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Various Approaches to Reasoning with Frequency Based Decision Reducts: A Survey

  • Dominik Ślęzak
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 56)

Abstract

Various aspects of reduct approximations are discussed. In particular, we show how to use them to develop flexible tools for analysis of strongly inconsistent and/or noisy data tables. A special attention is paid to the notion of a rough membership decision reduct — a feature subset (almost) preserving the frequency based information about conditions-→decision dependencies. Approximate criteria of preserving such a kind of information under attribute reduction are considered. These criteria are specified by using distances between frequency distributions and information measures related to different ways of interpreting rough membership based knowledge.

Keywords

Decision Rule Decision Table Approximation Threshold Decision Class Information Pattern 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Physica-Verlag Heidelberg 2000

Authors and Affiliations

  • Dominik Ślęzak
    • 1
    • 2
  1. 1.Warsaw UniversityWarsawPoland
  2. 2.Polish-Japanese Institute of Information TechnologyWarsawPoland

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