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|Title:||An improved conjugate gradient scheme to the solution of least squares SVM||Authors:||Chu, W.
|Keywords:||Conjugate gradient (CG)
Least square support vector machines (LS-SVM)
Sequential minimal optimization (SMO)
|Issue Date:||Mar-2005||Citation:||Chu, W., Ong, C.J., Keerthi, S.S. (2005-03). An improved conjugate gradient scheme to the solution of least squares SVM. IEEE Transactions on Neural Networks 16 (2) : 498-501. ScholarBank@NUS Repository. https://doi.org/10.1109/TNN.2004.841785||Abstract:||The least square support vector machines (LS-SVM) formulation corresponds to the solution of a linear system of equations. Several approaches to its numerical solutions have been proposed in the literature. In this letter, we propose an improved method to the numerical solution of LS-SVM and show that the problem can be solved using one reduced system of linear equations. Compared with the existing algorithm for LS-SVM, the approach used in this letter is about twice as efficient. Numerical results using the proposed method are provided for comparisons with other existing algorithms. © 2005 IEEE.||Source Title:||IEEE Transactions on Neural Networks||URI:||http://scholarbank.nus.edu.sg/handle/10635/59472||ISSN:||10459227||DOI:||10.1109/TNN.2004.841785|
|Appears in Collections:||Staff Publications|
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