Analysis of Structural Clustering Based on Normalized Metric
TANG Xu-Qing1, ZHU Ping1, CHENG Jia-Xing2
1.School of Science, Jiangnan University, Wuxi 214122 2.Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Anhui University, Hefei 230039
Abstract:On the basis of the ordered granular space, structural clustering (or classification) analysis is proposed based on normalized metric. Firstly, the concept of consistent clustering according to metric is presented, and the research on consistent clustering characteristic of ordered granular space is given. Secondly, structural clustering analysis theory is given based on normalized metric, and the algorithm to obtain its structural clustering is discussed. Thirdly, the research on the determination of the optimal clustering based on ordered granular space is carried out. A method to obtain the optimal clustering is given, and the method is global optimal. Finally, the fusion technology based on structural clusters of normalized metrics is studied by the intersection operation of two normalized metrics. The conclusions provide a comprehensive theory and methodology on structural clustering (or classification) analysis based on metric.
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