Support vector mixture for classification and regression problems
Tin-Yau Kwok, J.
Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on
Volume 1, Issue , 16-20 Aug 1998 Page(s):255 - 258 vol.1
Digital Object Identifier   10.1109/ICPR.1998.711129
Summary:We study the incorporation of the support vector machine (SVM) into the (hierarchical) mixture of experts model to form a support vector mixture. We show that, in both classification and regression problems, the use of a support vector mixture leads to quadratic programming (QP) problems that are very similar to those for a SVM, with no increase in the dimensionality of the QP problems. Moreover, a support vector mixture, besides allowing for the use of different experts in different regions of the input space, also supports easy combination of different architectures such as polynomial networks and radial basis function networks

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