code: def lfrfitmodel():
      privileged_groups = [{"sex": 1.0}]
      unprivileged_groups = [{"sex": 0.0}]
  
      lfrAlgoInstance = LFR(
          unprivileged_groups=unprivileged_groups,
          privileged_groups=privileged_groups,
      )
      ad = load_preproc_data_adult().split([0.7], shuffle=True)[0]
      TR = lfrAlgoInstance.fit(ad)
  
      return TR
  
file_path: AIF360/tests/test_lfr.py
imports: import os
  import sys
  import numpy
  import pytest
  from aif360.algorithms.preprocessing import LFR
  from aif360.algorithms.preprocessing.optim_preproc_helpers.data_preproc_functions import load_preproc_data_adult
label_desc: Use image node_id 3 for calling a global function with example usage: lfrfitmodel() and returns: TR