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Generalizing Rough Set Theory Through Dominance-Based Rough Set Approach

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Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC 2005)

Abstract

Ordinal properties of data related to preferences have been taken into account in the Dominance-based Rough Set Approach (DRSA). We show that DRSA is also relevant in case where preferences are not considered but a kind of monotonicity relating attribute values is meaningful for the analysis of data at hand. In general terms, monotonicity concerns relationship between different aspects of a phenomenon described by data: for example, “the larger the house, the higher its price” or “the closer the house to the city centre, the higher its price”. In this perspective, the DRSA gives a very general framework in which the classical rough set approach based on indiscernibility relation can be considered as a special case.

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© 2005 Springer-Verlag Berlin Heidelberg

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Greco, S., Matarazzo, B., Słowiński, R. (2005). Generalizing Rough Set Theory Through Dominance-Based Rough Set Approach. In: Ślęzak, D., Yao, J., Peters, J.F., Ziarko, W., Hu, X. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2005. Lecture Notes in Computer Science(), vol 3642. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11548706_1

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  • DOI: https://doi.org/10.1007/11548706_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28660-8

  • Online ISBN: 978-3-540-31824-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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