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International Joint Conference on Rough Sets

IJCRS 2017: Rough Sets pp 43–55Cite as

Certainty-Based Rough Sets

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10314))

Abstract

The departing point of this study is a data table with certainty values associated to attribute values. These values are deeply rooted in possibility theory, they can be obtained with standard procedures and they are efficiently manageable in databases. Our aim is to study rough set approximations and reducts in this framework. We define three categories of approximations that make use of the certainty value and generalize different aspects of the approximations: their equation, the binary relation used and the granulation. Further, new kinds of reducts aimed to make use or reduce the information provided by the certainty values are given.

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Notes

  1. 1.

    Let us remark that we are not using the term information system on purpose, since outside the rough-set community it has a different and broader meaning, as discussed in [2].

  2. 2.

    By \(C_A(x)\) we mean an overall confidence of x based on attributes \(A\subseteq Att\), it is not specified here how to compute this value.

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Author information

Authors and Affiliations

  1. Department of Informatics, Systems and Communication (DISCo), University of Milano–Bicocca, Milano, Italy

    Davide Ciucci & Ivan Forcati

Authors
  1. Davide Ciucci
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  2. Ivan Forcati
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Corresponding author

Correspondence to Davide Ciucci .

Editor information

Editors and Affiliations

  1. Polish-Japanese Academy of Information Technology, Warsaw, Poland

    Lech Polkowski

  2. University of Regina, Regina, Saskatchewan, Canada

    Yiyu Yao

  3. University of Warmia and Mazury, Olsztyn, Poland

    Piotr Artiemjew

  4. University of Milano-Bicocca, Milano, Italy

    Davide Ciucci

  5. Southwest Jiaotong University, Chengdu, China

    Dun Liu

  6. Warsaw University, Warszawa, Poland

    Dominik Ślęzak

  7. Silesian University, Sosnowiec, Poland

    Beata Zielosko

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Ciucci, D., Forcati, I. (2017). Certainty-Based Rough Sets. In: Polkowski, L., et al. Rough Sets. IJCRS 2017. Lecture Notes in Computer Science(), vol 10314. Springer, Cham. https://doi.org/10.1007/978-3-319-60840-2_3

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  • DOI: https://doi.org/10.1007/978-3-319-60840-2_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60839-6

  • Online ISBN: 978-3-319-60840-2

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