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A new method for noise data detection based on DBSCAN and SVDD
Hao SX(郝胜轩); Zhou XF(周晓锋); Song H(宋宏)
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784-789
收录类别EI ; CPCI(ISTP)
EI收录号20161402187711
WOS记录号WOS:000380502300149
产权排序1
ISSN号2379-7711
ISBN号978-1-4799-8730-6
关键词Svdd Dbscan Noise Data Detection
摘要To improve the quality of real datasets by remove noise data, a new method for noise data detection based on Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and support vector data description (SVDD) was proposed in this article. Firstly, classical DBSCAN algorithm was used to cluster the data and remove the outliers. Secondly, SVDD was used to train the grouped data according to the cluster result, and gained discriminant model for each group. All these discriminant models were used in whole dataset to classify the data. The point does not belong to any class is identified as noise data and be removed. Experimental studies are done using UCI dataset. It is shown that the method we proposed is considerably efficient.
语种英语
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被引频次:2[WOS]   [WOS记录]     [WOS相关记录]
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/17358
专题数字工厂研究室
作者单位1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
2.University of Chinese Academy of Sciences, Beijing, China
3.Key Laboratory of Network Control System, Chinese Academy of Sciences, Shenyang, China
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Hao SX,Zhou XF,Song H. A new method for noise data detection based on DBSCAN and SVDD[C]. Piscataway, NJ, USA:IEEE,2015:784-789.
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