{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T10:41:50Z","timestamp":1740134510827,"version":"3.37.3"},"reference-count":22,"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":[{"name":"National Key Basic Research Program of China","award":["613148","2010ZX03006-002","2011ZX03005-003-03"],"award-info":[{"award-number":["613148","2010ZX03006-002","2011ZX03005-003-03"]}]},{"name":"National Science and Technology Major Project of the Ministry of Science and Technology","award":["613148","2010ZX03006-002","2011ZX03005-003-03"],"award-info":[{"award-number":["613148","2010ZX03006-002","2011ZX03005-003-03"]}]},{"name":"National Science and Technology Major Project of the Ministry of Science and Technology","award":["613148","2010ZX03006-002","2011ZX03005-003-03"],"award-info":[{"award-number":["613148","2010ZX03006-002","2011ZX03005-003-03"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Applied Mathematics"],"published-print":{"date-parts":[[2013]]},"abstract":"<jats:p>Feature selection has proved to be a beneficial tool in learning problems with the main advantages of interpretation and generalization. Most existing feature selection methods do not achieve optimal classification performance, since they neglect the correlations among highly correlated features which all contribute to classification. In this paper, a novel semisupervised feature selection algorithm based on support vector machine (SVM) is proposed, termed SENFS. In order to solve SENFS, an efficient algorithm based on the alternating direction method of multipliers is then developed. One advantage of SENFS is that it encourages highly correlated features to be selected or removed together. Experimental results demonstrate the effectiveness of our feature selection method on simulation data and benchmark data sets.<\/jats:p>","DOI":"10.1155\/2013\/416320","type":"journal-article","created":{"date-parts":[[2013,12,4]],"date-time":"2013-12-04T17:54:43Z","timestamp":1386179683000},"page":"1-11","source":"Crossref","is-referenced-by-count":7,"title":["A Semisupervised Feature Selection with Support Vector Machine"],"prefix":"10.1155","volume":"2013","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4893-7244","authenticated-orcid":true,"given":"Kun","family":"Dai","sequence":"first","affiliation":[{"name":"National Digital Switching System Engineering and Technological Research Center, Zhengzhou 450002, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hong-Yi","family":"Yu","sequence":"additional","affiliation":[{"name":"National Digital Switching System Engineering and Technological Research Center, Zhengzhou 450002, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qing","family":"Li","sequence":"additional","affiliation":[{"name":"National Digital Switching System Engineering and Technological Research Center, Zhengzhou 450002, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2008.03.007"},{"issue":"1","key":"2","first-page":"59","volume":"42","year":"1988","journal-title":"The American Statistician"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1049\/iet-cvi.2009.0121"},{"year":"2006","key":"4"},{"issue":"1","key":"5","doi-asserted-by":"crossref","first-page":"19","DOI":"10.3233\/IDA-2000-4103","volume":"4","year":"2000","journal-title":"Intelligent Data Analysis"},{"year":"2006","key":"7"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-009-5125-7"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2012.03.001"},{"issue":"2","key":"11","first-page":"589","volume":"16","year":"2006","journal-title":"Statistica Sinica"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2005.00503.x"},{"key":"13","first-page":"832","volume":"15","year":"2011","journal-title":"Journal of Machine Learning Research"},{"journal-title":"Proceedings of the 16th International Conference on Machine Learning (ICML '99)","first-page":"200","year":"1999","key":"14"},{"key":"15","first-page":"203","volume":"9","year":"2008","journal-title":"Journal of Machine Learning Research"},{"year":"1995","key":"16"},{"key":"17","first-page":"1687","volume":"7","year":"2006","journal-title":"Journal of Machine Learning Research (JMLR)"},{"key":"18","doi-asserted-by":"publisher","DOI":"10.1007\/BF01580138"},{"key":"19","doi-asserted-by":"publisher","DOI":"10.1137\/090767558"},{"issue":"2","key":"20","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1137\/080725891","volume":"2","year":"2009","journal-title":"SIAM Journal on Imaging Sciences"},{"year":"2003","key":"21"},{"key":"22","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2010.10.021"},{"year":"1993","key":"23"},{"key":"24","doi-asserted-by":"publisher","DOI":"10.1561\/2200000016"}],"container-title":["Journal of Applied Mathematics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/jam\/2013\/416320.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/jam\/2013\/416320.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/jam\/2013\/416320.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,4]],"date-time":"2019-08-04T08:29:51Z","timestamp":1564907391000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.hindawi.com\/journals\/jam\/2013\/416320\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013]]},"references-count":22,"alternative-id":["416320","416320"],"URL":"https:\/\/doi.org\/10.1155\/2013\/416320","relation":{},"ISSN":["1110-757X","1687-0042"],"issn-type":[{"type":"print","value":"1110-757X"},{"type":"electronic","value":"1687-0042"}],"subject":[],"published":{"date-parts":[[2013]]}}}