aif360.algorithms.postprocessing.EqOddsPostprocessing

class aif360.algorithms.postprocessing.EqOddsPostprocessing(unprivileged_groups, privileged_groups, seed=None)[source]

Equalized odds postprocessing is a post-processing technique that solves a linear program to find probabilities with which to change output labels to optimize equalized odds [8] [9].

References

[8]M. Hardt, E. Price, and N. Srebro, “Equality of Opportunity in Supervised Learning,” Conference on Neural Information Processing Systems, 2016.
[9]G. Pleiss, M. Raghavan, F. Wu, J. Kleinberg, and K. Q. Weinberger, “On Fairness and Calibration,” Conference on Neural Information Processing Systems, 2017.
Parameters:
  • unprivileged_groups (list(dict)) – Representation for unprivileged group.
  • privileged_groups (list(dict)) – Representation for privileged group.
  • seed (int, optional) – Seed to make predict repeatable.

Methods

fit Compute parameters for equalizing odds using true and predicted labels.
fit_predict fit and predict methods sequentially.
fit_transform Train a model on the input and transform the dataset accordingly.
predict Perturb the predicted labels to obtain new labels that satisfy equalized odds constraints.
transform Return a new dataset generated by running this Transformer on the input.
__init__(unprivileged_groups, privileged_groups, seed=None)[source]
Parameters:
  • unprivileged_groups (list(dict)) – Representation for unprivileged group.
  • privileged_groups (list(dict)) – Representation for privileged group.
  • seed (int, optional) – Seed to make predict repeatable.
fit(dataset_true, dataset_pred)[source]

Compute parameters for equalizing odds using true and predicted labels.

Parameters:
Returns:

EqOddsPostprocessing – Returns self.
fit_predict(dataset_true, dataset_pred)[source]

fit and predict methods sequentially.

predict(dataset)[source]

Perturb the predicted labels to obtain new labels that satisfy equalized odds constraints.

Parameters:
  • dataset (BinaryLabelDataset) – Dataset containing labels that needs to be transformed.
  • dataset – Transformed dataset.