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In Pursuit of Patterns in Data Reasoning from Data - The Rough Set Way

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Rough Sets and Current Trends in Computing (RSCTC 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2475))

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Abstract

This paper concerns some aspects of rough set based data analysis. In particular rough set look on Bayes’ formula leads to new methodology of reasoning from data and shows interesting relationship between Bayes’ theorem, rough sets and flow graphs. Three methods of flow graphs application in drawing conclusions from data are presented and examined.

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References

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Author information

Authors and Affiliations

  1. Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, ul. Baltycka 5, 44 100, Gliwice, Poland

    Zdzisław Pawlak

Authors
  1. Zdzisław Pawlak
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Editor information

Editors and Affiliations

  1. Penn State Great Valley School of Professional Graduate Studies, 30 East Swedesford Road, Malvern, PA, 19355, USA

    James J. Alpigini

  2. Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB, R3T 5V6, Canada

    James F. Peters

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

    Andrzej Skowron

  4. Department of Systems and Information Engineering, Maebashi Institute of Technology, 460-1 Kamisadori-Cho, Maebashi-City, 371-0816, Japan

    Ning Zhong

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© 2002 Springer-Verlag Berlin Heidelberg

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Pawlak, Z. (2002). In Pursuit of Patterns in Data Reasoning from Data - The Rough Set Way. In: Alpigini, J.J., Peters, J.F., Skowron, A., Zhong, N. (eds) Rough Sets and Current Trends in Computing. RSCTC 2002. Lecture Notes in Computer Science(), vol 2475. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45813-1_1

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  • DOI: https://doi.org/10.1007/3-540-45813-1_1

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44274-5

  • Online ISBN: 978-3-540-45813-5

  • eBook Packages: Springer Book Archive

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