Article ID: | iaor20003793 |
Country: | Netherlands |
Volume: | 12 |
Issue: | 1/2/3 |
Start Page Number: | 53 |
End Page Number: | 79 |
Publication Date: | Jan 1999 |
Journal: | Computational Optimization and Applications |
Authors: | Bennett Kristin P., Bredensteiner Erin J. |
Keywords: | computational analysis, programming: linear |
We examine the problem of how to discriminate between objects of three or more classes. Specifically, we investigate how two-class discrimination methods can be extended to the multiclass case. We show how the linear programming (LP) approaches based on the work of Mangasarian and quadratic programming (QP) approaches based on Vapnik's Support Vector Machine (SVM) can be combined to yield two new approaches to the multiclass problem. In LP multiclass discrimination, a single linear program is used to construct a piecewise-linear classification function. In our proposed multiclass SVM method, a single quadratic program is used to construct a piecewise-nonlinear classification function. Each piece of this function can take the form of a polynomial, a radial basis function, or even a neural network. For the