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International Conference on Rough Sets and Current Trends in Computing

RSCTC 1998: Rough Sets and Current Trends in Computing pp 373–380Cite as

Some Heuristics for Default Knowledge Discovery

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

Abstract

In this paper discovery of default knowledge as proposed by Mollestad [7], [8], [9], [10] is further investigated. Mollestad’s algorithm, as described in [9], is refined and extended in several ways. In particular, new heuristics guiding the search for default decision rules are proposed and evaluated. The results so far have been encouraging when the (modified) framework is compared to other rough set methods.

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Author information

Authors and Affiliations

  1. Knowledge Systems Group, Dept. of Computer and Information Science, Norwegian University of Science and Technology, N-7034, Trondheim, Norway

    Tor-Kristian Jenssen, Jan Komorowski & Aleksander Øhrn

Authors
  1. Tor-Kristian Jenssen
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  2. Jan Komorowski
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  3. Aleksander Øhrn
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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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Jenssen, TK., Komorowski, J., Øhrn, A. (1998). Some Heuristics for Default Knowledge Discovery. 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_51

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  • DOI: https://doi.org/10.1007/3-540-69115-4_51

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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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