A support vector clustering method
Ben-Hur, A.; Horn, D.; Siegelmann, H.T.; Vapnik, V.
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Volume 2, Issue , 2000 Page(s):724 - 727 vol.2
Digital Object Identifier   10.1109/ICPR.2000.906177
Summary:We present a novel kernel method for data clustering using a description of the data by support vectors. The kernel reflects a projection of the data points from data space to a high dimensional feature space. Cluster boundaries are defined as spheres in feature space, which represent complex geometric shapes in data space. We utilize this geometric representation of the data to construct a simple clustering algorithm

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