class_docstr: Explanation object specific to trees.
class_docstr_tok: ["Explanation","object","specific","to","trees","."]
code: def _weight_nodes_decision(self, nodes, decision_nodes):
      nodes = deepcopy(nodes)
  
      new_nodes = []
      for node in nodes:
          node_id = int(node["data"]["id"])
          if node_id in decision_nodes:
              node["data"]["weight"] = 2
          else:
              node["data"]["weight"] = 1
          new_nodes.append(node)
  
      return new_nodes
  
imports: from ..api.base import ExplainerMixin, ExplanationMixin
  from ..utils._explanation import gen_name_from_class, gen_local_selector, gen_global_selector, gen_perf_dicts
  from sklearn.base import ClassifierMixin, RegressorMixin
  from sklearn.tree import DecisionTreeClassifier
  from sklearn.tree import DecisionTreeRegressor
  from sklearn.base import is_classifier
  from sklearn.utils.validation import check_is_fitted
  import numpy
  from abc import abstractmethod
  from sklearn.tree import _tree
  from copy import deepcopy
  from ..utils._clean_x import preclean_X
  from ..utils._clean_simple import clean_dimensions, typify_classification
  from ..utils._unify_data import unify_data
  import logging
label_desc: Use image node_id 5 for calling the TreeExplanation obj's underlying member method code with example usage: obj._weight_nodes_decision(nodes, decision_nodes) and returns: new_nodes