The K-Exemplars clustering method

Hsiou Hen Kao, Li Ching Huang, Miin Jye Wen, Kuo Lung Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In order to apply the concepts of k-means to deal with any specified dissimilarity measures, we propose a k-exemplars clustering method that modifies k-means by restricting the cluster centers on data points. The proposed method not only has similar clustering accuracy as k-means but also faster convergence. According to the definition of the objective function of k-exemplars, the proposed method can be used to deal with a relational data set, and the cluster centers (exemplars) of each cluster will also be extracted. Hence, the k-exemplars can work in an environment with specified dissimilarity measures.

Original languageEnglish
Title of host publicationMaterials and Diverse Technologies in Industry and Manufacture
Pages224-230
Number of pages7
DOIs
Publication statusPublished - 2013 Oct 22
Event2013 International Conference on Mechanical, Automotive and Materials Engineering, CMAME 2013 - , Hong Kong
Duration: 2013 Jul 262013 Jul 27

Publication series

NameApplied Mechanics and Materials
Volume376
ISSN (Print)1660-9336
ISSN (Electronic)1662-7482

Other

Other2013 International Conference on Mechanical, Automotive and Materials Engineering, CMAME 2013
CountryHong Kong
Period13-07-2613-07-27

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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