Incremental missing data imputation via modified granular evolving fuzzy model

Detalhes bibliográficos
Ano de defesa: 2018
Autor(a) principal: Garcia, Cristiano Mesquita lattes
Orientador(a): Leite, Daniel Furtado
Banca de defesa: Camargo, Heloisa de Arruda, Cintra, Marcos Evandro
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: eng
Instituição de defesa: Universidade Federal de Lavras
Programa de Pós-Graduação: Programa de Pós-Graduação em Engenharia de Sistemas e Automação
Departamento: Departamento de Engenharia
País: brasil
Palavras-chave em Português:
Evolving intelligence
Fuzzy systems
Data stream
Incremental learning
Missing data imputation
Inteligência em evolução
Sistemas Fuzzy
Fluxo de dados
Aprendizagem incremental
Imputação de dados perdidos
Área do conhecimento CNPq:
Engenharia de Software
Link de acesso: https://repositorio.ufla.br/handle/1/30140
Resumo: Não se aplica.
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spelling 2018-08-23T11:45:29Z2018-08-23T11:45:29Z2018-08-222018-07-17GARCIA, C. M. Incremental missing data imputation via modified granular evolving fuzzy model. 2018. 71 p. Dissertação (Mestrado em Engenharia de Sistemas e Automação)-Universidade Federal de Lavras, Lavras, 2018.https://repositorio.ufla.br/handle/1/30140Não se aplica.Large amounts of data have been produced daily. Extracting information and knowledge from data is meaningful for many purposes and endeavors, such as prediction of future values of time series, classification, semi-supervised learning and control. Computational intelligence and machine learning methods, such as neural networks and fuzzy systems, usually require complete datasets to work properly. Real-world datasets may contain missing values due to, e.g., malfunctioning of sensors or data transfer problems. In online environments, the properties of the data may change over time so that offline model training based on multiple passes over data is prohibited due to its inherent time and memory constraints. This study proposes a method for incremental missing data imputation using a modified granular evolving fuzzy model, namely evolving Fuzzy Granular Predictor (eFGP). eFGP is equipped with an incremental learning algorithm that simultaneously impute missing data and adapt model parameters and structure. eFGP is able to handle single and multiple missing values on data samples by developing reduced-term consequent polynomials and relying on information of time-varying granules. The method is evaluated in prediction and function approximation problems considering the constraints of online data stream. Particularly, the underlying data streams may be subject to missing at random (MAR) and missing completely at random (MCAR) types of missing values. Predictions given by the model evolved after data imputation are compared to those provided by state-of-the-art fuzzy and neuro-fuzzy evolving modeling methods in the sense of accuracy. Results and statistical comparisons with other approaches corroborate to conclude that eFGP is competitive as a general evolving intelligent method and overcomes its counterparts in MAR and MCAR scenarios according to an ANOVA-Tukey statistical hypothesis test.Universidade Federal de LavrasPrograma de Pós-Graduação em Engenharia de Sistemas e AutomaçãoUFLAbrasilDepartamento de EngenhariaEngenharia de SoftwareEvolving intelligenceFuzzy systemsData streamIncremental learningMissing data imputationInteligência em evoluçãoSistemas FuzzyFluxo de dadosAprendizagem incrementalImputação de dados perdidosIncremental missing data imputation via modified granular evolving fuzzy modelImputação incremental de dados faltantes via modelo granular fuzzy evolutivo modificadoinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisLeite, Daniel FurtadoEsmin, Ahmed Ali AbdallaCamargo, Heloisa de ArrudaCintra, Marcos Evandrohttp://lattes.cnpq.br/0099830309630110Garcia, Cristiano Mesquitainfo:eu-repo/semantics/openAccessengreponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAORIGINALDISSERTAÇÃO_Incremental missing data imputation via modified granular evolving fuzzy model.pdfDISSERTAÇÃO_Incremental missing data imputation via modified granular evolving fuzzy model.pdfapplication/pdf1468079https://repositorio.ufla.br/bitstreams/65f38ea7-e60c-4e12-bbc4-344834f4f5af/download2e9e0171a505e10cfc1db4d03fd46d9cMD51trueAnonymousREADLICENSElicense.txtlicense.txttext/plain; charset=utf-8953https://repositorio.ufla.br/bitstreams/d21b041b-0cfa-4884-ac51-9da3245ca434/download760884c1e72224de569e74f79eb87ce3MD52falseAnonymousREADTEXTDISSERTAÇÃO_Incremental missing data imputation via modified granular evolving