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Approximation Region-Based Decision Tables

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Rough Sets and Current Trends in Computing (RSCTC 1998)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1424))

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Abstract

Approximation region-based decision tables are tabular specifications of three, in general uncertain, decision rules corresponding to rough approximation regions: positive, boundary and negative regions. The focus of the paper is on the extraction of such decision tables from data, their relationship to conjunctive rules and probabilistic assessment of decision confidence. The theoretical framework of the paper is a variable precision model of rough sets.

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References

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Author information

Authors and Affiliations

  1. Computer Science Department, University of Regina, Regina, Saskatchewan, S4S 0A2, Canada

    Wojciech Ziarko

Authors
  1. Wojciech Ziarko
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Editor information

Editors and Affiliations

  1. Institute of Mathematics, Warsaw University of Technology, Pl. Politechniki 1, 00-665, Warszawa, Poland

    Lech Polkowski

  2. Institute of Mathematics, Warsaw University, Banacha 2, 02-097, Warszawa, Poland

    Andrzej Skowron

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© 1998 Springer-Verlag Berlin Heidelberg

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Ziarko, W. (1998). Approximation Region-Based Decision Tables. In: Polkowski, L., Skowron, A. (eds) Rough Sets and Current Trends in Computing. RSCTC 1998. Lecture Notes in Computer Science(), vol 1424. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-69115-4_25

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  • DOI: https://doi.org/10.1007/3-540-69115-4_25

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64655-6

  • Online ISBN: 978-3-540-69115-0

  • eBook Packages: Springer Book Archive

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