code: def setUpClass(self):
      scikit_data = load_boston()
      num_classes = 3
      self.X = scikit_data.data.astype("f").astype(
          "d"
      )  ## scikit-learn downcasts data
      t = scikit_data.target
      target = (
          np.digitize(t, np.histogram(t, bins=num_classes - 1)[1]) - 1
      )
  
      # Save the data and the model
      self.scikit_data = scikit_data
      self.target = target
      self.feature_names = scikit_data.feature_names
      self.output_name = "target"
  
imports: import itertools
  import unittest
  import numpy
  import pandas
  import pytest
  from coremltools._deps import _HAS_SKLEARN, _HAS_XGBOOST
  from coremltools.models.utils import _is_macos, _macos_version, evaluate_classifier, evaluate_classifier_with_probabilities
label_desc: Use image node_id 1 for calling the BoostedTreeMultiClassClassificationBostonHousingXGboostNumericTest obj's underlying member method code with example usage: obj.setUpClass() without return types