self.scikit_data = scikit_data
  
imports: import json
  import tempfile
  import unittest
  from coremltools._deps import _HAS_SKLEARN, _HAS_XGBOOST
  from coremltools.converters import sklearn
  from coremltools.models.utils import _macos_version
label_desc: Use image node_id 1 for calling the GradientBoostingBinaryClassifierXGboostTest obj's underlying member method code with example usage: obj.setUpClass() without return types