REFRESH: Responsible and Efficient Feature Reselection guided by SHAP values

Author:

Sharma Shubham1ORCID,Dutta Sanghamitra2ORCID,Albini Emanuele1ORCID,Lecue Freddy1ORCID,Magazzeni Daniele1ORCID,Veloso Manuela1ORCID

Affiliation:

1. JPMorgan Chase & Co., USA

2. University of Maryland, College Park, USA

Publisher

ACM

Reference54 articles.

1. Explaining individual predictions when features are dependent: More accurate approximations to Shapley values

2. Interpretable Machine Learning in Healthcare

3. Alexander Babuta Marion Oswald and Christine Rinik. 2018. Machine learning algorithms and police decision-making: legal ethical and regulatory challenges. (2018). Alexander Babuta Marion Oswald and Christine Rinik. 2018. Machine learning algorithms and police decision-making: legal ethical and regulatory challenges. (2018).

4. Michiel  A Bakker , Alejandro Noriega-Campero , Duy Patrick Tu , Prasanna Sattigeri , Kush  R Varshney , and AS Pentland . 2019 . On fairness in budget-constrained decision making . In KDD Workshop of Explainable Artificial Intelligence. Michiel A Bakker, Alejandro Noriega-Campero, Duy Patrick Tu, Prasanna Sattigeri, Kush R Varshney, and AS Pentland. 2019. On fairness in budget-constrained decision making. In KDD Workshop of Explainable Artificial Intelligence.

5. Tom Begley , Tobias Schwedes , Christopher Frye , and Ilya Feige . 2020. Explainability for fair machine learning. arXiv preprint arXiv:2010.07389 ( 2020 ). Tom Begley, Tobias Schwedes, Christopher Frye, and Ilya Feige. 2020. Explainability for fair machine learning. arXiv preprint arXiv:2010.07389 (2020).

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