code: def nclasses(self):
      if not self.is_classifier():
          return 1
      else:
          return len(np.unique(self.y_train))
  
imports: import json
  import math
  from collections import defaultdict
  from typing import List, Mapping
  import numpy
  from dtreeviz.models.shadow_decision_tree import VisualisationNotYetSupportedError
  from dtreeviz.models.shadow_decision_tree import ShadowDecTree
  from dtreeviz import utils
  import xgboost
  from xgboost.core import Booster
label_desc: Use image node_id 29 for calling the ShadowXGBDTree obj's underlying member method code with example usage: obj.nclasses() and returns: int, len