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 ∈-approximation. As a necessary extension, a method suitable for a correct determination of attributes' significance is proposed. In particular, the notions of positive ∈-classification region and ∈-approximation quality are considered. A criterion for reduction of condition attributes is given. Furthermore, a generalized definition of the fuzzy extension ω is proposed. © Springer-Verlag Berlin Heidelberg 2007.
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CITATION STYLE
Mieszkowicz-Rolka, A., & Rolka, L. (2007). Determining significance of attributes in the unified rough set approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4482 LNAI, pp. 71–78). Springer Verlag. https://doi.org/10.1007/978-3-540-72530-5_8
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