{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T18:27:11Z","timestamp":1761676031297,"version":"3.37.3"},"reference-count":20,"publisher":"Wiley","license":[{"start":{"date-parts":[[2013,1,1]],"date-time":"2013-01-01T00:00:00Z","timestamp":1356998400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51174236"],"award-info":[{"award-number":["51174236"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational Intelligence and Neuroscience"],"published-print":{"date-parts":[[2013]]},"abstract":"<jats:p>Working set selection is a major step in decomposition methods for training least squares support vector machines (LS-SVMs). In this paper, a new technique for the selection of working set in sequential minimal optimization- (SMO-) type decomposition methods is proposed. By the new method, we can select a single direction to achieve the convergence of the optimality condition. A simple asymptotic convergence proof for the new algorithm is given. Experimental comparisons demonstrate that the classification accuracy of the new method is not largely different from the existing methods, but the training speed is faster than existing ones.<\/jats:p>","DOI":"10.1155\/2013\/968438","type":"journal-article","created":{"date-parts":[[2013,2,18]],"date-time":"2013-02-18T23:54:47Z","timestamp":1361231687000},"page":"1-7","source":"Crossref","is-referenced-by-count":8,"title":["Single Directional SMO Algorithm for Least Squares Support Vector Machines"],"prefix":"10.1155","volume":"2013","author":[{"given":"Xigao","family":"Shao","sequence":"first","affiliation":[{"name":"School of Mathematics and Statistics, Central South University, Changsha, Hunan 41007, China"},{"name":"Wengjing College, Yantai University, Yantai, Shandong 264005, China"}]},{"given":"Kun","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, Central South University, Changsha, Hunan 41007, China"}]},{"given":"Bifeng","family":"Liao","sequence":"additional","affiliation":[{"name":"School of Mathematics and Information Science, Yantai University, Yantai, Shandong 264005, China"}]}],"member":"311","reference":[{"issue":"5","key":"1","first-page":"757","volume":"27","year":"2008","journal-title":"Computing and Informatics"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1023\/B:MACH.0000008082.80494.e0"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2005.852239"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2009.02.045"},{"issue":"3","key":"5","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1023\/A:1018628609742","volume":"9","year":"1999","journal-title":"Neural Processing Letters"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2005.844091"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-8655(02)00190-3"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2004.841785"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1162\/089976603762553013"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2007.899715"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2011.03.009"},{"volume-title":"Training of support vector machines using sequential minimal optimization","year":"1999","key":"13"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.1162\/089976601300014493"},{"key":"15","first-page":"1889","volume":"6","year":"2005","journal-title":"Journal of Machine Learning Research"},{"key":"16","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2008.12.014"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2006.889500"},{"key":"18","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2006.875973"},{"key":"19","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2011.06.011"},{"key":"20","doi-asserted-by":"publisher","DOI":"10.1007\/s11063-010-9162-9"},{"key":"22","doi-asserted-by":"publisher","DOI":"10.1145\/1961189.1961199"}],"container-title":["Computational Intelligence and Neuroscience"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2013\/968438.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2013\/968438.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2013\/968438.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,6,21]],"date-time":"2017-06-21T03:44:36Z","timestamp":1498016676000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.hindawi.com\/journals\/cin\/2013\/968438\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013]]},"references-count":20,"alternative-id":["968438","968438"],"URL":"https:\/\/doi.org\/10.1155\/2013\/968438","relation":{},"ISSN":["1687-5265","1687-5273"],"issn-type":[{"type":"print","value":"1687-5265"},{"type":"electronic","value":"1687-5273"}],"subject":[],"published":{"date-parts":[[2013]]}}}