code: def test_rej_opt_clf_predict(
      new_adult, old_adult, log_reg_probs, old_ROC
  ):
      """Test RejectOptionClassifier predict matches old."""
      _, y, _ = new_adult
      old_adult_pred = old_adult.copy()
      old_adult_pred.scores = log_reg_probs[:, [1]]
  
      threshold = old_ROC.classification_threshold
      margin = old_ROC.ROC_margin
      ROC = RejectOptionClassifier(
          "sex", threshold=threshold, margin=margin
      )
      y_pred = pd.DataFrame(log_reg_probs, index=y.index)
      y_postpred = ROC.fit_predict(y_pred, y)
  
      assert np.allclose(
          y_postpred, old_ROC.predict(old_adult_pred).labels.ravel()
      )
  
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 5 for calling a global function with example usage: test_rej_opt_clf_predict(new_adult, old_adult, log_reg_probs, old_ROC) without return types