code: def get_prediction(self, id):
      all_nodes = self.internal + self.leaves
      if self.is_classifier():
          node_value = [
              node.n_sample_classes()
              for node in all_nodes
              if node.id == id
          ]
          return np.argmax(node_value[0])
      elif not self.is_classifier():
          node_samples = [
              node.samples() for node in all_nodes if node.id == id
          ][0]
          return np.mean(self.y_train[node_samples])
  
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 26 for calling the ShadowXGBDTree obj's underlying member method code with example usage: obj.get_prediction(id) and returns: np, np