k-Class Pattern Recognition
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by J. Weston, C. Watkins
http://www.clrc.rhbnc.ac.uk/research/SVM/pub/essan.ps
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Abstract:
Abstract. The solution of binary classification problems using support vector machines (SVMs) is well developed, but multi-class problems with more than two classes have typically been solved by combining independently produced binary classifiers. We propose a formulation of the SVM that enables a multi-class pattern recognition problem to be solved in a single optimisation. We also propose a similar generalization of linear programming machines. We report experiments using bench-mark datasets in which these two methods achieve a reduction in the number of support vectors and kernel calculations needed.
Citations
| 4717 | The Nature of Statistical Learning Theory – Vapnik - 1995 |
| 1031 | Support-vector network – Cortes, Vapnik - 1995 |
| 153 | Extracting support data for a given task – Schölkopf, Burges, et al. - 1995 |
| 53 | Comparison of view-based object recognition algorithms using realistic 3d models – Blanz, Schlkopf, et al. - 1996 |
| 20 | Multicategory discrimination via linear programming. Optimization Methods and SoBware – Bennett, Mangasarian - 1994 |
