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        "author": "supercoderhawk, Mikhail Korobov",
        "author_email": "supercoderhawk@gmail.com, kmike84@gmail.com",
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            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
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        "description": "================\nsklearn-crfsuite\n================\n\n.. image:: https://img.shields.io/pypi/v/sklearn-crfsuite.svg\n   :target: https://pypi.python.org/pypi/sklearn-crfsuite\n   :alt: PyPI Version\n\n.. image:: https://img.shields.io/travis/TeamHG-Memex/sklearn-crfsuite/master.svg\n   :target: https://travis-ci.org/TeamHG-Memex/sklearn-crfsuite\n   :alt: Build Status\n\n.. image:: https://codecov.io/github/TeamHG-Memex/sklearn-crfsuite/coverage.svg?branch=master\n   :target: https://codecov.io/github/TeamHG-Memex/sklearn-crfsuite?branch=master\n   :alt: Code Coverage\n\n.. image:: https://readthedocs.org/projects/sklearn-crfsuite/badge/?version=latest\n   :target: https://sklearn-crfsuite.readthedocs.io/en/latest/?badge=latest\n   :alt: Documentation\n\nsklearn-crfsuite is a thin CRFsuite_ (python-crfsuite_) wrapper which provides\ninterface simlar to scikit-learn_. ``sklearn_crfsuite.CRF`` is a scikit-learn\ncompatible estimator: you can use e.g. scikit-learn model\nselection utilities (cross-validation, hyperparameter optimization) with it,\nor save/load CRF models using joblib_.\n\n.. _CRFsuite: http://www.chokkan.org/software/crfsuite/\n.. _python-crfsuite: https://github.com/scrapinghub/python-crfsuite\n.. _scikit-learn: http://scikit-learn.org/\n.. _joblib: https://github.com/joblib/joblib\n\nLicense is MIT.\n\nDocumentation can be found `here <https://sklearn-crfsuite.readthedocs.io>`_.\n\n----\n\n.. image:: https://hyperiongray.s3.amazonaws.com/define-hg.svg\n\t:target: https://www.hyperiongray.com/?pk_campaign=github&pk_kwd=sklearn-crfsuite\n\t:alt: define hyperiongray\n\n\nChanges\n=======\n\n0.3.6 (2017-06-22)\n------------------\n\n* added ``sklearn_crfsuite.metrics.flat_recall_score``.\n\n0.3.5 (2017-03-21)\n------------------\n\n* Properly close file descriptor in ``FileResource.cleanup``;\n* declare Python 3.6 support, stop testing on Python 3.3.\n\n0.3.4 (2016-11-17)\n------------------\n\n* Small formatting fixes.\n\n0.3.3 (2016-03-15)\n------------------\n\n* scikit-learn dependency is now optional for sklearn_crfsuite;\n  it is required only when you use metrics and scorers;\n* added ``metrics.flat_precision_score``.\n\n0.3.2 (2015-12-18)\n------------------\n\n* Ignore more errors in ``FileResource.__del__``.\n\n0.3.1 (2015-12-17)\n------------------\n\n* Ignore errors in ``FileResource.__del__``.\n\n0.3 (2015-12-17)\n----------------\n\n* Added ``sklearn_crfsuite.metrics.sequence_accuracy_score()`` function and\n  related ``sklearn_crfsuite.scorers.sequence_accuracy``;\n* ``FileResource.__del__`` method made more robust.\n\n0.2 (2015-12-11)\n----------------\n\n* **backwards-incompatible**: ``crf.tagger`` attribute is renamed to\n  ``crf.tagger_``; when model is not trained accessing this attribute\n  no longer raises an exception, its value is set to None instead.\n\n* new CRF attributes available after training:\n\n    * ``classes_``\n    * ``size_``\n    * ``num_attributes_``\n    * ``attributes_``\n    * ``state_features_``\n    * ``transition_features_``\n\n* Tutorial is added.\n\n0.1 (2015-11-27)\n----------------\n\nInitial release.",
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        "name": "sklearn-pycrfsuite",
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