class_docstr: A node in a shadow tree. Each node has left and right pointers to child nodes, if any.
  As part of tree construction process, the samples examined at each decision node or at each leaf node are
  saved into field node_samples.
class_docstr_tok: ["A","node","in","a","shadow","tree",".","Each","node","has","left","and","right","pointers","to","child","nodes",",","if","any",".","As","part","of","tree","construction","process",",","the","samples","examined","at","each","decision","node","or","at","each","leaf","node","are","saved","into","field","node_samples","."]
docstr: If the tree model is a classifier and we know the class names, return the class name associated with the
  prediction for this leaf node.
  
  Return prediction class or value otherwise.
docstr_tok: ["If","the","tree","model","is","a","classifier","and","we","know","the","class","names",",","return","the","class","name","associated","with","the","prediction","for","this","leaf","node",".","Return","prediction","class","or","value","otherwise","."]
code: def prediction_name(self) -> (str, None):
      """
      If the tree model is a classifier and we know the class names, return the class name associated with the
      prediction for this leaf node.
  
      Return prediction class or value otherwise.
      """
      if self.isclassifier():
          # In a GBT model, the trees are always regressive trees (even if the GBT is a classifier).
          if (
              "tensorflow_decision_forests.keras.GradientBoostedTreesModel"
              in str(type(self.shadow_tree.tree_model))
          ):
              return round(self.prediction(), 6)
          if self.shadow_tree.class_names is not None:
              return self.shadow_tree.class_names[self.prediction()]
      return self.prediction()
  
imports: from abc import ABC, abstractmethod
  from numbers import Number
  from typing import List, Tuple, Mapping
  import numpy
  import pandas
  import sklearn
  from dtreeviz import utils
label_desc: Use image node_id 14 for calling the ShadowDecTreeNode obj's underlying member method code with example usage: obj.prediction_name() and returns: self, round, self