A Systematic Literature Review on Support Vector Machines Applied to Classification

Miguel Angel Cano Lengua, Erik Alex Papa Quiroz

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

6 Citas (Scopus)

Resumen

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?

Idioma originalInglés
Título de la publicación alojadaProceedings of the 2020 IEEE Engineering International Research Conference, EIRCON 2020
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781728183671
DOI
EstadoPublicada - 21 oct. 2020
Evento2020 IEEE Engineering International Research Conference, EIRCON 2020 - Lima, Perú
Duración: 21 oct. 202023 oct. 2020

Serie de la publicación

NombreProceedings of the 2020 IEEE Engineering International Research Conference, EIRCON 2020

Conferencia

Conferencia2020 IEEE Engineering International Research Conference, EIRCON 2020
País/TerritorioPerú
CiudadLima
Período21/10/2023/10/20

Nota bibliográfica

Publisher Copyright:
© 2020 IEEE.

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