An Improved Conjugate Gradient Scheme to the Solution of Least Squares SVM
W. Chu, C.J. Ong, S. Sathiya Keerthi · IEEE Transactions on Neural Networks · 2005
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.