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README.rst

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.. -*- mode: rst -*-
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|GitHubActions|_ |Codecov|_ |ReadTheDocs|_ |License|_ |PythonVersion|_ |PyPi|_ |Conda|_ |Release|_ |Commits|_ |DOI|_
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|GitHubActions| |Codecov| |ReadTheDocs| |License| |PythonVersion| |PyPi| |Conda| |Release| |Commits| |DOI|
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.. |GitHubActions| image:: https://github.com/scikit-learn-contrib/MAPIE/actions/workflows/test.yml/badge.svg
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.. _GitHubActions: https://github.com/scikit-learn-contrib/MAPIE/actions
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.. |Codecov| image:: https://codecov.io/gh/scikit-learn-contrib/MAPIE/branch/master/graph/badge.svg?token=F2S6KYH4V1
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.. _Codecov: https://codecov.io/gh/scikit-learn-contrib/MAPIE
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.. |ReadTheDocs| image:: https://readthedocs.org/projects/mapie/badge
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.. _ReadTheDocs: https://mapie.readthedocs.io/en/latest
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:alt: Documentation Status
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.. |License| image:: https://img.shields.io/github/license/simai-ml/MAPIE
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.. _License: https://github.com/scikit-learn-contrib/MAPIE/blob/master/LICENSE
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.. _Conda: https://anaconda.org/conda-forge/mapie
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.. |Release| image:: https://img.shields.io/github/v/release/scikit-learn-contrib/mapie
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.. _Release: https://github.com/scikit-learn-contrib/MAPIE/releases
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.. |DOI| image:: https://img.shields.io/badge/10.48550/arXiv.2207.12274-B31B1B.svg
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.. _DOI: https://arxiv.org/abs/2207.12274
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.. image:: https://github.com/simai-ml/MAPIE/raw/master/doc/images/mapie_logo_nobg_cut.png
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MAPIE has been developed through a collaboration between Quantmetry, Michelin, ENS Paris-Saclay,
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and with the financial support from Région Ile de France and Confiance.ai.
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|Quantmetry|_ |Michelin|_ |ENS|_ |Confiance.ai|_ |IledeFrance|_
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.. |ENS| image:: https://file.diplomeo-static.com/file/00/00/01/34/13434.svg
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.. _ENS: https://ens-paris-saclay.fr/en
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.. |Confiance.ai| image:: https://pbs.twimg.com/profile_images/1443838558549258264/EvWlv1Vq_400x400.jpg
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.. _Confiance.ai: https://www.confiance.ai/
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.. _IledeFrance: https://www.iledefrance.fr/
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🔍 References

doc/theoretical_description_binary_classification.rst

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These 3 notions are tightly related for score-based classifier, as it is shown in [1].
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Prediction sets can be computed in the same way for multiclass and binary classification with
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:class:`~mapie.calibration.MapieClassifier`, and there are the same theoretical guarantees.
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:class:`~mapie.classification.MapieClassifier`, and there are the same theoretical guarantees.
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Nevertheless, prediction sets are often much less informative in the binary case than in the multiclass case.
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From Gupta et al [1]:

setup.py

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"Programming Language :: Python :: 3.7",
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"Programming Language :: Python :: 3.8",
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"Programming Language :: Python :: 3.9",
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"Programming Language :: Python :: 3.10"
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"Programming Language :: Python :: 3.10",
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"Programming Language :: Python :: 3.11"
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]
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setup(

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