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Applying Rough Sets to Data Tables Containing Missing Values

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Book cover Rough Sets and Intelligent Systems Paradigms (RSEISP 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4585))

Abstract

Rough sets are applied to data tables containing missing values. Discernibility and indiscernibility between a missing value and another value are considered simultaneously. A family of possible equivalence classes is obtained, in which each equivalence class has the possibility that it is an actual one. By using the family of possible equivalence classes, we can derive lower and upper approximations, even if the approximations are not obtained by previous methods.Furthermore, the lower and upper approximations coincide with those obtained from methods of possible worlds.

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Author information

Authors and Affiliations

  1. Faculty of Management and Information Science, Josai International University, 1 Gumyo, Togane, Chiba, 283-8555, Japan

    Michinori Nakata

  2. Department of Mathematics and Computer Aided Sciences, Faculty of Engineering, Kyushu Institute of Technology, Tobata, Kitakyushu, 804-8550, Japan

    Hiroshi Sakai

Authors
  1. Michinori Nakata
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  2. Hiroshi Sakai
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Editor information

Marzena Kryszkiewicz James F. Peters Henryk Rybinski Andrzej Skowron

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© 2007 Springer-Verlag Berlin Heidelberg

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Nakata, M., Sakai, H. (2007). Applying Rough Sets to Data Tables Containing Missing Values. In: Kryszkiewicz, M., Peters, J.F., Rybinski, H., Skowron, A. (eds) Rough Sets and Intelligent Systems Paradigms. RSEISP 2007. Lecture Notes in Computer Science(), vol 4585. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73451-2_20

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  • DOI: https://doi.org/10.1007/978-3-540-73451-2_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73450-5

  • Online ISBN: 978-3-540-73451-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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