class_docstr: Class that stores the attributes of a tree node.
  
  Parameters
  ----------
  class_label
      Class label if the node is a leaf node.
  
  split_feature_idx
      Feature index for the split, if the node is a split node.
  
  split_feature_val
      Feature value for the split, if the node is a split node.
class_docstr_tok: ["Class","that","stores","the","attributes","of","a","tree","node",".","Parameters","--","--","--","--","--","class_label","Class","label","if","the","node","is","a","leaf","node",".","split_feature_idx","Feature","index","for","the","split",",","if","the","node","is","a","split","node",".","split_feature_val","Feature","value","for","the","split",",","if","the","node","is","a","split","node","."]
code: def __init__(
      self,
      class_label: int | None = None,
      split_feature_idx: int | None = None,
      split_feature_val: int | float | None = None,
  ):
      self.class_label = class_label
      self.split_feature_idx = split_feature_idx
      self.split_feature_val = split_feature_val
      self.children: list = []
  
file_path: river/river/datasets/synth/random_tree.py
imports: from __future__ import annotations
  import random
  from river import datasets
label_desc: Use image node_id 1 to create a new TreeNode object  with example: obj = TreeNode(class_label, split_feature_idx, split_feature_val)