A Clustering Algorithm based on Delaunay Triangulation

被引：1
作者：
Xia, Ying [1 ]
Peng, Xi [1 ]
机构：
[1] Chongqing Univ Posts & Telecom, Sino Korea ChongQing GIS Res Ctr, Chongqing 400065, Peoples R China
来源：
2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23 | 2008年
关键词：
Delaunay triangulation; Cluster with Parameter-free; Median;
D O I：
10.1109/WCICA.2008.4593651
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Most clustering methods require user-specified parameters or prior knowledge to produce their best results, this demands pre-processing or several trials. Both are extremely expensive and inefficient, because the best-fit parameters are not easy to get. This paper presents a new approach (CBDTM) which is on the basis of Delaunay Triangulation. This approach introduces the median length of k-nearest edges as measure to divide edges for each point. The parameters of CBDTM are not specified by users, and the experiment shows to us that it can find different shape dusters not only in different density data sets, but also in data sets with noise. AD operations complete within expected time O(nlogn), where n is the number of the data sets. The performance comparison experiments show to us, CBDTM more efficient and it has better quality than AUTOCLUST.
引用
收藏
页码：4517 / 4521
页数：5
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