Multicriteria Model-Agnostic Counterfactual Explainability for Classifiers-Reference-Cited by-同舟云学术

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Multicriteria Model-Agnostic Counterfactual Explainability for Classifiers

Published:2024-06-30 Issue: Volume:31 Page:1-8
ISSN:
Container-title:2024 International Joint Conference on Neural Networks (IJCNN)
language:
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Author:

Zufiria Pedro J.¹,Fernández-Sánchez-Pascuala Ignacio²,Rojas Cristian R.³

Affiliation:

1. Universidad Politécnica de Madrid,Dep. Matemática Aplicada a las TIC Inform. Proc. and Telec. Center (IPTC) ETSI Telecomunicación,Madrid,Spain

2. Universidad Politécnica de Madrid,Dep. Matemática Aplicada a las TIC ETSI Telecomunicación,Madrid,Spain

3. KTH Royal Institute of Technology,Division of Decision and Control Systems,Stockholm,Sweden

Funder

Ministerio de Ciencia e Innovación

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10649807/10649898/10651525.pdf?arnumber=10651525

Reference20 articles.

1. Counterfactual explanations without opening the black box: Automated decisions and the GDPR;Wachter;Harv. JL & Tech.,2018

2. Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)

3. Machine Learning Interpretability: A Survey on Methods and Metrics

4. Solving the Black Box Problem: A Normative Framework for Explainable Artificial Intelligence

5. Model-agnostic interpretability of machine learning;Ribeiro,2016

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