Creating an ensemble of diverse support vector machines using adaboost

Authors:
Naiyan Hari Cândido Lima;Adrião Duarte Dória Neto;Jorge Dantas de Melo
Affiliations:
Departament of Computer Engineering and Automation, Universidade Federal do Rio Grande do Norte;Departament of Computer Engineering and Automation, Universidade Federal do Rio Grande do Norte;Departament of Computer Engineering and Automation, Universidade Federal do Rio Grande do Norte
Venue:
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Year:
2009

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Abstract

Support vector machines are one of the most employed methods of pattern classification, and the Adaboost algorithm is an effective way of improving the performance of the weak learners that compose the ensemble. In this article, we propose to create an Adaboost-based ensemble of SVM, by altering the Gaussian width parameter of the RBF-SVM. Using data sets from the UCI repository, we made tests to evaluate the algorithm.