Extension of text_explainability for sensitivity testing (robustness, fairness)
Project description
Extension of text_explainability for sensitivity testing (robustness, fairness).
Marcel Robeer, 2021
Installation
Method | Instructions |
---|---|
pip |
Install from PyPI via pip3 install text_sensitivity . |
Local | Clone this repository and install via pip3 install -e . or locally run python3 setup.py install . |
Documentation
Full documentation of the latest version is provided at https://marcelrobeer.github.io/text_sensitivity/.
Example usage
See example_usage.md to see an example of how the package can be used, or run the lines in example_usage.py
to do explore it interactively.
Releases
text_explainability
is officially released through PyPI.
See CHANGELOG.md for a full overview of the changes for each version.
Citation
@misc{text_sensitivity,
title = {Python package text_sensitivity},
author = {Marcel Robeer and Elize Herrewijnen},
howpublished = {\url{https://git.science.uu.nl/m.j.robeer/text_sensitivity}},
year = {2021}
}
Maintenance
Contributors
- Marcel Robeer (
@m.j.robeer
) - Elize Herrewijnen (
@e.herrewijnen
)
Todo
Tasks yet to be done:
- Word-level perturbations
- Add fairness-specific metrics:
- Subgroup fairness
- Counterfactual fairness
- Add expected behavior
- Robustness: equal to prior prediction, or in some cases might expect that it deviates
- Fairness: may deviate from original prediction
- Tests
- Add tests for perturbations
- Add tests for sensitivity testing schemes
- Add visualization ability
Credits
- Edward Ma. NLP Augmentation. 2019.
- Daniele Faraglia and other contributors. Faker. 2012.
Project details
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