• 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