Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/106266
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dc.contributor.authorSuganthan, P. N.en
dc.contributor.authorYe, Renen
dc.date.accessioned2013-10-18T07:06:33Zen
dc.date.accessioned2019-12-06T22:07:42Z-
dc.date.available2013-10-18T07:06:33Zen
dc.date.available2019-12-06T22:07:42Z-
dc.date.copyright2012en
dc.date.issued2012en
dc.identifier.citationYe, R., & Suganthan, P.N. (2012). A kernel-ensemble bagging support vector machine. 2012 12th International Conference on Intelligent Systems Design and Applications (ISDA), pp.847-852.en
dc.identifier.urihttps://hdl.handle.net/10356/106266-
dc.description.abstractThis paper proposes a kernel-ensemble bagging SVM classifier for binary class classification. The classifier is advantageous over bagging SVM classifiers because it has a two-phase grid search module, a proposed parameter randomization module and a proposed ranking module. The novel modules enhance the diversity thus improve the performance of the proposed SVM classifier. Six UCI datasets are used to evaluate the proposed kernel-ensemble bagging SVM. The result show that the proposed SVM classifier outperforms the single kernel bagging SVM classifiers.en
dc.language.isoenen
dc.rights© 2012 IEEEen
dc.subjectDRNTU::Engineering::Electrical and electronic engineeringen
dc.titleA kernel-ensemble bagging support vector machineen
dc.typeConference Paperen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen
dc.contributor.conferenceInternational Conference on Intelligent Systems Design and Applications (12th : 2012 : Kochi, India)en
dc.identifier.doi10.1109/ISDA.2012.6416648en
item.fulltextNo Fulltext-
item.grantfulltextnone-
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