Evaluation and Simplification of rules created by 1-v-r Rough SVM multiclassification
Pawan J. Lingras, Cory J. Butz · 2006
Complexity of rules created by support vector machine (SVM) based multiclassifiers is an important issue in adopting these classifiers. Recently, we have shown how traditional SVMs can be represented using interval or rough sets. We have also extended the rough SVMs to multiclassification using both the 1-v-r and 1-v-1 approaches. In this paper, we describe an algorithmic implementation of the previously proposed mathematical formulation for 1-v-r approach. Analysis of the time requirements shows that the proposed classifier has a competitive linear time requirement. The approach presented here also will also help practitioners simplify the rules used in the classification process