Releases: jlgarridol/sslearn
Releases · jlgarridol/sslearn
1.0.5.3
v1.0.5.2
[1.0.5.2] - 2024-05-27
HotFix
- Remove some files that are not necessary in the package.
v1.0.5.1
[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
[1.0.5] - 2024-05-08
Added
feature_fusion
andprobability_fusion
methods for restricted insslearn.restricted
module.
Fixed
- CoForest random integer is now compatible with Windows.
v1.0.4.1
[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
[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
[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 nowsparse_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
[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 nowsparse_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
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 inOneHotEncoder
. Changed tosparse_output
.
Zenodo Indexed
1.0.1 Update python-package.yml