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An Efficient Algorithm for Inference in Rough Set Flow Graphs

  • Conference paper

Part of the Lecture Notes in Computer Science book series (TRS,volume 4100)

Abstract

Pawlak recently introduced rough set flow graphs (RSFGs) as a graphical framework for reasoning from data. No study, however, has yet investigated the complexity of the accompanying inference algorithm, nor the complexity of inference in RSFGs. In this paper, we show that the traditional RSFG inference algorithm has exponential time complexity. We then propose a new RSFG inference algorithm that exploits the factorization in a RSFG. We prove its correctness and establish its polynomial time complexity. In addition, we show that our inference algorithm never does more work than the traditional algorithm. Our discussion also reveals that, unlike traditional rough set research, RSFGs make implicit independency assumptions regarding the problem domain.

Keywords

  • Reasoning under uncertainty
  • rough set flow graphs

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© 2006 Springer-Verlag Berlin Heidelberg

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Butz, C.J., Yan, W., Yang, B. (2006). An Efficient Algorithm for Inference in Rough Set Flow Graphs. In: Peters, J.F., Skowron, A. (eds) Transactions on Rough Sets V. Lecture Notes in Computer Science, vol 4100. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11847465_5

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  • DOI: https://doi.org/10.1007/11847465_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-39382-5

  • Online ISBN: 978-3-540-39383-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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