A Modified Version of the K-Means Algorithm with a Distance Based on Cluster Symmetry

  • Authors:
  • Mu-Chun Su;Chien-Hsing Chou

  • Affiliations:
  • National Central Univ., Chung-Li, Taiwan;Tamkang Univ., Tamsui, Taiwan

  • Venue:
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Year:
  • 2001

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Abstract

In this paper, we propose a modified version of the K-means algorithm to cluster data. The proposed algorithm adopts a novel nonmetric distance measure based on the idea of 驴point symmetry.驴 This kind of 驴point symmetry distance驴 can be applied in data clustering and human face detection. Several data sets are used to illustrate its effectiveness.