{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T06:55:59Z","timestamp":1768892159465,"version":"3.49.0"},"reference-count":26,"publisher":"Hindawi Limited","license":[{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Electrical and Computer Engineering"],"published-print":{"date-parts":[[2015]]},"abstract":"<jats:p>As a machine learning method, AdaBoost is widely applied to data classification and object detection because of its robustness and efficiency. AdaBoost constructs a global and optimal combination of weak classifiers based on a sample reweighting. It is known that this kind of combination improves the classification performance tremendously. As the popularity of AdaBoost increases, many variants have been proposed to improve the performance of AdaBoost. Then, a lot of comparison and review studies for AdaBoost variants have also been published. Some researchers compared different AdaBoost variants by experiments in their own fields, and others reviewed various AdaBoost variants by basically introducing these algorithms. However, there is a lack of mathematical analysis of the generalization abilities for different AdaBoost variants. In this paper, we analyze the generalization abilities of six AdaBoost variants in terms of classification margins. The six compared variants are Real AdaBoost, Gentle AdaBoost, Modest AdaBoost, Parameterized AdaBoost, Margin-pruning Boost, and Penalized AdaBoost. Finally, we use experiments to verify our analyses.<\/jats:p>","DOI":"10.1155\/2015\/835357","type":"journal-article","created":{"date-parts":[[2015,2,10]],"date-time":"2015-02-10T16:10:43Z","timestamp":1423584643000},"page":"1-17","source":"Crossref","is-referenced-by-count":17,"title":["Analysis of Generalization Ability for Different AdaBoost Variants Based on Classification and Regression Trees"],"prefix":"10.1155","volume":"2015","author":[{"given":"Shuqiong","family":"Wu","sequence":"first","affiliation":[{"name":"Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama, Kanagawa 226-8503, Japan"}]},{"given":"Hiroshi","family":"Nagahashi","sequence":"additional","affiliation":[{"name":"Imaging Science and Engineering Laboratory, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama, Kanagawa 226-8503, Japan"}]}],"member":"98","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1109\/lsp.2011.2146772"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1109\/tcsvt.2011.2177192"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1109\/lsp.2012.2210870"},{"issue":"5","key":"6","first-page":"771","volume":"14","year":"1999","journal-title":"Journal of Japanese Society for Artificial Intelligence"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1024691352"},{"issue":"3","key":"8","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1023\/A:1007614523901","volume":"37","year":"1999","journal-title":"Machine Learning"},{"issue":"10","key":"9","first-page":"1747","volume":"45","year":"2012","journal-title":"Journal of University of Electronic Science and Technology of China"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1109\/lsp.2014.2313570"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1016218223"},{"issue":"5","key":"12","first-page":"987","volume":"12","year":"2005","journal-title":"Graphicon"},{"key":"15"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1023\/a:1012470815092"},{"issue":"4","key":"19","first-page":"633","volume":"4","year":"2004","journal-title":"Journal of Machine Learning Research"},{"key":"22","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2007.04.009"},{"key":"31","doi-asserted-by":"publisher","DOI":"10.1109\/tpami.2004.68"},{"key":"33","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007618119488"},{"key":"38"},{"key":"35","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2007.06.019"},{"key":"39","doi-asserted-by":"publisher","DOI":"10.1109\/tpami.2008.235"},{"key":"40","doi-asserted-by":"publisher","DOI":"10.1109\/tpami.2010.92"},{"key":"43","doi-asserted-by":"publisher","DOI":"10.1016\/j.dss.2007.12.002"},{"key":"48","first-page":"70","volume":"47","year":"2008","journal-title":"Proceedings of World Academy of Science: Engineering & Technolog"},{"key":"49","year":"2008"},{"issue":"1","key":"52","first-page":"295","volume":"3","year":"2012","journal-title":"Journal of Information Systems and Communication"},{"issue":"1","key":"53","first-page":"35","volume":"3","year":"2012","journal-title":"Journal of Information Systems and Communication"},{"key":"54","year":"2013"}],"container-title":["Journal of Electrical and Computer Engineering"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/jece\/2015\/835357.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/jece\/2015\/835357.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/jece\/2015\/835357.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,6,23]],"date-time":"2017-06-23T01:17:37Z","timestamp":1498180657000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.hindawi.com\/journals\/jece\/2015\/835357\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015]]},"references-count":26,"alternative-id":["835357","835357"],"URL":"https:\/\/doi.org\/10.1155\/2015\/835357","relation":{},"ISSN":["2090-0147","2090-0155"],"issn-type":[{"value":"2090-0147","type":"print"},{"value":"2090-0155","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015]]}}}