A new clustering method based on references, density and neural network

被引：0
|
作者：
Gou, Hong-Tu [1 ]
Xu, Jian-Suo [2 ]
Wang, Li [3 ]
机构：
[1] Tianjin Univ, Sch Management, Tianjin 300072, Peoples R China
[2] Henan Normal Univ, Sch Management & Econ, Xinxiang 453007, Peoples R China
[3] AnShan Univ Sci & Technol, Sch Comp, AnShan 114044, Peoples R China
来源：
PROCEEDINGS OF 2006 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2006年
关键词：
clustering; neural network; density; reference; data mining;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, a new clustering algorithm that is called RDVS (clustering using references and density by ViSOM) is presented to overcome the shortcomings of clustering methods based on density or neural network. The creativity of RDVS is capturing the shape and extent of a cluster by references and their densities, and then analyzes them by ViSOM. RDVS keeps the ability of density-based clustering method's good features and it can give a visual clustering results. Both theory analysis and experimental results confirm that RDVS can discover clusters with arbitrary shape and is insensitive to noise data, and its executing efficiency is much higher than visom.
引用
收藏
页码：1060 / +
页数：3
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