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	Membership calculation based on dimension hierarchical division
	Zhou Ping; Wang Jinlei; Chen Xiankai; Zhang Guanjun
	2013
会议名称	2013 2nd International Conference on Sensors, Measurement and lntelligent Materials, ICSMIM 2013
会议地点	Guangzhou, China
英文摘要	Since dataset usually contain noises, it is very helpful to find out and remove the noise in a preprocessing step. Fuzzy membership can measure a samples weight. The weight should be smaller for noise sample but bigger for important sample. Therefore, appropriate sample memberships are vital. The article proposed a novel approach, Membership Calculate based on Hierarchical Division (MCHD), to calculate the membership of training samples. MCHD uses the conception of dimension similarity, which develop a bottom-up clustering technique to calculate the sample membership iteratively. The experiment indicates that MCHD can effectively detect noise and removes them from the dataset. Fuzzy support vector machine based on MCHD outperforms most of approaches published recently and hold the better generalization ability to handle the noise.
收录类别	EI
语种	英语
内容类型	会议论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/5109]
专题	深圳先进技术研究院_数字所
作者单位	2013
推荐引用方式 GB/T 7714	Zhou Ping,Wang Jinlei,Chen Xiankai,et al. Membership calculation based on dimension hierarchical division[C]. 见:2013 2nd International Conference on Sensors, Measurement and lntelligent Materials, ICSMIM 2013. Guangzhou, China.

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