def setUpClass(self):
        """
        Set up the unit test by loading the dataset and training a model.
        """
        scikit_data = load_boston()
        scikit_model = GradientBoostingClassifier(random_state=1)
        t = scikit_data["target"]
        target = np.digitize(t, np.histogram(t)[1]) - 1
        scikit_model.fit(scikit_data["data"], target)
        self.target = target

        s = 0
        for est in scikit_model.estimators_:
            for e in est:
                s = s + e.tree_.node_count
        self.scikit_model_node_count = s
        
        # Save the data and the model
        self.scikit_data = scikit_data
        self.scikit_model = scikit_model

        Set up the unit test by loading the dataset and training a model.
        
coremltools/test/xgboost_tests/test_boosted_trees_classifier.py