text-sensitivity 0.1.8

Extension of text_explainability for sensitivity testing (robustness, fairness)

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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.