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

机译:鲁棒和归纳支持向量聚类的聚类结构的动态表征

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摘要

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
机译:开发了由支持向量聚类描述的聚类结构的拓扑和动态特征。结果表明,每个簇都可以分解成其组成的盆地级单元,并且可以自然地扩展到扩大的簇域,这是归纳簇的基础。还构造了一个简化的加权图,该图保留了簇的拓扑结构,并用于开发鲁棒的归纳聚类算法。仿真结果表明了该方法的鲁棒性和有效性。

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