Interpretability of Machine Learning Models

Author:

Czerwinska Urszula

Publisher

Springer International Publishing

Reference57 articles.

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3. Adler, P., Falk, C., Friedler, S. A., Rybeck, G., Scheidegger, C., Smith, B., & Venkatasubramanian, S. (2016a). Auditing black-box models for indirect influenc.

4. Adler, P., Falk, C., Friedler, S. A., Rybeck, G., Scheidegger, C., Smith, B., & Venkatasubramanian, S. (2016b). GitHub - algofairness/BlackBoxAuditing: Research code for auditing and exploring black box machine-learning models. Retrieved January 13, 2021, from Github website.: https://github.com/algofairness/BlackBoxAuditing

5. Agarwal, A., Beygelzimer, A., Dudík, M., Langford, J., & Wallach, H. M. (2018). A reductions approach to fair classification. CoRR, abs/1803.0. Retrieved from http://arxiv.org/abs/1803.02453

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