Abstract
We study multigranulation decision-theoretic rough sets in incomplete information systems. Based on Bayesian decision procedure, we propose the notions of weighted mean multigranulation decision-theoretic rough sets, optimistic multigranulation decision-theoretic rough sets, and pessimistic multigranulation decision-theoretic rough sets in an incomplete information system. We investigate the relationships between the proposed multigranulation decision-theoretic rough set models and other related rough set models. We also study some basic properties of these models. We give an example to illustrate the application of the proposed models.
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Acknowledgments
The paper is completed during authors’ visit to University of Regina. Authors sincerely thank their supervisor Professor Yiyu Yao for his valuable suggestions and careful reading. This work is supported by the National Natural Science Foundation of China (No. 61473181), China Postdoctoral Science Foundation funded project (No. 2013M532063), and Shaanxi Province Postdoctoral Science Foundation funded project (The first batch).
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Yang, HL., Guo, ZL. Multigranulation decision-theoretic rough sets in incomplete information systems. Int. J. Mach. Learn. & Cyber. 6, 1005–1018 (2015). https://doi.org/10.1007/s13042-015-0407-9
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DOI: https://doi.org/10.1007/s13042-015-0407-9