{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,5]],"date-time":"2025-10-05T16:56:56Z","timestamp":1759683416699},"reference-count":12,"publisher":"World Scientific Pub Co Pte Ltd","issue":"07","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2015,11]]},"abstract":"<jats:p>In a learning process, features play a fundamental role. In this paper, we propose a Boosting-based feature selection algorithm called BoostFS. It extends AdaBoost which is designed for classification problems to feature selection. BoostFS maintains a distribution over training samples which is initialized from the uniform distribution. In each iteration, a decision stump is trained under the sample distribution and then the sample distribution is adjusted so that it is orthogonal to the classification results of all the generated stumps. Because a decision stump can also be regarded as one selected feature, BoostFS is capable to select a subset of features that are irrelevant to each other as much as possible. Experimental results on synthetic datasets, five UCI datasets and a real malware detection dataset all show that the features selected by BoostFS help to improve learning algorithms in classification problems, especially when the original feature set contains redundant features.<\/jats:p>","DOI":"10.1142\/s0218001415510118","type":"journal-article","created":{"date-parts":[[2015,6,24]],"date-time":"2015-06-24T07:47:48Z","timestamp":1435132068000},"page":"1551011","source":"Crossref","is-referenced-by-count":3,"title":["BoostFS: A Boosting-Based Irrelevant Feature Selection Algorithm"],"prefix":"10.1142","volume":"29","author":[{"given":"Qi-Guang","family":"Miao","sequence":"first","affiliation":[{"name":"School of Computer Science and technology, Xidian University, Xi'an, P. R. China"}]},{"given":"Ying","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Computer Science and technology, Xidian University, Xi'an, P. R. China"}]},{"given":"Jian-Feng","family":"Song","sequence":"additional","affiliation":[{"name":"School of Computer Science and technology, Xidian University, Xi'an, P. R. China"}]},{"given":"Jiachen","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer Science and technology, Xidian University, Xi'an, P. R. China"}]},{"given":"Yining","family":"Quan","sequence":"additional","affiliation":[{"name":"School of Computer Science and technology, Xidian University, Xi'an, P. R. China"}]}],"member":"219","published-online":{"date-parts":[[2015,9,28]]},"reference":[{"key":"rf1","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-012-0487-8"},{"key":"rf3","doi-asserted-by":"publisher","DOI":"10.1007\/s11416-013-0186-3"},{"key":"rf4","doi-asserted-by":"publisher","DOI":"10.4018\/978-1-60566-010-3.ch322"},{"key":"rf7","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1013203451"},{"key":"rf8","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1016218223"},{"key":"rf9","first-page":"1157","volume":"3","author":"Guyon I.","year":"2003","journal-title":"J. Mach. Learn. Res."},{"key":"rf12","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2009.07.010"},{"key":"rf14","doi-asserted-by":"publisher","DOI":"10.1016\/S0004-3702(97)00043-X"},{"key":"rf19","doi-asserted-by":"publisher","DOI":"10.1007\/s11416-006-0027-8"},{"key":"rf20","doi-asserted-by":"publisher","DOI":"10.1007\/11551188_33"},{"key":"rf21","doi-asserted-by":"crossref","DOI":"10.7551\/mitpress\/8291.001.0001","volume-title":"Boosting: Foundations and Algorithms","author":"Schapire R. E.","year":"2012"},{"key":"rf23","doi-asserted-by":"publisher","DOI":"10.1023\/B:VISI.0000013087.49260.fb"}],"container-title":["International Journal of Pattern Recognition and Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218001415510118","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T19:07:14Z","timestamp":1691780834000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218001415510118"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,9,28]]},"references-count":12,"journal-issue":{"issue":"07","published-online":{"date-parts":[[2015,9,28]]},"published-print":{"date-parts":[[2015,11]]}},"alternative-id":["10.1142\/S0218001415510118"],"URL":"https:\/\/doi.org\/10.1142\/s0218001415510118","relation":{},"ISSN":["0218-0014","1793-6381"],"issn-type":[{"value":"0218-0014","type":"print"},{"value":"1793-6381","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,9,28]]}}}