NDLI: A New SVM Multi-Class Classification Method Based on Error-Correcting Code

Content Provider	IEEE Xplore Digital Library
Author	Zelong Wang Fengxia Yan Feng He Jubo Zhu
Copyright Year	2008
Description	Author affiliation: Sch. of Sci., Nat. Univ. of Defense Technol., Changsha, China (Zelong Wang; Fengxia Yan; Jubo Zhu) \|\| Scholl of Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha, China (Feng He)
Abstract	Traditional SVM (support vector machine) multi-class classification methods are mainly based on one-to-one and one-to-multi, which both have disadvantages in applications: slow computational speed and low classification precision. This paper introduces a new method based on error correcting code to reduce the training time and improve the classification precision. In view of the relations among the length, the Hsmming distance and the order of the code and the generalization ability of each SVM, we propose the principles of code table-designing and the center-range method that ascertains the code order to eliminate the problem caused by error correcting code in factual application. Finally the results of experiments of HRRP recognition show this improved method has high computational efficiency and batter generalization ability.
Starting Page	21
Ending Page	24
File Size	214817
Page Count	4
File Format	PDF
ISBN	9780769535081
DOI	10.1109/CIS.2008.66
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-13
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	code table-designing Error-Correcting Code Optimization methods Helium Support vector machines Support vector machine classification Binary codes Computer applications Error correction codes Computational efficiency National security Computational intelligence center-range method
Content Type	Text
Resource Type	Article

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