Abstract
Knowledge reduction and knowledge discovery in information systems are important topics of rough set theory. Based on the relative indiscernibility relation and relative discernibility relation of decision systems, the notions of \(\lambda \) reduction and \(\mu \) reduction are proposed. The judgement theorems for \(\lambda \) consistent set and \(\mu \) consistent set are provided. The discernibility matrices with respect to \(\lambda \) reduction and \(\mu \) reduction are obtained and the reduction approaches are presented. Furthermore, the relationships among \(\lambda \) reduction, \(\mu \) reduction, positive region reduction and assignment reduction are analyzed.
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Acknowledgments
The authors are highly grateful to the anonymous referees for their insightful comments and valuable suggestions which greatly improve the quality of this paper. This work has been partially supported by the National Natural Science Foundation of China (Grant Nos. 61473239, 61372187), and the open research fund of key laboratory of intelligent network information processing, Xihua University (szjj2014-052).
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Qin, K., Jing, S. (2017). The Attribute Reductions Based on Indiscernibility and Discernibility Relations. In: Polkowski, L., et al. Rough Sets. IJCRS 2017. Lecture Notes in Computer Science(), vol 10313. Springer, Cham. https://doi.org/10.1007/978-3-319-60837-2_26
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DOI: https://doi.org/10.1007/978-3-319-60837-2_26
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