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Granular Sets – Foundations and Case Study of Tolerance Spaces

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Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4482))

Abstract

A novel approach to extend the notions of definability and rough set approximations in information systems with non-equivalence relations is proposed. The upper approximation is defined as set-theoretic complement of negative region of a given concept; therefore, it does not need to be definable. Fundamental properties of new approximation operators are compared with the previous ones reported in literature. The proposed idea is illustrated within tolerance approximation spaces. In particular, granulation based on maximal preclasses is considered.

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Ślȩzak, D., Wasilewski, P. (2007). Granular Sets – Foundations and Case Study of Tolerance Spaces. In: An, A., Stefanowski, J., Ramanna, S., Butz, C.J., Pedrycz, W., Wang, G. (eds) Rough Sets, Fuzzy Sets, Data Mining and Granular Computing. RSFDGrC 2007. Lecture Notes in Computer Science(), vol 4482. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72530-5_52

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  • DOI: https://doi.org/10.1007/978-3-540-72530-5_52

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72529-9

  • Online ISBN: 978-3-540-72530-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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