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Title: Fuzzy clustering validity for spatial data
Authors: Hu, C
Meng, L
Shi, W 
Keywords: Fuzzy clustering
Spatial data
Issue Date: 2008
Publisher: Taylor & Francis Asia Pacific (Singapore)
Source: Geo-spatial information science (地球空间信息科学学报), Sept. 2008, v. 11, no. 3, p. 191-196 How to cite?
Journal: Geo-spatial information science (地球空间信息科学学报) 
Abstract: The validity measurement of fuzzy clustering is a key problem. If clustering is formed, it needs a kind of machine to verify its validity. To make mining more accountable, comprehensible and with a usable spatial pattern, it is necessary to first detect whether the data set has a clustered structure or not before clustering. This paper discusses a detection method for clustered patterns and a fuzzy clustering algorithm, and studies the validity function of the result produced by fuzzy clustering based on two aspects, which reflect the un-certainty of classification during fuzzy partition and spatial location features of spatial data, and proposes a new validity function of fuzzy clustering for spatial data. The experimental result indicates that the new validity function can accurately measure the validity of the results of fuzzy clustering. Especially, for the result of fuzzy clustering of spatial data, it is robust and its classification result is better when compared to other indices.
ISSN: 1009-5020
EISSN: 1993-5153
DOI: 10.1007/s11806-008-0094-8
Rights: © 2008 中国学术期刊电子杂志出版社。本内容的使用仅限于教育、科研之目的。
© 2008 China Academic Journal Electronic Publishing House. It is to be used strictly for educational and research use.
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