class_docstr: Class to represent Naive Bayes. Naive Bayes is a special case of Bayesian Model
  where the only edges in the model are from the feature variables to the dependent variable.
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docstr: Returns a list of all ancestors of all the observed nodes.
  
  Parameters
  ----------
  obs_nodes_list: string, list-type
      name of all the observed nodes
docstr_tok: ["Returns","a","list","of","all","ancestors","of","all","the","observed","nodes",".","Parameters","--","--","--","--","--","obs_nodes_list",":","string",",","list-type","name","of","all","the","observed","nodes"]
code: def _get_ancestors_of(self, obs_nodes_list):
      """
      Returns a list of all ancestors of all the observed nodes.
  
      Parameters
      ----------
      obs_nodes_list: string, list-type
          name of all the observed nodes
      """
      if not obs_nodes_list:
          return set()
      return set(obs_nodes_list) | set(self.dependent)
  
file_path: pgmpy/pgmpy/models/NaiveBayes.py
imports: from pgmpy.independencies import Independencies
  from pgmpy.models import BayesianNetwork
label_desc: Use image node_id 4 for calling the NaiveBayes obj's underlying member method code with example usage: obj._get_ancestors_of(obs_nodes_list) and returns: unknown, set