On multigranulation rough sets in incomplete information system
作者： Xibei Yang , Xiaoning Song , Zehua Chen , Jingyu Yang
DOI: 10.1007/S13042-011-0054-8
关键词:
摘要: Multigranulation rough set is a new and interesting topic in the theory of set. In this paper, multigranulation sets approach introduced into incomplete information system. The tolerance relation, similarity relation limited relations are employed to construct optimistic pessimistic sets, respectively. Not only properties about these discussed, but also relationships among models explored. It shown that by theory, based lower approximations fall between approximations, upper approximations. Such results consistent those single-granulation models.
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sci-hub.se 参考文章(33)
Zdzisław Pawlak, Reasoning about Knowledge Springer, Dordrecht. pp. 81- 115 ,(1991) , 10.1007/978-94-011-3534-4_7
Qian, Liang, Yuhua, Jiye, Wei, Pessimistic Rough Decision 浙江海洋学院学报：自然科学版. ,vol. 29, pp. 440- 449 ,(2010)
Jerzy Stefanowski, Alexis Tsoukiàs, On the Extension of Rough Sets under Incomplete Information Lecture Notes in Computer Science. pp. 73- 81 ,(1999) , 10.1007/978-3-540-48061-7_11
Zdzisław Pawlak, Rough Sets: Theoretical Aspects of Reasoning about Data ,(1991)
Weiguo Yi, Mingyu Lu, Zhi Liu, Multi-valued attribute and multi-labeled data decision tree algorithm International Journal of Machine Learning and Cybernetics. ,vol. 2, pp. 67- 74 ,(2011) , 10.1007/S13042-011-0015-2
Xibei Yang, Jun Xie, Xiaoning Song, Jingyu Yang, Credible rules in incomplete decision system based on descriptors Knowledge Based Systems. ,vol. 22, pp. 8- 17 ,(2009) , 10.1016/J.KNOSYS.2008.04.008
Yee Leung, Wei-Zhi Wu, Wen-Xiu Zhang, Knowledge acquisition in incomplete information systems: A rough set approach European Journal of Operational Research. ,vol. 168, pp. 164- 180 ,(2006) , 10.1016/J.EJOR.2004.03.032
XIBEI YANG, DONGJUN YU, JINGYU YANG, XIAONING SONG, DIFFERENCE RELATION-BASED ROUGH SET AND NEGATIVE RULES IN INCOMPLETE INFORMATION SYSTEM International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems. ,vol. 17, pp. 649- 665 ,(2009) , 10.1142/S0218488509006194
Guang-Bin Huang, Dian Hui Wang, Yuan Lan, Extreme learning machines: a survey International Journal of Machine Learning and Cybernetics. ,vol. 2, pp. 107- 122 ,(2011) , 10.1007/S13042-011-0019-Y
Jie Li, Guan Han, Jing Wen, Xinbo Gao, Robust tensor subspace learning for anomaly detection International Journal of Machine Learning and Cybernetics. ,vol. 2, pp. 89- 98 ,(2011) , 10.1007/S13042-011-0017-0