A K-means Algorithm with a Novel Non-Metric Distance

Mu Chun Su, Chien Hsing Chou

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

4 Scopus citations

Abstract

In this paper, we propose a new clustering algorithm to cluster data. The proposed algorithm adopts a new non-metric measure based on the idea of "symmetry". The detected clusters may be a set of clusters of different geometrical structures. Three data sets are tested to illustrate the effectiveness of our proposed algorithm.

Original languageEnglish
Title of host publicationProceedings of the Fifth Joint Conference on Information Sciences, JCIS 2000, Volume 1
EditorsP.P. Wang, P.P. Wang
Pages417-420
Number of pages4
Edition1
StatePublished - 2000
EventProceedings of the Fifth Joint Conference on Information Sciences, JCIS 2000 - Atlantic City, NJ, United States
Duration: 27 Feb 20003 Mar 2000

Publication series

NameProceedings of the Joint Conference on Information Sciences
Number1
Volume5

Conference

ConferenceProceedings of the Fifth Joint Conference on Information Sciences, JCIS 2000
Country/TerritoryUnited States
CityAtlantic City, NJ
Period27/02/003/03/00

Keywords

  • Data Clustering
  • K-means algorithm
  • Pattern Recognition

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