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

Authors:
Jaewook Lee;Daewon Lee
Affiliations:
IEEE;-
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
2006

Citing 8
Cited 27

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Abstract

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.