Comparison of the techniques decision tree and MLP for data mining in SPAMs detection to computer networks

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorCollege of Technology of São Paulo State-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorCosta, Kelton-
Autor(es): dc.creatorRibeiro, Patricia-
Autor(es): dc.creatorCamargo, Atair-
Autor(es): dc.creatorRossi, Victor-
Autor(es): dc.creatorMartins, Henrique-
Autor(es): dc.creatorNeves, Miguel-
Autor(es): dc.creatorFabris, Ricardo-
Autor(es): dc.creatorImaisumi, Renato-
Autor(es): dc.creatorPapa, Joao Paulo-
Data de aceite: dc.date.accessioned2025-08-21T21:56:36Z-
Data de disponibilização: dc.date.available2025-08-21T21:56:36Z-
Data de envio: dc.date.issued2022-04-29-
Data de envio: dc.date.issued2022-04-29-
Data de envio: dc.date.issued2013-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/INTECH.2013.6653725-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/227401-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/227401-
Descrição: dc.descriptionAnomalies in computer networks has increased in the last decades and raised concern to create techniques to identify these unusual traffic patterns. This research aims to use data mining techniques in order to correctly identify these anomalies. Weka is a collection of machine learning algorithms for data mining tasks - was used to identify and analyse anomalies of a data set called SPAMBASE in order to improve this environment. © 2013 IEEE.-
Descrição: dc.descriptionCollege of Technology of São Paulo State, Bauru-
Descrição: dc.descriptionDepartment of Computing UNESP University Paulista State, Bauru-
Descrição: dc.descriptionDepartment of Computing UNESP University Paulista State, Bauru-
Formato: dc.format344-348-
Idioma: dc.languageen-
Relação: dc.relation2013 3rd International Conference on Innovative Computing Technology, INTECH 2013-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectAnomalies-
Palavras-chave: dc.subjectArtificial Neural Networks-
Palavras-chave: dc.subjectComputer networks-
Palavras-chave: dc.subjectData Mining-
Título: dc.titleComparison of the techniques decision tree and MLP for data mining in SPAMs detection to computer networks-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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