Uncertainty-Based Rejection in Machine Learning: Implications for Model Development and Interpretability

Detalhes bibliográficos
Autor(a) principal: Barandas, Marília
Data de Publicação: 2022
Outros Autores: Folgado, Duarte, Santos, Ricardo, Simão, Raquel, Gamboa, Hugo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/134349
Resumo: POCI-01-0247-FEDER-033479
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spelling Uncertainty-Based Rejection in Machine Learning: Implications for Model Development and InterpretabilityArtificial intelligenceHuman activity recognitionInterpretabilityMachine learningRejection optionUncertainty quantificationControl and Systems EngineeringSignal ProcessingHardware and ArchitectureComputer Networks and CommunicationsElectrical and Electronic EngineeringPOCI-01-0247-FEDER-033479Uncertainty is present in every single prediction of Machine Learning (ML) models. Uncertainty Quantification (UQ) is arguably relevant, in particular for safety-critical applications. Prior research focused on the development of methods to quantify uncertainty; however, less attention has been given to how to leverage the knowledge of uncertainty in the process of model development. This work focused on applying UQ into practice, closing the gap of its utility in the ML pipeline and giving insights into how UQ is used to improve model development and its interpretability. We identified three main research questions: (1) How can UQ contribute to choosing the most suitable model for a given classification task? (2) Can UQ be used to combine different models in a principled manner? (3) Can visualization techniques improve UQ’s interpretability? These questions are answered by applying several methods to quantify uncertainty in both a simulated dataset and a real-world dataset of Human Activity Recognition (HAR). Our results showed that uncertainty quantification can increase model robustness and interpretability.DF – Departamento de FísicaLIBPhys-UNLRUNBarandas, MaríliaFolgado, DuarteSantos, RicardoSimão, RaquelGamboa, Hugo2022-03-11T23:22:45Z2022-02-012022-02-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10362/134349eng2079-9292PURE: 36763081https://doi.org/10.3390/electronics11030396info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:12:49Zoai:run.unl.pt:10362/134349Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:48:04.502058Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Uncertainty-Based Rejection in Machine Learning: Implications for Model Development and Interpretability
title Uncertainty-Based Rejection in Machine Learning: Implications for Model Development and Interpretability
spellingShingle Uncertainty-Based Rejection in Machine Learning: Implications for Model Development and Interpretability
Barandas, Marília
Artificial intelligence
Human activity recognition
Interpretability
Machine learning
Rejection option
Uncertainty quantification
Control and Systems Engineering
Signal Processing
Hardware and Architecture
Computer Networks and Communications
Electrical and Electronic Engineering
title_short Uncertainty-Based Rejection in Machine Learning: Implications for Model Development and Interpretability
title_full Uncertainty-Based Rejection in Machine Learning: Implications for Model Development and Interpretability
title_fullStr Uncertainty-Based Rejection in Machine Learning: Implications for Model Development and Interpretability
title_full_unstemmed Uncertainty-Based Rejection in Machine Learning: Implications for Model Development and Interpretability
title_sort Uncertainty-Based Rejection in Machine Learning: Implications for Model Development and Interpretability
author Barandas, Marília
author_facet Barandas, Marília
Folgado, Duarte
Santos, Ricardo
Simão, Raquel
Gamboa, Hugo
author_role author
author2 Folgado, Duarte
Santos, Ricardo
Simão, Raquel
Gamboa, Hugo
author2_role author
author
author
author
dc.contributor.none.fl_str_mv DF – Departamento de Física
LIBPhys-UNL
RUN
dc.contributor.author.fl_str_mv Barandas, Marília
Folgado, Duarte
Santos, Ricardo
Simão, Raquel
Gamboa, Hugo
dc.subject.por.fl_str_mv Artificial intelligence
Human activity recognition
Interpretability
Machine learning
Rejection option
Uncertainty quantification
Control and Systems Engineering
Signal Processing
Hardware and Architecture
Computer Networks and Communications
Electrical and Electronic Engineering
topic Artificial intelligence
Human activity recognition
Interpretability
Machine learning
Rejection option
Uncertainty quantification
Control and Systems Engineering
Signal Processing
Hardware and Architecture
Computer Networks and Communications
Electrical and Electronic Engineering
description POCI-01-0247-FEDER-033479
publishDate 2022
dc.date.none.fl_str_mv 2022-03-11T23:22:45Z
2022-02-01
2022-02-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/134349
url http://hdl.handle.net/10362/134349
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2079-9292
PURE: 36763081
https://doi.org/10.3390/electronics11030396
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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