class_docstr: An implementation of `"FEATHER-N" <https://arxiv.org/abs/2005.07959>`_
  from the CIKM '20 paper "Characteristic Functions on Graphs: Birds of a Feather,
  from Statistical Descriptors to Parametric Models". The procedure
  uses characteristic functions of node features with random walk weights to describe
  node neighborhoods.
  
  Args:
      reduction_dimensions (int): SVD reduction dimensions. Default is 64.
      svd_iterations (int): SVD iteration count. Default is 20.
      theta_max (float): Maximal evaluation point. Default is 2.5.
      eval_points (int): Number of characteristic function evaluation points. Default is 25.
      order (int): Scale - number of adjacency matrix powers. Default is 5.
      seed (int): Random seed value. Default is 42.
docstr: Creating a sparse normalized adjacency matrix.
  
  Arg types:
      * **graph** *(NetworkX graph)* - The graph to be embedded.
  Return types:
      * **A_tilde** *(Scipy array)* - The normalized adjacency matrix.
docstr_tok: ["Creating","a","sparse","normalized","adjacency","matrix",".","Arg","types",":","*","*","*","graph","*","*","*","(","NetworkX","graph",")","*","-","The","graph","to","be","embedded",".","Return","types",":","*","*","*","A_tilde","*","*","*","(","Scipy","array",")","*","-","The","normalized","adjacency","matrix","."]
code: def _create_A_tilde(self, graph):
      """
      Creating a sparse normalized adjacency matrix.
  
      Arg types:
          * **graph** *(NetworkX graph)* - The graph to be embedded.
      Return types:
          * **A_tilde** *(Scipy array)* - The normalized adjacency matrix.
      """
      A = nx.adjacency_matrix(
          graph, nodelist=range(graph.number_of_nodes())
      )
      D_inverse = self._create_D_inverse(graph)
      A_tilde = D_inverse.dot(A)
      return A_tilde
  
file_path: karateclub/karateclub/node_embedding/attributed/feathernode.py
imports: import scipy
  import numpy
  import networkx
  from typing import Union
  from scipy.sparse import coo_matrix
  from karateclub.estimator import Estimator
  from sklearn.decomposition import TruncatedSVD
label_desc: Use image node_id 3 for calling the FeatherNode obj's underlying member method code with example usage: obj._create_A_tilde(graph) and returns: A_tilde