{
    "info": {
        "author": "Shlomi Hod",
        "author_email": "shlomi.hod@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Natural Language :: English",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Programming Language :: Python :: 3 :: Only",
            "Topic :: Scientific/Engineering :: Artificial Intelligence",
            "Topic :: Text Processing :: Linguistic"
        ],
        "description": "Responsibly\n===========\n\n.. image:: https://img.shields.io/badge/docs-passing-brightgreen.svg\n    :target: https://docs.responsibly.ai\n\n.. image:: https://img.shields.io/gitter/room/nwjs/nw.js.svg\n   :alt: Join the chat at https://gitter.im/ResponsiblyAI/responsibly\n   :target: https://gitter.im/ResponsiblyAI/responsibly\n\n.. image:: https://img.shields.io/travis/ResponsiblyAI/responsibly/master.svg\n    :target: https://travis-ci.org/ResponsiblyAI/responsibly\n\n.. image::  https://img.shields.io/coveralls/ResponsiblyAI/responsibly/master.svg\n   :target: https://coveralls.io/r/ResponsiblyAI/responsibly\n\n.. image::  https://img.shields.io/scrutinizer/g/ResponsiblyAI/responsibly.svg\n  :target: https://scrutinizer-ci.com/g/ResponsiblyAI/responsibly/?branch=master\n\n.. image::  https://img.shields.io/pypi/v/responsibly.svg\n  :target: https://pypi.org/project/responsibly\n\n.. image::  https://img.shields.io/github/license/ResponsiblyAI/responsibly.svg\n    :target: https://docs.responsibly.ai/about/license.html\n\n**Toolkit for Auditing and Mitigating Bias and Fairness**\n**of Machine Learning Systems \ud83d\udd0e\ud83e\udd16\ud83e\uddf0**\n\n*Responsibly* is developed for **practitioners** and **researchers** in mind,\nbut also for learners. Therefore, it is compatible with\ndata science and machine learning tools of trade in Python,\nsuch as Numpy, Pandas, and especially **scikit-learn**.\n\nThe primary goal is to be one-shop-stop for **auditing** bias\nand fairness of machine learning systems, and the secondary one\nis to mitigate bias and adjust fairness through\n**algorithmic interventions**.\nBesides, there is a particular focus on **NLP** models.\n\n*Responsibly* consists of three sub-packages:\n\n1. ``responsibly.dataset``\n     Collection of common benchmark datasets from fairness research.\n\n2. ``responsibly.fairness``\n     Demographic fairness in binary classification,\n     including metrics and algorithmic interventions.\n\n3. ``responsibly.we``\n     Metrics and debiasing methods for bias (such as gender and race)\n     in word embedding.\n\nFor fairness, *Responsibly*'s functionality is aligned with the book\n`Fairness and Machine Learning\n- Limitations and Opportunities <https://fairmlbook.org>`_\nby Solon Barocas, Moritz Hardt and Arvind Narayanan.\n\nIf you would like to ask for a feature or report a bug,\nplease open a\n`new issue <https://github.com/ResponsiblyAI/responsibly/issues/new>`_\nor write us in `Gitter <https://gitter.im/ResponsiblyAI/responsibly>`_.\n\nRequirements\n------------\n\n-  Python 3.5+\n\nInstallation\n------------\n\nInstall responsibly with pip:\n\n.. code:: sh\n\n   $ pip install responsibly\n\nor directly from the source code:\n\n.. code:: sh\n\n   $ git clone https://github.com/ResponsiblyAI/responsibly.git\n   $ cd responsibly\n   $ python setup.py install\n\nCitation\n--------\n\nIf you have used *Responsibly* in a scientific publication,\nwe would appreciate citations to the following:\n\n::\n\n  @Misc{,\n    author = {Shlomi Hod},\n    title =  {{Responsibly}: Toolkit for Auditing and Mitigating Bias and Fairness of Machine Learning Systems},\n    year =   {2018--},\n    url =    \"http://docs.responsibly.ai/\",\n    note =   {[Online; accessed <today>]}\n  }\n\nRevision History\n================\n\n0.1.1 (2019/08/04)\n------------------\n\n- Fix a dependencies issue with ``smart_open``\n\n- Change URLs to https\n\n0.1.0 (2019/07/31)\n------------------\n\n- Rename the project to ``responsibly`` from ``ethically``\n\n- Word embedding bias\n\n  - Improve functionality of ``BiasWordEmbedding``\n\n- Threshold fairness interventions\n\n  - Fix bugs with ROCs handling\n  - Improve API and add functionality (``plot_thresholds``)\n\n0.0.5 (2019/06/14)\n------------------\n\n- Word embedding bias\n\n  - Fix bug in computing WEAT\n\n  - Computing and plotting factual property\n    association to projections on a bias direction,\n    similar to WEFAT\n\n\n0.0.4 (2019/06/03)\n------------------\n\n- Word embedding bias\n\n  - Unrestricted ``most_similar``\n\n  - Unrestricted ``generate_analogies``\n\n  - Running specific experiments with ``calc_all_weat``\n\n  - Plotting clustering by classification\n    of biased neutral words\n\n\n0.0.3 (2019/04/10)\n------------------\n\n- Fairness in Classification\n\n  - Three demographic fairness criteria\n\n    - Independence\n    - Separation\n    - Sufficiency\n\n  - Equalized odds post-processing algorithmic interventions\n  - Complete two notebook demos (FICO and COMPAS)\n\n- Word embedding bias\n\n  - Measuring bias with WEAT method\n\n- Documentation improvements\n\n- Fixing security issues with dependencies\n\n\n0.0.2 (2018/09/01)\n------------------\n\n- Word embedding bias\n\n  - Generating analogies along the bias direction\n  - Standard evaluations of word embedding (word pairs and analogies)\n  - Plotting indirect bias\n  - Scatter plot of bias direction projections between two word embedding\n  - Improved verbose mode\n\n\n0.0.1 (2018/08/17)\n------------------\n\n-  Gender debiasing for word embedding based on Bolukbasi et al.\n\n\n",
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