DocumentCode :
2682520
Title :
Evaluation and Simplification of rules created by 1-v-r Rough SVM multiclassification
Author :
Lingras, Pawan ; Butz, Cory
Author_Institution :
Dept. of Math. & Comput. Sci., Saint Mary´´s Univ., Halifax, NS
fYear :
2006
fDate :
3-6 June 2006
Firstpage :
553
Lastpage :
558
Abstract :
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
Keywords :
pattern classification; rough set theory; support vector machines; classification process; rough SVM multiclassification; rough sets; support vector machine; Computer science; Electronic mail; Kernel; Noise level; Proposals; Rough sets; Set theory; Support vector machine classification; Support vector machines; Testing; Support vector machines; classification; multiclass; rough sets;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Information Processing Society, 2006. NAFIPS 2006. Annual meeting of the North American
Conference_Location :
Montreal, Que.
Print_ISBN :
1-4244-0362-6
Electronic_ISBN :
1-4244-0363-4
Type :
conf
DOI :
10.1109/NAFIPS.2006.365469
Filename :
4216862
Link To Document :
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