class_docstr: Unit test class for testing scikit-learn converter.
docstr: 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.
      """
      import numpy as np
      from sklearn.datasets import load_boston
      from sklearn.tree import DecisionTreeClassifier
  
      scikit_data = load_boston()
      scikit_model = DecisionTreeClassifier(random_state=1)
      t = scikit_data.target
      target = np.digitize(t, np.histogram(t)[1]) - 1
      scikit_model.fit(scikit_data.data, target)
  
      # Save the data and the model
      self.scikit_data = scikit_data
      self.target = target
      self.scikit_model = scikit_model
  
file_path: coremltools/coremltools/test/xgboost_tests/test_decision_tree_classifier.py
imports: import unittest
  from coremltools._deps import _HAS_SKLEARN, _HAS_XGBOOST
label_desc: Use image node_id 1 for calling the DecisionTreeMultiClassClassifierScikitTest obj's underlying member method code with example usage: obj.setUpClass() without return types