teex: a toolbox for the evaluation of explanations

We present teex, a Python toolbox for the evaluation of explanations. teex focuses on the evaluation of local explanations of the predictions of machine learning models by comparing them to ground-truth explanations. It supports several types of explanations: feature importance vectors, saliency map...

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Detalles Bibliográficos
Autores: Antoñanzas Acero, Jesús Maria, Jia, Yunzhe, Frank, Eibe, Bifet Figuerol, Albert Carles, Pfahringer, Bernhard
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/396241
Acceso en línea:https://hdl.handle.net/2117/396241
https://dx.doi.org/10.1016/j.neucom.2023.126642
Access Level:acceso abierto
Palabra clave:Python (Computer program language)
Explainable AI
Explanation evaluation
Python
Python (Llenguatge de programació)
Àrees temàtiques de la UPC::Informàtica::Llenguatges de programació::Python
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spelling teex: a toolbox for the evaluation of explanationsAntoñanzas Acero, Jesús MariaJia, YunzheFrank, EibeBifet Figuerol, Albert CarlesPfahringer, BernhardPython (Computer program language)Explainable AIExplanation evaluationPythonPython (Llenguatge de programació)Àrees temàtiques de la UPC::Informàtica::Llenguatges de programació::PythonWe present teex, a Python toolbox for the evaluation of explanations. teex focuses on the evaluation of local explanations of the predictions of machine learning models by comparing them to ground-truth explanations. It supports several types of explanations: feature importance vectors, saliency maps, decision rules, and word importance maps. A collection of evaluation metrics is provided for each type. Real-world datasets and generators of synthetic data with ground-truth explanations are also contained within the library. teex contributes to research on explainable AI by providing tested, streamlined, user-friendly tools to compute quality metrics for the evaluation of explanation methods. Source code and a basic overview can be found at github.com/chus-chus/teex, and tutorials and full API documentation are at teex.readthedocs.io.teex has been developed as part of the TAIAO project (TimeEvolving Data Science/Artificial Intelligence for Advanced Open Environmental Science), funded by the New Zealand Ministry of Business, Innovation, and Employment (MBIE).Peer ReviewedElsevier20232023-10-2820232023-11-10journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/396241https://dx.doi.org/10.1016/j.neucom.2023.126642reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/3962412026-05-27T15:37:01Z
dc.title.none.fl_str_mv teex: a toolbox for the evaluation of explanations
title teex: a toolbox for the evaluation of explanations
spellingShingle teex: a toolbox for the evaluation of explanations
Antoñanzas Acero, Jesús Maria
Python (Computer program language)
Explainable AI
Explanation evaluation
Python
Python (Llenguatge de programació)
Àrees temàtiques de la UPC::Informàtica::Llenguatges de programació::Python
title_short teex: a toolbox for the evaluation of explanations
title_full teex: a toolbox for the evaluation of explanations
title_fullStr teex: a toolbox for the evaluation of explanations
title_full_unstemmed teex: a toolbox for the evaluation of explanations
title_sort teex: a toolbox for the evaluation of explanations
dc.creator.none.fl_str_mv Antoñanzas Acero, Jesús Maria
Jia, Yunzhe
Frank, Eibe
Bifet Figuerol, Albert Carles
Pfahringer, Bernhard
author Antoñanzas Acero, Jesús Maria
author_facet Antoñanzas Acero, Jesús Maria
Jia, Yunzhe
Frank, Eibe
Bifet Figuerol, Albert Carles
Pfahringer, Bernhard
author_role author
author2 Jia, Yunzhe
Frank, Eibe
Bifet Figuerol, Albert Carles
Pfahringer, Bernhard
author2_role author
author
author
author
dc.subject.none.fl_str_mv Python (Computer program language)
Explainable AI
Explanation evaluation
Python
Python (Llenguatge de programació)
Àrees temàtiques de la UPC::Informàtica::Llenguatges de programació::Python
topic Python (Computer program language)
Explainable AI
Explanation evaluation
Python
Python (Llenguatge de programació)
Àrees temàtiques de la UPC::Informàtica::Llenguatges de programació::Python
description We present teex, a Python toolbox for the evaluation of explanations. teex focuses on the evaluation of local explanations of the predictions of machine learning models by comparing them to ground-truth explanations. It supports several types of explanations: feature importance vectors, saliency maps, decision rules, and word importance maps. A collection of evaluation metrics is provided for each type. Real-world datasets and generators of synthetic data with ground-truth explanations are also contained within the library. teex contributes to research on explainable AI by providing tested, streamlined, user-friendly tools to compute quality metrics for the evaluation of explanation methods. Source code and a basic overview can be found at github.com/chus-chus/teex, and tutorials and full API documentation are at teex.readthedocs.io.
publishDate 2023
dc.date.none.fl_str_mv 2023
2023-10-28
2023
2023-11-10
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/396241
https://dx.doi.org/10.1016/j.neucom.2023.126642
url https://hdl.handle.net/2117/396241
https://dx.doi.org/10.1016/j.neucom.2023.126642
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.301603

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