Clustering by comparing regions of different density
作者:
Ja‐Chen Lin,
Jenn‐Yih Lin,
Zen Chen,
期刊:
Journal of the Chinese Institute of Engineers
(Taylor Available online 1996)
卷期:
Volume 19,
issue 1
页码: 35-47
ISSN:0253-3839
年代: 1996
DOI:10.1080/02533839.1996.9677763
出版商: Taylor & Francis Group
关键词: clustering;different density;number of clusters
数据来源: Taylor
摘要:
This paper presents a histogram‐based clustering method that automatically determines the number of clusters in a set of data points. Input data are first partitioned into several rectangular blocks. The number of points in each block is determined, and the thirty percent of the blocks with the most points are marked to obtain a feature. Next, the forty percent of the blocks with the most points are marked to obtain a second feature. These two features are then compared to determine the number of clusters in the input data. The proposed clustering method is fast, and the data to be clustered do not need to be linearly separable. Experimental results are included.
点击下载:
PDF (894KB)
返 回