DocumentCode :
510026
Title :
A Novel Solution Scheme for the Kernel MSE Model
Author :
Wang Jinghua
Author_Institution :
Shenzhen Grad. Sch., Univ. Town of Shenzhen, Shenzhen, China
Volume :
2
fYear :
2009
fDate :
7-8 Nov. 2009
Firstpage :
375
Lastpage :
378
Abstract :
In this paper we first show that the minimum squared-error solutions of kernel minimum squared-error (KMSE) models are neither unique nor numerically stable. We then propose a novel scheme for KMSE. This solution scheme can produce the unique solution and the maximum between-class margin. This solution has a highly accurate classification rate. The experimental result illustrates the feasibility and effectiveness of MNMSE solution of KMSE.
Keywords :
least mean squares methods; kernel minimum squared-error model; minimum squared-error solution; Artificial intelligence; Cities and towns; Computational complexity; Computational intelligence; Equations; Kernel; Pattern recognition; Transforms; Kernel minimum squared error; Modelling; Pattern Recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3835-8
Electronic_ISBN :
978-0-7695-3816-7
Type :
conf
DOI :
10.1109/AICI.2009.302
Filename :
5375805
Link To Document :
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