code: def gamma(self, y_true, y_pred, sens):
      pos_0 = y_pred[sens == 0] == 1
      pos_1 = y_pred[sens == 1] == 1
      if np.sum(pos_0) == 0 or np.sum(pos_1) == 0:
          return 0
      fdr_0 = np.sum(pos_0 & (y_true[sens == 0] == -1)) / np.sum(pos_0)
      fdr_1 = np.sum(pos_1 & (y_true[sens == 1] == -1)) / np.sum(pos_1)
      if fdr_0 == 0 or fdr_1 == 0:
          return 0
      return min(fdr_0 / fdr_1, fdr_1 / fdr_0)
  
file_path: AIF360/aif360/algorithms/inprocessing/celisMeta/FalseDiscovery.py
imports: import numpy
  from aif360.algorithms.inprocessing.celisMeta.General import General
label_desc: Use image node_id 5 for calling the FalseDiscovery obj's underlying member method code with example usage: obj.gamma(y_true, y_pred, sens) and returns: min, int, int