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A modified version of the K-means algorithm with a distance based on cluster symmetry

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2 Author(s)
Mu-Chun Su ; Dept. of Comput. Sci. & Inf. Eng., Nat. Central Univ., Chung-Li, Taiwan ; Chien-Hsing Chou

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 “point symmetry”. This kind of “point symmetry distance” can be applied in data clustering and human face detection. Several data sets are used to illustrate its effectiveness

Published in:

Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:23 ,  Issue: 6 )

Date of Publication:

Jun 2001

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