================
sklearn-crfsuite
================
.. image:: https://img.shields.io/pypi/v/sklearn-crfsuite.svg
:target: https://pypi.python.org/pypi/sklearn-crfsuite
:alt: PyPI Version
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:target: https://travis-ci.org/TeamHG-Memex/sklearn-crfsuite
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.. image:: https://codecov.io/github/TeamHG-Memex/sklearn-crfsuite/coverage.svg?branch=master
:target: https://codecov.io/github/TeamHG-Memex/sklearn-crfsuite?branch=master
:alt: Code Coverage
.. image:: https://readthedocs.org/projects/sklearn-crfsuite/badge/?version=latest
:target: https://sklearn-crfsuite.readthedocs.io/en/latest/?badge=latest
:alt: Documentation
sklearn-crfsuite is a thin CRFsuite_ (python-crfsuite_) wrapper which provides
interface simlar to scikit-learn_. ``sklearn_crfsuite.CRF`` is a scikit-learn
compatible estimator: you can use e.g. scikit-learn model
selection utilities (cross-validation, hyperparameter optimization) with it,
or save/load CRF models using joblib_.
.. _CRFsuite: http://www.chokkan.org/software/crfsuite/
.. _python-crfsuite: https://github.com/scrapinghub/python-crfsuite
.. _scikit-learn: http://scikit-learn.org/
.. _joblib: https://github.com/joblib/joblib
License is MIT.
Documentation can be found `here <https://sklearn-crfsuite.readthedocs.io>`_.
----
.. image:: https://hyperiongray.s3.amazonaws.com/define-hg.svg
:target: https://www.hyperiongray.com/?pk_campaign=github&pk_kwd=sklearn-crfsuite
:alt: define hyperiongray
Changes
=======
0.5.0 (2024-06-18)
------------------
* The ``CRF.predict()`` and ``CRF.predict_marginals()`` methods now return a
numpy array, as expected by newer versions of scikit-learn.
* Fixed the parameters of a call to the
``sklearn.metrics.classification_report()`` function from the
``flat_classification_report()`` function.
* ``sequence_accuracy_score`` now works with numpy arrays.
0.4.0 (2024-06-18)
------------------
* Dropped official support for Python 3.7 and lower, and added official support
for Python 3.8 and higher.
* Added support for scikit-learn 0.24.0 and higher.
* Increased minimum versions of dependencies as follows:
* python-crfsuite: 0.8.3 → 0.9.7
* scikit-learn: 0.24.0
* tabulate: 0.4.2
* Internal changes: enabled GitHub Actions for CI, added a tox environment for
minimum supported versions of dependencies, applied automatic code cleanups.
0.3.6 (2017-06-22)
------------------
* added ``sklearn_crfsuite.metrics.flat_recall_score``.
0.3.5 (2017-03-21)
------------------
* Properly close file descriptor in ``FileResource.cleanup``;
* declare Python 3.6 support, stop testing on Python 3.3.
0.3.4 (2016-11-17)
------------------
* Small formatting fixes.
0.3.3 (2016-03-15)
------------------
* scikit-learn dependency is now optional for sklearn_crfsuite;
it is required only when you use metrics and scorers;
* added ``metrics.flat_precision_score``.
0.3.2 (2015-12-18)
------------------
* Ignore more errors in ``FileResource.__del__``.
0.3.1 (2015-12-17)
------------------
* Ignore errors in ``FileResource.__del__``.
0.3 (2015-12-17)
----------------
* Added ``sklearn_crfsuite.metrics.sequence_accuracy_score()`` function and
related ``sklearn_crfsuite.scorers.sequence_accuracy``;
* ``FileResource.__del__`` method made more robust.
0.2 (2015-12-11)
----------------
* **backwards-incompatible**: ``crf.tagger`` attribute is renamed to
``crf.tagger_``; when model is not trained accessing this attribute
no longer raises an exception, its value is set to None instead.
* new CRF attributes available after training:
* ``classes_``
* ``size_``
* ``num_attributes_``
* ``attributes_``
* ``state_features_``
* ``transition_features_``
* Tutorial is added.
0.1 (2015-11-27)
----------------
Initial release.
Raw data
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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\n0.5.0 (2024-06-18)\n------------------\n\n* The ``CRF.predict()`` and ``CRF.predict_marginals()`` methods now return a\n numpy array, as expected by newer versions of scikit-learn.\n\n* Fixed the parameters of a call to the\n ``sklearn.metrics.classification_report()`` function from the\n ``flat_classification_report()`` function.\n\n* ``sequence_accuracy_score`` now works with numpy arrays.\n\n0.4.0 (2024-06-18)\n------------------\n\n* Dropped official support for Python 3.7 and lower, and added official support\n for Python 3.8 and higher.\n\n* Added support for scikit-learn 0.24.0 and higher.\n\n* Increased minimum versions of dependencies as follows:\n\n * python-crfsuite: 0.8.3 \u2192 0.9.7\n * scikit-learn: 0.24.0\n * tabulate: 0.4.2\n\n* Internal changes: enabled GitHub Actions for CI, added a tox environment for\n minimum supported versions of dependencies, applied automatic code cleanups.\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.\n",
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