Releases: interpretml/DiCE
Releases · interpretml/DiCE
v0.12: Xgboost interface and Python 3.12 support
What's Changed
- Xgboost interface by @lldartsll in #452
- Bug fixes and more robust tests
- Enable test case
test_columns_out_of_order
and other code changes by @gaugup - Add newer python versions to builds by @gaugup in #449
New Contributors
- @lldartsll made their first contribution in #452
- @BogdanTurbal made their first contribution in #450
- @asendotsinski made their first contribution in #415
- @CloseChoice made their first contribution in #455
A big thank you to all the contributors!
Full Changelog: v0.11...v0.12
v0.11: Bug fixes and better support for non-numeric classes
- Ensure same type for CF output and input features
- Return original class instead of encoded class in CFs
- Better error checking for input query instance
- Dynamic creation of datasets for testing
- Approximate equality checking for float values in dataframe
- Other bug fixes
Thank you @gaugup, @bdavj, @DanieleMorotti for your contributions.
v0.10: Bug fixes and Python 3.11 support
- Support for python 3.11
- Update to requirements and tests
- Updated adult dataset download logic
- Misc. bug fixes
v0.9: Unified API for deep learning and sklearn models
- [Major refactor] Unified API for deep learning and sklearn models
- Support for generating CFs without training data (private data mode) for sklearn models
- Bug fixes and implementing iteration limits for search on CFs
New Contributors
- @lange-martin made their first contribution in #304
- @bgalvao made their first contribution in #313
- @daikikatsuragawa made their first contribution in #311
Full Changelog: v0.8...v0.9
v0.8: More configurable parameters for generating counterfactuals and better input checking
- Better error checking for user input parameters
- Improved error messages for feature importance functions
- Bug fixes for dimension mismatch with categorical variables
- Add capability to serialize and de-serialize dice-ml explainers
- Add more configurable parameters to generate_counterfactuals function
- Increased test coverage
- Replaced boston housing with california housing dataset
- Tests and support for Python 3.10, removed test support for 3.6
Contributors: @gaugup, @amit-sharma
Version bump 0.7.2 (Minor bug fixes)
The release contains the following:-
- Fix for logging
- Fix indentation in schema files
- Add documentation to save generated counterfactuals to disk
Minor version update: Better input checks
- Better input checks and minor bug fixes
Bug fixes and improvements to data interfaces and input validation
- Bug fixes for feature importance calculation and data interfaces
- Example notebooks: Use test data always to generate counterfactuals
- Updates to the genetic algorithm and KD-tree algorithm
- Better input validation and informative error messages for Dice explainers
- Improved test coverage
A big thank you to @gaugup and @soundarya98 for their contributions.
Minor version update: Fixed CF schema and better tests
- Added init so schema are packaged with distribution
- All flake8 lint errors fixed. Flake8 validation is now enabled on all new commits.
- Better automation for tests
Thank you @gaugup and @gregorybchris for your contributions!
Optimized methods and updated schema for counterfactuals
- Better exception handling for invalid user inputs (e.g., total_CFs=0)
- Updated schema for serializing counterfactual explanations object
- Better description for DiCE in getting started notebook
- Add progress bar for counterfactual computation
- Optimizations for genetic and random methods
- Better test coverage
Thank you @gaugup and @soundarya88 for your contributions!