Literature DB >> 15787157

An improved conjugate gradient scheme to the solution of least squares SVM.

Wei Chu, Chong Jin Ong, S Sathiya Keerthi.   

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.

Mesh:

Year:  2005        PMID: 15787157     DOI: 10.1109/TNN.2004.841785

Source DB:  PubMed          Journal:  IEEE Trans Neural Netw        ISSN: 1045-9227


  3 in total

1.  Single directional SMO algorithm for least squares support vector machines.

Authors:  Xigao Shao; Kun Wu; Bifeng Liao
Journal:  Comput Intell Neurosci       Date:  2013-02-18

2.  An Automated and Intelligent Medical Decision Support System for Brain MRI Scans Classification.

Authors:  Muhammad Faisal Siddiqui; Ahmed Wasif Reza; Jeevan Kanesan
Journal:  PLoS One       Date:  2015-08-17       Impact factor: 3.240

3.  Predicting multi-class responses to preoperative chemoradiotherapy in rectal cancer patients.

Authors:  Jungsoo Gim; Yong Beom Cho; Hye Kyung Hong; Hee Cheol Kim; Seong Hyeon Yun; Hong-Gyun Wu; Seung-Yong Jeong; Je-Gun Joung; Taesung Park; Woong-Yang Park; Woo Yong Lee
Journal:  Radiat Oncol       Date:  2016-03-22       Impact factor: 3.481

  3 in total

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