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A systematic literature review on support vector machines aplied to classification

dc.contributor.authorCano Lengua, Miguel Angel
dc.contributor.authorPapa Quiroz, Erik Alex
dc.date.accessioned2021-07-16T18:14:04Z
dc.date.available2021-07-16T18:14:04Z
dc.date.issued2020-11-19
dc.identifier.citationCano, M. A., & Papa, E. A. (2020). A systematic literature review on support vector machines aplied to classification. 2020 IEEE Engineering International Research Conference (EIRCON), 1-4. https://doi.org/10.1109/EIRCON51178.2020.9254028es_PE
dc.identifier.urihttps://hdl.handle.net/11537/27242
dc.descriptionEl texto completo de este trabajo no está disponible en el Repositorio Académico UPN por restricciones de la casa editorial donde ha sido publicado.es_PE
dc.description.abstractABSTRACT This paper aims to identify the current state of the art of the latest research related to support vector machines through a literature review system according to the methodology proposed by Kitchenham and Charter, in order to answer the following research questions: Q1: In which research areas are they used? Q2: What are the main applications related with classification? Q3: What optimization methods or algorithms are used in SVMs?es_PE
dc.formatapplication/pdfes_PE
dc.language.isoenges_PE
dc.publisherIEEEes_PE
dc.rightsinfo:eu-repo/semantics/openAccesses_PE
dc.rightsAtribución-NoComercial-CompartirIgual 3.0 Estados Unidos de América*
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.sourceUniversidad Privada del Nortees_PE
dc.sourceRepositorio Institucional - UPNes_PE
dc.subjectMáquinases_PE
dc.subjectClasificaciónes_PE
dc.subjectVectoreses_PE
dc.subjectAlgoritmoses_PE
dc.titleA systematic literature review on support vector machines aplied to classificationes_PE
dc.typeinfo:eu-repo/semantics/conferenceObjectes_PE
dc.publisher.countryPEes_PE
dc.identifier.journal2020 IEEE Engineering International Research Conference (EIRCON)es_PE
dc.description.peer-reviewRevisión por pareses_PE
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#2.11.04es_PE
dc.description.sedeComases_PE
dc.identifier.doihttps://doi.org/10.1109/EIRCON51178.2020.9254028


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