Release notes
=============

2.0.0 (2025-11-24)
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* Suspended support fro UARFF files
* Significant improvement of the backbone decision tree generation mechanism by moving away from object-oriented structure and focusing purely on Python-optimized structures (dicts)
* Parsing dataframe is up to 10 times faster  (usually more like 5x)
* Fitting model using SHAP values, but without oversampling is up to 4 times faster
* Oversampling alone is up 30 times faster
* Fixes in dependencies related to upgraded numpy and shap packages.

1.3.2 (2025-02-05)
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* Fixes in dependencies
* Fixes in numpy float representation of dataframes read from UARFF
* Added more examples to documentation

1.3.0 (2024-09-06)
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* Fixed catBoost problem and minor visualization bugs
* Fixed class balancing code
* Added labelling of phantom branches in the leaves
* Fixed bug with additional columns added when parity=='local'
* Improved SHAP-guided sampling
* Bugfixes in importance samplers
* Added medoid CF for categorical variables
* Fixed invalid requirements in build file
* gower replaced with gower-multiprocessing
* Fixed visualization issue when no instance nor counterfactual is passed.
* Fixed issue with categorical variables.
* Fixed with gower installed without multiprocessing
* Added balancing to BOTH sampling strategy, to overcome heavy imbalance generated by SHAP-sampler

1.2.0 (2024-04-30)
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* Fixes in SHAP guided sampler
* Fixed in export to HMR
* Added documentation section on visualization


1.1.0 (2024-03-08)
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* Changed modularization (internal, so it will not affect usage). Samplers were moved to separate module

1.0.3 (2024-03-01)
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* Fixes in tree visualization
* Improved documentation

1.0.1 (2024-02-23)
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* Added pypl installation
* Added sphinx documentation