Rough multi-category decision theoretic framework

  • Authors:

  • Pawan Lingras;Min Chen;Duoqian Miao

  • Affiliations:

  • Department of Mathematics & Computing Science, Saint Mary's University, Halifax, Nova Scotia, Canada;Department of Mathematics & Computing Science, Saint Mary's University, Halifax, Nova Scotia, Canada and School of Electronics and Information Engineering, Tongji University, Shanghai, P.R. China;School of Electronics and Information Engineering, Tongji University, Shanghai, P.R. China

  • Venue:
  • RSKT'08 Proceedings of the 3rd international conference on Rough sets and knowledge technology
  • Year:
  • 2008

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Abstract

Decision theoretic framework has been helpful in providing a better understanding of classification models. In particular, decision theoretic interpretations of different types of the binary rough set classification model have led to the refinement of these models. This study extends the decision theoretic rough set model to supervised and unsupervised multi-category problems. The proposed framework can be used to study the multi-classification and clustering problems within the context of rough set theory.