Clustering by Sorting Potential Values (CSPV): A novel potential-based clustering method

被引:39
作者
Lu, Yonggang [1 ]
Wan, Yi [1 ]
机构
[1] Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou 730000, Peoples R China
关键词
Clustering; Potential field; Spatial distribution; Distance matrix; Pattern recognition;
D O I
10.1016/j.patcog.2012.02.035
中图分类号
TP18 [人工智能理论];
学科分类号
140502 [人工智能];
摘要
A novel clustering method called Clustering by Sorting Potential Values (CSPV) is proposed. The clustering is done in an efficient tree-growing fashion based on both the distances and the hypothetical potential values produced from the distribution of all the data points. The method is simple but is shown to be very effective in identifying different kinds of clusters. It outperforms four popular clustering methods in most of our experiments and is the only one that works for all the six studied data sets. Moreover, it is designed as a generic method which can be easily applied to different clustering problems. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:3512 / 3522
页数:11
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