A modified version of the K-means algorithm with a distance based on cluster symmetry
Mu‐Chun Su, Chien-Hsing Chou · IEEE Transactions on Pattern Analysis and Machine Intelligence · 2001
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.