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Title: A kernel-ensemble bagging support vector machine
Authors: Suganthan, P. N.
Ye, Ren
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.
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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