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Merge branch 'dev' of https://github.com/maks-sh/scikit-uplift into dev
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MANIFEST.in

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include *.rst
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recursive-include sklift/datasets/ *.rst
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include MANIFEST.in

Readme.rst

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.. _PyPi: https://badge.fury.io/py/scikit-uplift
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.. |Docs| image:: https://readthedocs.org/projects/scikit-uplift/badge/?version=latest
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.. _Docs: https://scikit-uplift.readthedocs.io/en/latest/
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.. _Docs: https://www.uplift-modeling.com/en/latest/
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.. |License| image:: https://img.shields.io/badge/license-MIT-green
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.. _License: https://github.com/maks-sh/scikit-uplift/blob/master/LICENSE
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.. |Open In Colab4| image:: https://colab.research.google.com/assets/colab-badge.svg
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.. _Open In Colab4: https://colab.research.google.com/github/maks-sh/scikit-uplift/blob/master/notebooks/pipeline_usage_RU.ipynb
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.. _scikit-uplift.readthedocs.io: https://scikit-uplift.readthedocs.io/en/latest/
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.. _uplift-modeling.com: https://www.uplift-modeling.com/en/latest/
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.. image:: https://raw.githubusercontent.com/maks-sh/scikit-uplift/dev/docs/_static/sklift-github-logo.png
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:align: center
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* Select a tiny group of customers in the campaign where a price per customer is high.
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Read more about uplift modeling problem in `User Guide <https://scikit-uplift.readthedocs.io/en/latest/user_guide/index.html>`__,
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Read more about uplift modeling problem in `User Guide <https://www.uplift-modeling.com/en/latest/user_guide/index.html>`__.
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Articles in russian on habr.com: `Part 1 <https://habr.com/ru/company/ru_mts/blog/485980/>`__
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and `Part 2 <https://habr.com/ru/company/ru_mts/blog/485976/>`__.
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Documentation
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--------------
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The full documentation is available at `scikit-uplift.readthedocs.io`_.
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The full documentation is available at `uplift-modeling.com`_.
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Or you can build the documentation locally using `Sphinx <http://sphinx-doc.org/>`_ 1.4 or later:
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We welcome new contributors of all experience levels.
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- Please see our `Contributing Guide <https://scikit-uplift.readthedocs.io/en/latest/contributing.html>`_ for more details.
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- Please see our `Contributing Guide <https://www.uplift-modeling.com/en/latest/contributing.html>`_ for more details.
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- By participating in this project, you agree to abide by its `Code of Conduct <https://github.com/maks-sh/scikit-uplift/blob/master/.github/CODE_OF_CONDUCT.md>`__.
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If you have any questions, please contact us at [email protected]
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Contributing
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~~~~~~~~~~~~~~~
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:alt: Top contributor 1
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:alt: Legend
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Important links
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~~~~~~~~~~~~~~~
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- Official source code repo: https://github.com/maks-sh/scikit-uplift/
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- Issue tracker: https://github.com/maks-sh/scikit-uplift/issues
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- Documentation: https://scikit-uplift.readthedocs.io/en/latest/
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- User Guide: https://scikit-uplift.readthedocs.io/en/latest/user_guide/index.html
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- Contributing guide: https://scikit-uplift.readthedocs.io/en/latest/contributing.html
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- Release History: https://scikit-uplift.readthedocs.io/en/latest/changelog.html
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- Documentation: https://www.uplift-modeling.com/en/latest/
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- User Guide: https://www.uplift-modeling.com/en/latest/user_guide/index.html
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- Contributing guide: https://www.uplift-modeling.com/en/latest/contributing.html
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- Release History: https://www.uplift-modeling.com/en/latest/changelog.html
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===============
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docs/index.rst

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* Select a tiny group of customers in the campaign where a price per customer is high.
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Read more about *uplift modeling* problem in `User Guide <https://scikit-uplift.readthedocs.io/en/latest/user_guide/index.html>`__,
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Read more about *uplift modeling* problem in `User Guide <https://www.uplift-modeling.com/en/latest/user_guide/index.html>`__,
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Articles in russian on habr.com: `Part 1 <https://habr.com/ru/company/ru_mts/blog/485980/>`__
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and `Part 2 <https://habr.com/ru/company/ru_mts/blog/485976/>`__.
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If you have any questions, please contact us at [email protected]
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docs/quick_start.rst

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Train and predict your uplift model
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Use the intuitive python API to train uplift models.
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Use the intuitive python API to train uplift models with `sklift.models <https://www.uplift-modeling.com/en/latest/api/models/index.html>`__.
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Evaluate your uplift model
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===========================
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Uplift model evaluation metrics are available in `sklift.metrics <https://www.uplift-modeling.com/en/latest/api/metrics/index.html>`__.
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Visualize performance metrics with `sklift.viz <https://www.uplift-modeling.com/en/latest/api/viz/index.html>`__.
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setup.py

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include_package_data=True,
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install_requires=REQUIRED,
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extras_require=EXTRAS,
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classifiers=[

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