code: def get_prediction(self, id):
      if self.is_classifier():
          counts = self.tree_model.tree_.value[id][0]
          return np.argmax(counts)
      else:
          return self.tree_model.tree_.value[id][0][0]
  
imports: from collections import defaultdict
  from typing import List, Mapping
  import numpy
  from sklearn.utils import compute_class_weight
  from dtreeviz.models.shadow_decision_tree import ShadowDecTree
  from dtreeviz.utils import criterion_remapping
label_desc: Use image node_id 20 for calling the ShadowSKDTree obj's underlying member method code with example usage: obj.get_prediction(id) and returns: np, self