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Welcome to error-parity's documentation!
========================================

The :code:`error-parity` package allows you to easily achieve error-rate 
fairness between societal groups.
It's compatible with any score-based predictor, and can map out all of its 
attainable fairness-accuracy trade-offs.

Full code available on the `GitHub repository`_, 
including various `jupyter notebook examples`_ .

Check out the following sub-pages:

.. toctree::
   :maxdepth: 1

   Readme file <readme>
   API reference <modules>
   Example notebooks <notebooks>


Citing
------

The :code:`error-parity` package is the basis for the following `publication`_:

.. code-block:: bib

   @inproceedings{
   cruz2024unprocessing,
   title={Unprocessing Seven Years of Algorithmic Fairness},
   author={Andr{\'e} Cruz and Moritz Hardt},
   booktitle={The Twelfth International Conference on Learning Representations},
   year={2024},
   url={https://openreview.net/forum?id=jr03SfWsBS}
   }

All additional supplementary materials are available on the `supp-materials`_ branch of the `GitHub repository`_.


Indices
=======

* :ref:`genindex`
* :ref:`modindex`


.. _GitHub repository: https://github.com/socialfoundations/error-parity
.. _jupyter notebook examples: https://github.com/socialfoundations/error-parity/tree/main/examples
.. _publication: https://arxiv.org/abs/2306.07261
.. _supp-materials: https://github.com/socialfoundations/error-parity/tree/supp-materials