CRFsuite (python-crfsuite) wrapper which provides interface simlar to scikit-learn
Project description
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.
License is MIT.
Documentation can be found here.
Changes
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.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file sklearn-crfsuite-0.3.2.tar.gz.
File metadata
- Download URL: sklearn-crfsuite-0.3.2.tar.gz
- Upload date:
- Size: 24.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | ad36bb063b10b7558d08368c76e95faad316ade19eda49f7aba9b3d77cd73426 |
|
| MD5 | f8dc0127464ebcd1301a925548e818a7 |
|
| BLAKE2b-256 | fd7d97e374715d0f4f963e43a4bb1523d7bd605b88a31ee36ad71749c27bd298 |
File details
Details for the file sklearn_crfsuite-0.3.2-py2.py3-none-any.whl.
File metadata
- Download URL: sklearn_crfsuite-0.3.2-py2.py3-none-any.whl
- Upload date:
- Size: 12.2 kB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 5e088e9850bc2de891a051140cb39dd872324ae9047de0bebd7a57f82c71172b |
|
| MD5 | cfc0f43eb1a05e24821c1aafff9f47c9 |
|
| BLAKE2b-256 | d34cbfd49137bd6050a70e43069fc98c4fc0333101c701fba4c3c6f93d9589e4 |
