The metric-aware kernel-width choice for LIME

Barrera Vicent, Aurelio; Paluzo Hidalgo, Eduardo; Gutiérrez Naranjo, Miguel Ángel

Ponencia

dc.creator	Barrera Vicent, Aurelio	es
dc.creator	Paluzo Hidalgo, Eduardo	es
dc.creator	Gutiérrez Naranjo, Miguel Ángel	es
dc.date.accessioned	2024-04-23T09:58:40Z
dc.date.available	2024-04-23T09:58:40Z
dc.date.issued	2023
dc.identifier.citation	Barrera Vicent, A., Paluzo Hidalgo, E. y Gutiérrez Naranjo, M.Á. (2023). The metric-aware kernel-width choice for LIME. En 1st World Conference on eXplainable Artificial Intelligence: Late-Breaking Work, Demos and Doctoral Consortium, xAI-2023: LB-D-DC Lisbon 26 July 2023 through 28 July 2023 (117-122), Lisboa: CEUR-WS.
dc.identifier.issn	1613-0073	es
dc.identifier.uri	https://hdl.handle.net/11441/157016
dc.description.abstract	Local Interpretable Model-Agnostic Explanations (LIME) are a well-known approach to provide local interpretability to Machine Learning models. LIME uses an exponential smoothing kernel based on the kernel width value, which defines the width of the local neighbourhood. In this paper, we study the influence of the distances for these local explanations, and we explore the choice of kernel width to guarantee a fair performance comparison between the distances.	es
dc.format	application/pdf	es
dc.format.extent	5	es
dc.language.iso	eng	es
dc.publisher	CEUR-WS	es
dc.relation.ispartof	1st World Conference on eXplainable Artificial Intelligence: Late-Breaking Work, Demos and Doctoral Consortium, xAI-2023: LB-D-DC Lisbon 26 July 2023 through 28 July 2023 (2023), pp. 117-122.
dc.rights	Attribution-NonCommercial-NoDerivatives 4.0 Internacional	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/	*
dc.subject	Explainability	es
dc.subject	Kernel width	es
dc.subject	LIME	es
dc.subject	XAI	es
dc.title	The metric-aware kernel-width choice for LIME	es
dc.type	info:eu-repo/semantics/conferenceObject	es
dc.type.version	info:eu-repo/semantics/acceptedVersion	es
dc.rights.accessRights	info:eu-repo/semantics/openAccess	es
dc.contributor.affiliation	Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial	es
dc.publication.initialPage	117	es
dc.publication.endPage	122	es
dc.eventtitle	1st World Conference on eXplainable Artificial Intelligence: Late-Breaking Work, Demos and Doctoral Consortium, xAI-2023: LB-D-DC Lisbon 26 July 2023 through 28 July 2023	es
dc.eventinstitution	Lisboa	es

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