A Systematic Literature Review on Support Vector Machines Applied to Classification

Miguel Angel Cano Lengua, Erik Alex Papa Quiroz

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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?

Original languageEnglish
Title of host publicationProceedings of the 2020 IEEE Engineering International Research Conference, EIRCON 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728183671
DOIs
StatePublished - 21 Oct 2020
Externally publishedYes
Event2020 IEEE Engineering International Research Conference, EIRCON 2020 - Lima, Peru
Duration: 21 Oct 202023 Oct 2020

Publication series

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

Conference

Conference2020 IEEE Engineering International Research Conference, EIRCON 2020
CountryPeru
CityLima
Period21/10/2023/10/20

Keywords

  • classification
  • hyperplane
  • linear and nonlinear separation
  • optimization algorithms
  • Vector Support Machines

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