class_docstr: Node that splits the data in a Hoeffding Adaptive Tree.
  
  Parameters
  ----------
  stats
      Class observations
  adwin_delta
      The delta parameter of ADWIN.
  children
      Sequence of children nodes of this branch.
  attributes
      Other parameters passed to the split node.
docstr: Iterate over leaves from the left-most one to the right-most one.
  
  Overrides the base implementation by also including alternate subtrees.
code: def iter_leaves(self):
      """Iterate over leaves from the left-most one to the right-most one.
  
      Overrides the base implementation by also including alternate subtrees.
      """
      for child in self.children:
          yield from child.iter_leaves()
  
          if (
              isinstance(child, AdaBranchClassifier)
              and child._alternate_tree
          ):
              yield from child._alternate_tree.iter_leaves()
  
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 3 for calling the AdaBranchClassifier obj's underlying member method code with example usage: obj.iter_leaves() without return types