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|Title:||A kernel-ensemble bagging support vector machine||Authors:||Suganthan, P. N.
|Keywords:||DRNTU::Engineering::Electrical and electronic engineering||Issue Date:||2012||Source:||Ye, 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.||Abstract:||This 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.||URI:||https://hdl.handle.net/10356/106266
|DOI:||10.1109/ISDA.2012.6416648||Rights:||© 2012 IEEE||Fulltext Permission:||none||Fulltext Availability:||No Fulltext|
|Appears in Collections:||EEE Conference Papers|
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