K*-Means: A new generalized k-means clustering algorithm

Yiu Ming CHEUNG*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

139 Citations (Scopus)

Abstract

This paper presents a generalized version of the conventional k-means clustering algorithm [Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability, 1, University of California Press, Berkeley, 1967, p. 281]. Not only is this new one applicable to ellipse-shaped data clusters without dead-unit problem, but also performs correct clustering without pre-assigning the exact cluster number. We qualitatively analyze its underlying mechanism, and show its outstanding performance through the experiments.

Original languageEnglish
Pages (from-to)2883-2893
Number of pages11
JournalPattern Recognition Letters
Volume24
Issue number15
DOIs
Publication statusPublished - Nov 2003

Scopus Subject Areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

User-Defined Keywords

  • Cluster number
  • Clustering analysis
  • K-Means algorithm
  • Rival penalization

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