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Releases: jlgarridol/sslearn

v1.0.5.2

27 May 08:03
fcad2af
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[1.0.5.2] - 2024-05-27

HotFix

  • Remove some files that are not necessary in the package.

v1.0.5.1

20 May 11:13
58ba5b7
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[1.0.5.1] - 2024-05-20

Fixed

  • Fixed bugs in artificial_ssl_dataset, now support again pandas DataFrame and y_unlabeled returns the right values

v1.0.5

08 May 15:24
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[1.0.5] - 2024-05-08

Added

  • feature_fusion and probability_fusion methods for restricted in sslearn.restricted module.

Fixed

  • CoForest random integer is now compatible with Windows.

v1.0.4.1

06 Feb 12:43
a3d86de
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[1.0.4.1] - 2024-02-06

Fix a problem with pypi

Added

  • Add a parameter to artificial_ssl_dataset to force a minimum of instances. Issue #11
  • Add a parameter to artificial_ssl_dataset to return indexes. Issue #13

Changed

  • The artificial_ssl_dataset changed the process to generate the dataset, based in indexes. Issue #13

Fixed

  • DeTriTraining now is vectorized and is faster than before.

v1.0.4

06 Feb 11:10
c62fe64
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[1.0.4] - 2024-01-31

Added

  • Add a parameter to artificial_ssl_dataset to force a minimum of instances. Issue #11
  • Add a parameter to artificial_ssl_dataset to return indexes. Issue #13

Changed

  • The artificial_ssl_dataset changed the process to generate the dataset, based in indexes. Issue #13

Fixed

  • DeTriTraining now is vectorized and is faster than before.

v1.0.3.1

29 Mar 10:55
8cb356e
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[1.0.3.1] - 2023-03-29

Added

  • Methods now support no unlabeled data. In this case, the method will return the same as the base estimator.

Changed

  • In OneHotEncoder, the sparse parameter is now sparse_output to avoid a FutureWarning.

Fixed

  • CoForest now is most similar to the original paper.
  • TriTraining can use at least 3 n_jobs. Fixed the bug that allows using as many n_jobs as cpus in the machine.

v1.0.3

29 Mar 10:51
21b3d2c
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[1.0.3] - 2023-03-29

Added

  • Methods now support no unlabeled data. In this case, the method will return the same as the base estimator.

Changed

  • In OneHotEncoder, the sparse parameter is now sparse_output to avoid a FutureWarning.

Fixed

  • CoForest now is most similar to the original paper.
  • TriTraining can use at least 3 n_jobs. Fixed the bug that allows using as many n_jobs as cpus in the machine.

v1.0.2

17 Feb 13:52
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Change Log

[1.0.2] - 2023-02-17

Fixed

  • Fixed a bug in TriTraining when one of the base estimators has not a random_state parameter.
  • Fixed OneVsRestSSL with the random_state parameter.
  • Fixed WiWTriTraining when no instance_group parameter is not provided.
  • Fixed a FutureWarning for sparse parameter in OneHotEncoder. Changed to sparse_output.

Zenodo Indexed

24 Jan 12:01
86071ad
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1.0.1

Update python-package.yml

v1.0.0

05 Dec 13:38
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First public version of sslearn