code: def is_classifier(self):
      objective_name = self.config["learner"]["objective"][
          "name"
      ].split(":")[0]
      if objective_name == "binary" or objective_name == "multi":
          return True
      elif objective_name == "reg":
          return False
      return None
  
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 27 for calling the ShadowXGBDTree obj's underlying member method code with example usage: obj.is_classifier() and returns: None, True, False