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A multiple kernel framework for inductive semi-supervised SVM learning

✍ Scribed by Xilan Tian; Gilles Gasso; Stéphane Canu


Book ID
113816950
Publisher
Elsevier Science
Year
2012
Tongue
English
Weight
608 KB
Volume
90
Category
Article
ISSN
0925-2312

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As a kernel based method, the performance of least squares support vector machine (LS-SVM) depends on the selection of the kernel as well as the regularization parameter (Duan, Keerthi, & Poo, 2003). Crossvalidation is efficient in selecting a single kernel and the regularization parameter; however,