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An efficient clustering method for medical data applications
Li S(李帅); Zhou XF(周晓锋); Shi HB(史海波); Zheng ZY(郑泽宇)
作者部门数字工厂研究室
会议名称2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)
会议日期June 8-12, 2015
会议地点Shenyang, China
会议录名称2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)
出版者IEEE
出版地Piscataway, NJ, USA
2015
页码133-138
收录类别EI ; CPCI(ISTP)
EI收录号20161402187649
WOS记录号WOS:000380502300030
产权排序1
ISSN号2379-7711
ISBN号978-1-4799-8730-6
关键词Fast Search And Find Of Density Peaks Clustering Medical Data Applications
摘要Clustering task is aimed at classifying elements into clusters, which is applied to different fields of the human activity. In this paper, an efficient clustering method by fast search and find of density peaks (FSFDP) is used for medical data applications. Different computing methods of the local density are compared and analyzed. For datasets composed by a small number of points, the local density might be affected by large statistical errors. Kernel local density is more accurate for estimating the density. Experiments were conducted to validate the efficiencies of the clustering method based on different local density for UCI benchmark and real-life datasets. The results show the feasibility and efficiency of the method for medical data clustering analysis.
语种英语
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文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/17352
专题数字工厂研究室
作者单位Shenyang Institute of Automation, Chinese Academy of Sciences, Key Laboratory of Network Control System, Chinese Academy of Sciences, Shenyang, China
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Li S,Zhou XF,Shi HB,et al. An efficient clustering method for medical data applications[C]. Piscataway, NJ, USA:IEEE,2015:133-138.
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