The coming of age of interpretable and explainable machine learning models
Visualitza/Obre
10.14428/esann/2021.ES2021-2
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/368022
Tipus de documentText en actes de congrés
Data publicació2021
EditorI6doc.com
Condicions d'accésAccés obert
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Abstract
Machine learning-based systems are now part of a wide array of real-world applications seamlessly embedded in the social realm. In the wake of this realisation, strict legal regulations for these systems are currently being developed, addressing some of the risks they may pose. This is the coming of age of the interpretability and explainability problems in machine learning-based data analysis, which can no longer be seen just as an academic research problem. In this tutorial, associated to ESANN 2021 special session on “Interpretable Models in Machine Learning and Explainable Artificial Intelligence”, we discuss explainable and interpretable machine learning as post-hoc and ante-hoc strategies to address these problems and highlight several aspects related to them, including their assessment. The contributions accepted for the session are then presented in this context
CitacióLisboa, P. [et al.]. The coming of age of interpretable and explainable machine learning models. A: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. "29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning: ESANN 2021: online event, October 6-7-8, 2021: proceedings". I6doc.com, 2021, p. 547-556. DOI 10.14428/esann/2021.ES2021-2.
Versió de l'editorhttps://www.esann.org/sites/default/files/proceedings/2021/ES2021-2.pdf
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