A classification method based on a cloud of spheres

Detalhes bibliográficos
Autor(a) principal: Dias, Tiago
Data de Publicação: 2023
Outros Autores: Amaral, Paula
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/164888
Resumo: Funding Information: This work is funded by national funds through the FCT - Fundação para a Ciência e a Tecnologia , I.P., under the scope of the projects UIDB/00297/2020 , UIDP/00297/2020 (Center for Mathematics and Applications). Publisher Copyright: © 2023 The Author(s)
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spelling A classification method based on a cloud of spheresAnomaly detectionAutomatic classificationMINLPSpherical separationModelling and SimulationManagement Science and Operations ResearchControl and OptimizationComputational MathematicsFunding Information: This work is funded by national funds through the FCT - Fundação para a Ciência e a Tecnologia , I.P., under the scope of the projects UIDB/00297/2020 , UIDP/00297/2020 (Center for Mathematics and Applications). Publisher Copyright: © 2023 The Author(s)In this article we propose a binary classification model to distinguish a specific class that corresponds to a characteristic that we intend to identify (fraud, spam, disease). The classification model is based on a cloud of spheres that circumscribes the points of the class to be identified. It is intended to build a model based on a cloud and not on a disjoint set of clouds, establishing this condition on the connectivity of a graph induced by the spheres. To solve the problem, designed by a Cloud of Connected Spheres, a quadratic model with continuous and binary variables (MINLP) is proposed with the minimization of the number of spheres. The issue of connectivity implies in many models the imposition of an exponential number of constraints. However, because of the specific conditions of the problem under study, connectivity is enforced with linear constraints that scale quadratically with K, which serves as an upper bound on the number of spheres. This classification model is effective when the structure of the class to be identified is highly non-linear and non-convex, also adapting to the case of linear separation. Unlike neural networks, the classification model is transparent, with the structure perfectly identified. No kernel functions are used and it is not necessary to use meta-parameters unless it is intended also to maximize the separation margin as it is done in SVM. Finding the global optima for large instances is quite challenging, and to address this, a heuristic is proposed. The heuristic demonstrates nice results on a set of frequently tested real problems when compared to state-of-the-art algorithms.DM - Departamento de MatemáticaCMA - Centro de Matemática e AplicaçõesRUNDias, TiagoAmaral, Paula2024-03-13T23:28:43Z20232023-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article17application/pdfhttp://hdl.handle.net/10362/164888eng2192-4406PURE: 78472626https://doi.org/10.1016/j.ejco.2023.100077info: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:RCAAP2024-03-18T01:47:05Zoai:run.unl.pt:10362/164888Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T04:02:03.345451Repositório 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 A classification method based on a cloud of spheres
title A classification method based on a cloud of spheres
spellingShingle A classification method based on a cloud of spheres
Dias, Tiago
Anomaly detection
Automatic classification
MINLP
Spherical separation
Modelling and Simulation
Management Science and Operations Research
Control and Optimization
Computational Mathematics
title_short A classification method based on a cloud of spheres
title_full A classification method based on a cloud of spheres
title_fullStr A classification method based on a cloud of spheres
title_full_unstemmed A classification method based on a cloud of spheres
title_sort A classification method based on a cloud of spheres
author Dias, Tiago
author_facet Dias, Tiago
Amaral, Paula
author_role author
author2 Amaral, Paula
author2_role author
dc.contributor.none.fl_str_mv DM - Departamento de Matemática
CMA - Centro de Matemática e Aplicações
RUN
dc.contributor.author.fl_str_mv Dias, Tiago
Amaral, Paula
dc.subject.por.fl_str_mv Anomaly detection
Automatic classification
MINLP
Spherical separation
Modelling and Simulation
Management Science and Operations Research
Control and Optimization
Computational Mathematics
topic Anomaly detection
Automatic classification
MINLP
Spherical separation
Modelling and Simulation
Management Science and Operations Research
Control and Optimization
Computational Mathematics
description Funding Information: This work is funded by national funds through the FCT - Fundação para a Ciência e a Tecnologia , I.P., under the scope of the projects UIDB/00297/2020 , UIDP/00297/2020 (Center for Mathematics and Applications). Publisher Copyright: © 2023 The Author(s)
publishDate 2023
dc.date.none.fl_str_mv 2023
2023-01-01T00:00:00Z
2024-03-13T23:28:43Z
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/10362/164888
url http://hdl.handle.net/10362/164888
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2192-4406
PURE: 78472626
https://doi.org/10.1016/j.ejco.2023.100077
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 17
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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