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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)
Department数字工厂研究室
Conference Name2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)
Conference DateJune 8-12, 2015
Conference PlaceShenyang, China
Source Publication2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)
PublisherIEEE
Publication PlacePiscataway, NJ, USA
2015
Pages784-789
Indexed ByEI ; CPCI(ISTP)
EI Accession number20161402187711
WOS IDWOS:000380502300149
Contribution Rank1
ISSN2379-7711
ISBN978-1-4799-8730-6
KeywordSvdd Dbscan Noise Data Detection
AbstractTo 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.
Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/17358
Collection数字工厂研究室
Affiliation1.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
Recommended Citation
GB/T 7714
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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