Explaining black-box classifiers: Properties and functions-Reference-Cited by-同舟云学术

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Explaining black-box classifiers: Properties and functions

Published:2023-04 Issue: Volume:155 Page:40-65
ISSN:0888-613X
Container-title:International Journal of Approximate Reasoning
language:en
Short-container-title:International Journal of Approximate Reasoning

Author:

Amgoud Leila

Publisher

Elsevier BV

Subject

Applied Mathematics,Artificial Intelligence,Theoretical Computer Science,Software

Reference63 articles.

1. Explanation and justification in machine learning: a survey;Biran,2017

2. A survey of methods for explaining black box models;Guidotti;ACM Comput. Surv.,2019

3. Explanation in artificial intelligence: insights from the social sciences;Miller;Artif. Intell.,2019

4. Interpretable Machine Learning;Molnar,2020

5. A survey on the explainability of supervised machine learning;Burkart;J. Artif. Intell. Res.,2021

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. On the failings of Shapley values for explainability;International Journal of Approximate Reasoning;2024-08

2. Explainable Ensemble Machine Learning for Wheat Grain Identification;2023 IEEE International Conference on Data Mining Workshops (ICDMW);2023-12-04

3. A New Class of Explanations for Classifiers with Non-binary Features;Logics in Artificial Intelligence;2023

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