code: def new_ROC(new_adult, log_reg_probs):
      """Fit new ROC."""
      _, y, _ = new_adult
      y_pred = pd.DataFrame(log_reg_probs, index=y.index)
  
      ROC = RejectOptionClassifierCV(
          "sex", scoring="statistical_parity", step=0.1, n_jobs=-1
      )
      return ROC.fit(y_pred, y)
  
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 3 for calling a global function with example usage: new_ROC(new_adult, log_reg_probs) and returns: ROC