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2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)
This paper presents a part-versus-part decomposition method for massively parallel training of multi-class support vector machines (SVMs). By using this method, a massive multiclass classification problem is decomposed into a number of twoclass subproblems as small as needed. An important advantage of the part-versus-part method over existing popular pairwkeclassification approach is that a large-scale two-class subproblem can be further divided into a number of relatively smaller and balanceddoi:10.1109/ijcnn.2004.1380009 fatcat:g3cns7lvzvf4hfszlh5lk7awhm