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Using support vector machines for mining regression classes in large data sets

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3 Author(s)
Zonghai Sun ; Nat. Lab. of Ind. Control Technol., Zhejiang Univ., Hangzhou, China ; Lixin Gao ; Youxian Sun

Support vector machines (SVM) overcome the limit of the maximum-likelihood. method that only applies to very limited set of the density functions. They can estimate simultaneously the regression classes in the mixture data set. The validity of the SVM was demonstrated in experiments. The results indicate that the SVM can estimate the regression classes in the mixture data set with noise.

Published in:

TENCON '02. Proceedings. 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering  (Volume:1 )

Date of Conference:

28-31 Oct. 2002