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Jurity: Fairness & Evaluation Library
======================================

Jurity is a research library that provides fairness metrics, recommender system evaluations, classification metrics and bias mitigation techniques. The library adheres to PEP-8 standards and is tested heavily.

Jurity is developed by the Artificial Intelligence Center of Excellence at Fidelity Investments.


Available Fairness Metrics
---------------------------------

* `Average Odds <https://fidelity.github.io/jurity/about_fairness.html#average-odds>`_
* `Disparate Impact <https://fidelity.github.io/jurity/about_fairness.html#disparate-impact>`_
* `Equal Opportunity <https://fidelity.github.io/jurity/about_fairness.html#equal-opportunity>`_
* `False Negative Rate Difference <https://fidelity.github.io/jurity/about_fairness.html#fnr-difference>`_
* `False Omission Rate Difference <https://fidelity.github.io/jurity/about_fairness.html#for-difference>`_
* `Generalized Entropy Index <https://fidelity.github.io/jurity/about_fairness.html#generalized-entropy-index>`_
* `Predictive Equality <https://fidelity.github.io/jurity/about_fairness.html#predictive-equality>`_
* `Statistical Parity <https://fidelity.github.io/jurity/about_fairness.html#statistical-parity>`_
* `Theil Index <https://fidelity.github.io/jurity/about_fairness.html#theil-index>`_

Available Bias Mitigation Techniques
-------------------------------------------

* `Equalized Odds <https://fidelity.github.io/jurity/about_fairness.html#equalized-odds>`_

Available Recommenders Metrics
-------------------------------------------

* `AUC: Area Under the Curve <https://fidelity.github.io/jurity/about_reco.html#auc-area-under-the-curve>`_
* `CTR: Click-through rate <https://fidelity.github.io/jurity/about_reco.html#ctr-click-through-rate>`_
* `Precision@K <https://fidelity.github.io/jurity/about_reco.html#precision>`_
* `Recall@K <https://fidelity.github.io/jurity/about_reco.html#recall>`_
* `MAP@K: Mean Average Precision <https://fidelity.github.io/jurity/about_reco.html#map-mean-average-precision>`_
* `NDCG: Normalized discounted cumulative gain <https://fidelity.github.io/jurity/about_reco.html#ndcg-normalized-discounted-cumulative-gain>`_
* `Inter-List Diversity <https://fidelity.github.io/jurity/about_reco.html#inter-list-diversity>`_
* `Intra-List Diversity <https://fidelity.github.io/jurity/about_reco.html#intra-list-diversity>`_

Available Classification Metrics
---------------------------------

* `Accuracy  <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.accuracy_score.html>`_
* `AUC <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.roc_auc_score.html#sklearn.metrics.roc_auc_score>`_
* `F1 Score <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.f1_score.html>`_
* `Precision <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.precision_score.html>`_
* `Recall <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.recall_score.html>`_


.. include:: quick.rst


Source Code
===========
The source code is hosted on :repo:`GitHub <>`.

.. sidebar:: Contents

	.. toctree::
	   :maxdepth: 2

	   quick
	   install
	   about_fairness
	   about_reco
	   api


Indices and tables
==================

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