Working Set Selection Using Functional Gain for LS-SVMDownload PDFOpen Website

Published: 2007, Last Modified: 12 May 2023IEEE Trans. Neural Networks 2007Readers: Everyone
Abstract: para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> The efficiency of sequential minimal optimization (SMO) depends strongly on the working set selection. This letter shows how the improvement of SMO in each iteration, named the functional gain (FG), is used to select the working set for least squares support vector machine (LS-SVM). We prove the convergence of the proposed method and give some theoretical support for its performance. Empirical comparisons demonstrate that our method is superior to the maximum violating pair (MVP) working set selection. </para>
0 Replies

Loading