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https://doi.org/10.1109/TNN.2004.841785
| Title: | An improved conjugate gradient scheme to the solution of least squares SVM | Authors: | Chu, W. Ong, C.J. Keerthi, S.S. |
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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