An output grouping based approach to multiclass classification using support vector machines

Xuan Zhao*, Steven Guan, Ka Lok Man

*Corresponding author for this work

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

3 Citations (Scopus)

Abstract

Support Vector Machine (SVM) classifiers are binary classifiers in nature, which have to be coupled/assembled to solve multi-class problems. One-Versus-Rest (1-v-r) is a fast and accurate method for SVM multiclass classification. This paper investigates the effect of output grouping on multiclass classification with SVM and offers an even faster version of 1-v-r based on our output grouping algorithm.

Original languageEnglish
Title of host publicationAdvanced Multimedia and Ubiquitous Engineering - FutureTech and MUE
EditorsHai Jin, Young-Sik Jeong, Muhammad Khurram Khan, James J. Park
PublisherSpringer Verlag
Pages389-395
Number of pages7
ISBN (Print)9789811015359
DOIs
Publication statusPublished - 2016
Event11th International Conference on Future Information Technology, FutureTech 2016 - Beijing, China
Duration: 20 Apr 201622 Apr 2016

Publication series

NameLecture Notes in Electrical Engineering
Volume393
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference11th International Conference on Future Information Technology, FutureTech 2016
Country/TerritoryChina
CityBeijing
Period20/04/1622/04/16

Keywords

  • Decomposition method
  • Multiclass classification
  • Output grouping
  • Support vector machine

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