AutoOC: A Python module for automated multi-objective One-Class Classification

Detalhes bibliográficos
Autor(a) principal: Ferreira, Luís
Data de Publicação: 2023
Outros Autores: Cortez, Paulo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/1822/87713
Resumo: AutoOC is an open-source Python module to efficiently automate the selection and hyperparameter tuning of quality OCC (One-Class Classification) learners. By using a GE (Grammatical Evolution) approach, AutoOC searches for five base learners, namely IF (Isolation Forest), LOF (Local Outlier Factor), OC-SVM (One-Class SVM), AE (Autoencoder), and VAE (Variational Autoencoder). The module provides a multi-objective search, where predictive performance and computational efficiency are simultaneously optimized. By providing a simple set of functions, AutoOC allows the user to easily generate OCC models for a dataset, being well-suited for anomaly detection tasks, where most of the data is composed of normal records.
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spelling AutoOC: A Python module for automated multi-objective One-Class ClassificationAutomated machine learningDeep autoencodersGrammatical EvolutionMulti-objective optimizationOne-Class ClassificationPythonCiências Naturais::Ciências da Computação e da InformaçãoAutoOC is an open-source Python module to efficiently automate the selection and hyperparameter tuning of quality OCC (One-Class Classification) learners. By using a GE (Grammatical Evolution) approach, AutoOC searches for five base learners, namely IF (Isolation Forest), LOF (Local Outlier Factor), OC-SVM (One-Class SVM), AE (Autoencoder), and VAE (Variational Autoencoder). The module provides a multi-objective search, where predictive performance and computational efficiency are simultaneously optimized. By providing a simple set of functions, AutoOC allows the user to easily generate OCC models for a dataset, being well-suited for anomaly detection tasks, where most of the data is composed of normal records.- (undefined)ElsevierUniversidade do MinhoFerreira, LuísCortez, Paulo20232023-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/87713engFerreira, L., & Cortez, P. (2023, November). AutoOC: A Python module for automated multi-objective One-Class Classification. Software Impacts. Elsevier BV. http://doi.org/10.1016/j.simpa.2023.10059010.1016/j.simpa.2023.100590https://www.softwareimpacts.com/article/S2665-9638(23)00127-6/fulltextinfo: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:RCAAP2024-01-06T01:27:55Zoai:repositorium.sdum.uminho.pt:1822/87713Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:30:21.125675Repositório 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 AutoOC: A Python module for automated multi-objective One-Class Classification
title AutoOC: A Python module for automated multi-objective One-Class Classification
spellingShingle AutoOC: A Python module for automated multi-objective One-Class Classification
Ferreira, Luís
Automated machine learning
Deep autoencoders
Grammatical Evolution
Multi-objective optimization
One-Class Classification
Python
Ciências Naturais::Ciências da Computação e da Informação
title_short AutoOC: A Python module for automated multi-objective One-Class Classification
title_full AutoOC: A Python module for automated multi-objective One-Class Classification
title_fullStr AutoOC: A Python module for automated multi-objective One-Class Classification
title_full_unstemmed AutoOC: A Python module for automated multi-objective One-Class Classification
title_sort AutoOC: A Python module for automated multi-objective One-Class Classification
author Ferreira, Luís
author_facet Ferreira, Luís
Cortez, Paulo
author_role author
author2 Cortez, Paulo
author2_role author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Ferreira, Luís
Cortez, Paulo
dc.subject.por.fl_str_mv Automated machine learning
Deep autoencoders
Grammatical Evolution
Multi-objective optimization
One-Class Classification
Python
Ciências Naturais::Ciências da Computação e da Informação
topic Automated machine learning
Deep autoencoders
Grammatical Evolution
Multi-objective optimization
One-Class Classification
Python
Ciências Naturais::Ciências da Computação e da Informação
description AutoOC is an open-source Python module to efficiently automate the selection and hyperparameter tuning of quality OCC (One-Class Classification) learners. By using a GE (Grammatical Evolution) approach, AutoOC searches for five base learners, namely IF (Isolation Forest), LOF (Local Outlier Factor), OC-SVM (One-Class SVM), AE (Autoencoder), and VAE (Variational Autoencoder). The module provides a multi-objective search, where predictive performance and computational efficiency are simultaneously optimized. By providing a simple set of functions, AutoOC allows the user to easily generate OCC models for a dataset, being well-suited for anomaly detection tasks, where most of the data is composed of normal records.
publishDate 2023
dc.date.none.fl_str_mv 2023
2023-01-01T00:00:00Z
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 https://hdl.handle.net/1822/87713
url https://hdl.handle.net/1822/87713
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Ferreira, L., & Cortez, P. (2023, November). AutoOC: A Python module for automated multi-objective One-Class Classification. Software Impacts. Elsevier BV. http://doi.org/10.1016/j.simpa.2023.100590
10.1016/j.simpa.2023.100590
https://www.softwareimpacts.com/article/S2665-9638(23)00127-6/fulltext
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.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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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