Releases: ChEB-AI/python-chebai
Releases · ChEB-AI/python-chebai
v1.0.3
This release includes some minor fixes:
What's Changed
- fix import for XYBaseDataModule by @sfluegel05 in #107
- Upgrade pyproject backend by @aditya0by0 in #109
- fix handling of 0-label predictions by @sfluegel05 in #110
Full Changelog: v1.0.2...v1.0.3
v1.0.2
This release includes:
- Change from setup.pytopyproject.toml- we also took the opportunity to remove some imports that are no longer needed and move some rarely used imports to extras. This should speed up installation #99
- Separate test and validation split ratios (with updated default values: test set is now 10%, validation set 5% (compared to ~13% and ~2%)) #103
- Fixes: hyperparameters get saved corrects #97, trainer is now determinstic #101, minor fixes for ensemble #104
v1.0.1
This release includes:
- Support for using chebai-trained models in chebifier ensembles (e.g., via automatically calculating metrics on the validation set) #102
- Fixes and improvements related to the chebai-extensions in chebai-graph and chebai-proteins #96 #93 #91 #88
- Streamlining the load_processed_datafunction #92 #90
- Some minor fixes and improvements #84 #85
v1.0.0
Changes in the last months include:
- #80 Protein datasets have been moved to python-chebai-proteins
- #79 n_token_limitallows pruning dataset to predetermined length
- #74 model.out_dimdoes not have to be given as a command line parameter but is inferred from the dataset
- #69 / #71 The fuzzy loss from Flügel et al.: A fuzzy loss for ontology classification, NeSy 2024 has been added
- improved documentation, unittests and workflows