fuzzy model.pdf.txtDISSERTAÇÃO_Incremental missing data imputation via modified granular evolving fuzzy model.pdf.txtExtracted texttext/plain100899https://repositorio.ufla.br/bitstreams/b3c57134-ee0c-4b12-89b9-dc64bdb50c66/download36556e9c8160706ec6ee89a06f2232ebMD53falseAnonymousREADTHUMBNAILDISSERTAÇÃO_Incremental missing data imputation via modified granular evolving fuzzy model.pdf.jpgDISSERTAÇÃO_Incremental missing data imputation via modified granular evolving fuzzy model.pdf.jpgGenerated Thumbnailimage/jpeg3115https://repositorio.ufla.br/bitstreams/2f1c2208-9e5b-4024-a793-617c7cdae40e/download91cc3e791be9d8616272f3c77f1dc137MD54falseAnonymousREAD1/301402025-08-19 09:59:29.772open.accessoai:repositorio.ufla.br:1/30140https://repositorio.ufla.brRepositório InstitucionalPUBhttps://repositorio.ufla.br/server/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2025-08-19T12:59:29Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)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
dc.title.pt_BR.fl_str_mv Incremental missing data imputation via modified granular evolving fuzzy model
dc.title.alternative.pt_BR.fl_str_mv Imputação incremental de dados faltantes via modelo granular fuzzy evolutivo modificado
title Incremental missing data imputation via modified granular evolving fuzzy model
spellingShingle Incremental missing data imputation via modified granular evolving fuzzy model
Garcia, Cristiano Mesquita
Engenharia de Software
Evolving intelligence
Fuzzy systems
Data stream
Incremental learning
Missing data imputation
Inteligência em evolução
Sistemas Fuzzy
Fluxo de dados
Aprendizagem incremental
Imputação de dados perdidos
title_short Incremental missing data imputation via modified granular evolving fuzzy model
title_full Incremental missing data imputation via modified granular evolving fuzzy model
title_fullStr Incremental missing data imputation via modified granular evolving fuzzy model
title_full_unstemmed Incremental missing data imputation via modified granular evolving fuzzy model
title_sort Incremental missing data imputation via modified granular evolving fuzzy model
author Garcia, Cristiano Mesquita
author_facet Garcia, Cristiano Mesquita
author_role author
dc.contributor.advisor1.fl_str_mv Leite, Daniel Furtado
dc.contributor.advisor-co1.fl_str_mv Esmin, Ahmed Ali Abdalla
dc.contributor.referee1.fl_str_mv Camargo, Heloisa de Arruda
dc.contributor.referee2.fl_str_mv Cintra, Marcos Evandro
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/0099830309630110
dc.contributor.author.fl_str_mv Garcia, Cristiano Mesquita
contributor_str_mv Leite, Daniel Furtado
Esmin, Ahmed Ali Abdalla
Camargo, Heloisa de Arruda
Cintra, Marcos Evandro
dc.subject.cnpq.fl_str_mv Engenharia de Software
topic Engenharia de Software
Evolving intelligence
Fuzzy systems
Data stream
Incremental learning
Missing data imputation
Inteligência em evolução
Sistemas Fuzzy
Fluxo de dados
Aprendizagem incremental
Imputação de dados perdidos
dc.subject.por.fl_str_mv Evolving intelligence
Fuzzy systems
Data stream
Incremental learning
Missing data imputation
Inteligência em evolução
Sistemas Fuzzy
Fluxo de dados
Aprendizagem incremental
Imputação de dados perdidos
description Não se aplica.
publishDate 2018
dc.date.submitted.none.fl_str_mv 2018-07-17
dc.date.accessioned.fl_str_mv 2018-08-23T11:45:29Z
dc.date.available.fl_str_mv 2018-08-23T11:45:29Z
dc.date.issued.fl_str_mv 2018-08-22
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.citation.fl_str_mv GARCIA, C. M. Incremental missing data imputation via modified granular evolving fuzzy model. 2018. 71 p. Dissertação (Mestrado em Engenharia de Sistemas e Automação)-Universidade Federal de Lavras, Lavras, 2018.
dc.identifier.uri.fl_str_mv https://repositorio.ufla.br/handle/1/30140
identifier_str_mv GARCIA, C. M. Incremental missing data imputation via modified granular evolving fuzzy model. 2018. 71 p. Dissertação (Mestrado em Engenharia de Sistemas e Automação)-Universidade Federal de Lavras, Lavras, 2018.
url https://repositorio.ufla.br/handle/1/30140
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Universidade Federal de Lavras
dc.publisher.program.fl_str_mv Programa de Pós-Graduação em Engenharia de Sistemas e Automação
dc.publisher.initials.fl_str_mv UFLA
dc.publisher.country.fl_str_mv brasil
dc.publisher.department.fl_str_mv Departamento de Engenharia
publisher.none.fl_str_mv Universidade Federal de Lavras
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFLA
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instname_str Universidade Federal de Lavras (UFLA)
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