| 空间数据模糊聚类的有效性(英文) |
| |
| 作者单位： | School of Geodesy and Geomatics，Wuhan University，129 Luoyu Road，Wuhan 430079，China. |
| |
| 摘 要： | 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 uncertainty 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.
|
| 关 键 词： | 空间数据 模糊聚类 有效性 地球科学 |
Fuzzy clustering validity for spatial data |
| |
| Authors: | Chunchun Hu Lingkui Meng Wenzhong Shi |
| |
| Institution: | (1) School of Geodesy and Geomatics, Wuhan University, 129 Luoyu Road, Wuhan, 430079, China |
| |
| 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. |
| |
| Keywords: | fuzzy clustering spatial data validity uncertainty |
| 本文献已被 CNKI 维普 SpringerLink 等数据库收录！ |
|
