An algebraic multi-class classification method

Q. He*, Zhen Yan Liu, Zhong Zhi Shi

*Corresponding author for this work

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

2 Citations (Scopus)

Abstract

An algebraic multi-class classification method AHSC, i.e. Algebraic Hyper Surface Classification, is proposed. The separating algebraic hyper surface of two-class data may be directly constructed by a single polynomial in theory, but it is too difficult to separate multi-class data by a single polynomial even though the polynomial is multivalued. AHSC can be used for classifying multi-class data by integrating a series of polynomial networks based on binary numbers which are used for labeling the classes of samples. The problem that multi-class data can not always be separated by a single polynomial is solved by AHSC. Moreover, the order of polynomial can be chosen by using an adaptive method. The experiment results show that the new method can efficiently and accurately classify multi-class and high dimension data.

Original languageEnglish
Title of host publicationProceedings of 2004 International Conference on Machine Learning and Cybernetics
Pages3307-3312
Number of pages6
Publication statusPublished - 2004
EventProceedings of 2004 International Conference on Machine Learning and Cybernetics - Shanghai, China
Duration: 26 Aug 200429 Aug 2004

Publication series

NameProceedings of 2004 International Conference on Machine Learning and Cybernetics
Volume5

Conference

ConferenceProceedings of 2004 International Conference on Machine Learning and Cybernetics
Country/TerritoryChina
CityShanghai
Period26/08/0429/08/04

Keywords

  • Adaptive
  • Algebraic hyper surface
  • Multi-class classification
  • Polynomial network

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