This repo is based on Benchmark Evaluation of Counterfactual Algorithms for XAI: From a White box to a Black box. All notable changes to this project will be documented in this file.
0.2.0 - 2022-12-20
- Add a notebook for model training
1_AE_model_training.ipynb
- Add new attack methods (DeepFool, Carlini, LowProFool, Boundary, Ho)
- Add
requirements.txt
to projects - Add three new models (Linear SVC, Logistic Regression and Neural network 2) to
utils/models.py
- Add AE trained models to
./saved_models/
- Add original and generated datapoints to folder
./datapoints/
- Add information about Adversarial Robustness Toolbox in
art.md
- Add simplified model for test
- Update
README
andCHANGELOG
- Move output processing function to
save.py
- Remove irrelevant materials from CF
0.1.0 - 2022-11-30
- Fork Counterfactual Benchmark as the basis for further development
- Add
CHANGELOG.md
to record evolving changes in the development
- Add more patterns in
.gitignore
- Remove cache folders (
.vscode/
,.ipynb_checkpoints/
,__pycache__/
) out of git track lists