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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.