code: def test_rej_opt_clf_custom_scoring(new_adult):
      X, y, sample_weight = new_adult
      scoring = make_scorer(
          generalized_entropy_error, greater_is_better=False
      )
      pp = PostProcessingMeta(
          LogisticRegression(solver="lbfgs", max_iter=500),
          RejectOptionClassifierCV(
              "sex", scoring=scoring, step=0.1, refit=False, n_jobs=-1
          ),
      )
      pp.fit(X, y, sample_weight=sample_weight)
      res = pd.DataFrame(pp.postprocessor_.cv_results_)
      assert not res.isna().any(axis=None)
  
file_path: AIF360/tests/sklearn/test_reject_option_classification.py
imports: from itertools import product
  import numpy
  import pandas
  import pytest
  from sklearn.linear_model import LogisticRegression
  from sklearn.model_selection import train_test_split
  from sklearn.metrics import make_scorer
  from aif360.algorithms.postprocessing import RejectOptionClassification
  from aif360.sklearn.postprocessing import RejectOptionClassifier, RejectOptionClassifierCV, PostProcessingMeta
  from aif360.sklearn.metrics import generalized_entropy_error
label_desc: Use image node_id 10 for calling a global function with example usage: test_rej_opt_clf_custom_scoring(new_adult) without return types