lucasmaystre / choix

Inference algorithms for models based on Luce's choice axiom
MIT License
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machine-learning python ranking

choix

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choix is a Python library that provides inference algorithms for models based on Luce's choice axiom. These probabilistic models can be used to explain and predict outcomes of comparisons between items.

choix makes it easy to infer model parameters from these different types of data, using a variety of algorithms:

Getting started

To install the latest release directly from PyPI, simply type::

pip install choix

To get started, you might want to explore one of these notebooks:

You can also find more information on the official documentation <http://choix.lum.li/en/latest/>. In particular, the API reference <http://choix.lum.li/en/latest/api.html> contains a good summary of the library's features.

References

.. _Generalized Method-of-Moments for Rank Aggregation: https://papers.nips.cc/paper/4997-generalized-method-of-moments-for-rank-aggregation.pdf

.. _Efficient Bayesian Inference for Generalized Bradley-Terry models: https://hal.inria.fr/inria-00533638/document

.. _Extensions of Gaussian processes for ranking\: semi-supervised and active learning: http://www.gatsby.ucl.ac.uk/~chuwei/paper/gprl.pdf

.. _MM algorithms for generalized Bradley-Terry models: http://sites.stat.psu.edu/~dhunter/papers/bt.pdf

.. _Inverting a Steady-State: http://theory.stanford.edu/~sergei/papers/wsdm15-cset.pdf

.. _Fast and Accurate Inference of Plackett-Luce Models: https://infoscience.epfl.ch/record/213486/files/fastinference.pdf

.. _ChoiceRank\: Identifying Preferences from Node Traffic in Networks: https://infoscience.epfl.ch/record/229164/files/choicerank.pdf

.. _Iterative Ranking from Pair-wise Comparison: https://papers.nips.cc/paper/4701-iterative-ranking-from-pair-wise-comparisons.pdf

.. |build-status| image:: https://api.travis-ci.com/lucasmaystre/choix.svg?branch=master :alt: build status :scale: 100% :target: https://app.travis-ci.com/github/lucasmaystre/choix

.. |coverage| image:: https://codecov.io/gh/lucasmaystre/choix/branch/master/graph/badge.svg :alt: code coverage :scale: 100% :target: https://codecov.io/gh/lucasmaystre/choix

.. |docs| image:: https://readthedocs.org/projects/choix/badge/?version=latest :alt: documentation status :scale: 100% :target: http://choix.lum.li/en/latest/?badge=latest