Abstract
This paper discusses the problems arising in applications of the unified rough and fuzzy rough set approach to analysis of inconsistent information systems. The unified approach constitutes a parameterized generalization of the variable precision rough set model. It bases on a single notion of parameterized ε-approximation. As a necessary extension, a method suitable for a correct determination of attributes’ significance is proposed. In particular, the notions of positive ε-classification region and ε-approximation quality are considered. A criterion for reduction of condition attributes is given. Furthermore, a generalized definition of the fuzzy extension ω is proposed.
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Mieszkowicz-Rolka, A., Rolka, L. (2007). Determining Significance of Attributes in the Unified Rough Set Approach. 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_8
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DOI: https://doi.org/10.1007/978-3-540-72530-5_8
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