A Support Vector Clustering Method

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	Similar Articles Articles by Asa Ben-Hur Articles by Hava T. Siegelmann Articles by David Horn Articles by Vladimir Vapnik

15th International Conference on Pattern Recognition (ICPR'00) - Volume 2

Barcelona, Spain

September 03-September 08

ISBN: 0-7695-0750-6

	ASCII Text	x
	Asa Ben-Hur, Hava T. Siegelmann, David Horn, Vladimir Vapnik, "A Support Vector Clustering Method," Pattern Recognition, International Conference on, vol. 2, pp. 2724, 15th International Conference on Pattern Recognition (ICPR'00) - Volume 2, 2000.

	BibTex	x
	@article{ 10.1109/ICPR.2000.906177, author = {Asa Ben-Hur and Hava T. Siegelmann and David Horn and Vladimir Vapnik}, title = {A Support Vector Clustering Method}, journal ={Pattern Recognition, International Conference on}, volume = {2}, year = {2000}, isbn = {0-7695-0750-6}, pages = {2724}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2000.906177}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Pattern Recognition, International Conference on TI - A Support Vector Clustering Method SN - 0-7695-0750-6 SP EP A1 - Asa Ben-Hur, A1 - Hava T. Siegelmann, A1 - David Horn, A1 - Vladimir Vapnik, PY - 2000 VL - 2 JA - Pattern Recognition, International Conference on ER -

Asa Ben-Hur, Technion

Hava T. Siegelmann, Technion

David Horn, Tel Aviv University

Vladimir Vapnik, AT&T Labs Research

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2000.906177

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.

Citation:

Asa Ben-Hur, Hava T. Siegelmann, David Horn, Vladimir Vapnik, "A Support Vector Clustering Method," icpr, vol. 2, pp.2724, 15th International Conference on Pattern Recognition (ICPR'00) - Volume 2, 2000

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