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Imprecise Categories, Approximations and Rough Sets

  • Chapter
Rough Sets

Part of the book series: Theory and Decision Library ((TDLD,volume 9))

Abstract

Fundamental concepts in the proposed theory of knowledge are classifications and categories. In fact, categories are features (i.e. subsets) of objects which can be worded using knowledge available in a given knowledge base. Certainly some categories can be definable in one knowledge base but undefinable in another one. Thus, if a category is not definable in a given knowledge base, the question arises whether it can be defined “approximately” in the knowledge base. In other words, we want to address here the central point of our approach, the vague categories.

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Authors and Affiliations

  1. Institute of Computer Science, Warsaw University of Technology, Poland

    Zdzisław Pawlak

Authors
  1. Zdzisław Pawlak
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© 1991 Springer Science+Business Media Dordrecht

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Pawlak, Z. (1991). Imprecise Categories, Approximations and Rough Sets. In: Rough Sets. Theory and Decision Library, vol 9. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-3534-4_2

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  • DOI: https://doi.org/10.1007/978-94-011-3534-4_2

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-5564-2

  • Online ISBN: 978-94-011-3534-4

  • eBook Packages: Springer Book Archive

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