class_docstr: Learning node for Hoeffding Adaptive Tree.
  
  Parameters
  ----------
  stats
      Initial class observations.
  depth
      The depth of the learning node in the tree.
  splitter
      The numeric attribute observer algorithm used to monitor target statistics
      and perform split attempts.
  drift_detector
      The detector used internally to monitor drifts.
  rng
      Random number generator used in Poisson sampling.
  kwargs
      Other parameters passed to the learning node.
code: def kill_tree_children(self, hat):
      pass
  
imports: from __future__ import annotations
  import math
  from river import stats
  from river.utils.norm import normalize_values_in_dict
  from river.utils.random import poisson
  from ..utils import do_naive_bayes_prediction
  from .branch import DTBranch, NominalBinaryBranch, NominalMultiwayBranch, NumericBinaryBranch, NumericMultiwayBranch
  from .htc_nodes import LeafNaiveBayesAdaptive
  from .leaf import HTLeaf
label_desc: Use image node_id 2 for calling the AdaLeafClassifier obj's underlying member method code with example usage: obj.kill_tree_children(hat) without return types