docstr: The cost of eliminating a node is the number of neighbors it has in the
  current graph.
docstr_tok: ["The","cost","of","eliminating","a","node","is","the","number","of","neighbors","it","has","in","the","current","graph","."]
code: def cost(self, node):
      """
      The cost of eliminating a node is the number of neighbors it has in the
      current graph.
      """
      return len(list(self.moralized_model.neighbors(node)))
  
imports: from abc import abstractmethod
  from itertools import combinations
  import numpy
  from tqdm.auto import tqdm
  from pgmpy import config
  from pgmpy.models import BayesianNetwork
label_desc: Use image node_id 1 for calling the MinNeighbors obj's underlying member method code with example usage: obj.cost(node) and returns: len