class_docstr: Reweighing is a preprocessing technique that Weights the examples in each
  (group, label) combination differently to ensure fairness before
  classification [4]_.
  
  References:
      .. [4] F. Kamiran and T. Calders,  "Data Preprocessing Techniques for
         Classification without Discrimination," Knowledge and Information
         Systems, 2012.
docstr: Args:
      unprivileged_groups (list(dict)): Representation for unprivileged
          group.
      privileged_groups (list(dict)): Representation for privileged group.
code: def __init__(self, unprivileged_groups, privileged_groups):
      """
      Args:
          unprivileged_groups (list(dict)): Representation for unprivileged
              group.
          privileged_groups (list(dict)): Representation for privileged group.
      """
      super(Reweighing, self).__init__(
          unprivileged_groups=unprivileged_groups,
          privileged_groups=privileged_groups,
      )
  
      self.unprivileged_groups = unprivileged_groups
      self.privileged_groups = privileged_groups
  
      self.w_p_fav = 1.0
      self.w_p_unfav = 1.0
      self.w_up_fav = 1.0
      self.w_up_unfav = 1.0
  
file_path: AIF360/aif360/algorithms/preprocessing/reweighing.py
imports: import numpy
  from aif360.algorithms import Transformer
  from aif360.metrics import utils
label_desc: Use image node_id 1 to create a new Reweighing object from inherited base classes: Transformer with example: obj = Reweighing(unprivileged_groups, privileged_groups)