Dynamic Characterization of Cluster Structures for Robust and Inductive Support Vector Clustering

A topological and dynamical characterization of the cluster structures described by the support vector clustering is developed. It is shown that each cluster can be decomposed into its constituent basin level cells and can be naturally extended to an enlarged clustered domain, which serves as a basi...

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Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence 2006-11, Vol.28 (11), p.1869-1874
Hauptverfasser: LEE, Jaewook, LEE, Daewon
Format: Artikel
Sprache:eng
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Zusammenfassung:A topological and dynamical characterization of the cluster structures described by the support vector clustering is developed. It is shown that each cluster can be decomposed into its constituent basin level cells and can be naturally extended to an enlarged clustered domain, which serves as a basis for inductive clustering. A simplified weighted graph preserving the topological structure of the clusters is also constructed and is employed to develop a robust and inductive clustering algorithm. Simulation results are given to illustrate the robustness and effectiveness of the proposed method
ISSN:0162-8828
1939-3539
2160-9292
DOI:10.1109/TPAMI.2006.225