Please use this identifier to cite or link to this item:
https://doi.org/10.1109/TNN.2004.841785
DC Field | Value | |
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dc.title | An improved conjugate gradient scheme to the solution of least squares SVM | |
dc.contributor.author | Chu, W. | |
dc.contributor.author | Ong, C.J. | |
dc.contributor.author | Keerthi, S.S. | |
dc.date.accessioned | 2014-06-17T06:11:51Z | |
dc.date.available | 2014-06-17T06:11:51Z | |
dc.date.issued | 2005-03 | |
dc.identifier.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 | |
dc.identifier.issn | 10459227 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/59472 | |
dc.description.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. | |
dc.description.uri | http://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/TNN.2004.841785 | |
dc.source | Scopus | |
dc.subject | Conjugate gradient (CG) | |
dc.subject | Least square support vector machines (LS-SVM) | |
dc.subject | Sequential minimal optimization (SMO) | |
dc.type | Article | |
dc.contributor.department | MECHANICAL ENGINEERING | |
dc.description.doi | 10.1109/TNN.2004.841785 | |
dc.description.sourcetitle | IEEE Transactions on Neural Networks | |
dc.description.volume | 16 | |
dc.description.issue | 2 | |
dc.description.page | 498-501 | |
dc.description.coden | ITNNE | |
dc.identifier.isiut | 000227407500021 | |
Appears in Collections: | Staff Publications |
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