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: Return the leaves corresponding to the given input.
  
  Alternate subtree leaves are also included.
  
  Parameters
  ----------
  x
      The input instance.
  until_leaf
      Whether or not branch nodes can be returned in case of missing features or emerging
      feature categories.
code: def traverse(self, x, until_leaf=True) -> list[HTLeaf]:  # type: ignore
      """Return the leaves corresponding to the given input.
  
      Alternate subtree leaves are also included.
  
      Parameters
      ----------
      x
          The input instance.
      until_leaf
          Whether or not branch nodes can be returned in case of missing features or emerging
          feature categories.
      """
      found_nodes: list[HTLeaf] = []
      for node in self.walk(x, until_leaf=until_leaf):
          if (
              isinstance(node, AdaBranchClassifier)
              and node._alternate_tree
          ):
              if isinstance(node._alternate_tree, AdaBranchClassifier):
                  found_nodes.append(
                      node._alternate_tree.traverse(x, until_leaf=until_leaf)  # type: ignore
                  )
              else:
                  found_nodes.append(node._alternate_tree)  # type: ignore
  
      found_nodes.append(node)  # type: ignore
      return found_nodes
  
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 AdaBranchClassifier obj's underlying member method code with example usage: obj.traverse(x, until_leaf) and returns: found_nodes