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Data classification method based on Bayesian intuitionistic fuzzy rough sets
- XUE Zhan-ao, LI Yong-xiang, YAO Shou-qian, JING Meng-meng
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JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE). 2022, 57(5):
1-10.
doi:10.6040/j.issn.1671-9352.4.2021.250
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This paper proposed a Bayesian intuitionistic fuzzy rough set model based on the theory of intuitionistic fuzzy sets and rough sets, Bayesian probability and approximate relations is combined, and conducted research on it. Firstly, on the basis of rough sets, Bayesian probability based on intuitionistic fuzzy rough set is defined, combined with intuitionistic fuzzy approximation relation and fuzzy matrix, the intuitionistic fuzzy equivalence relation is given, and its properties are discussed. Secondly, according to the characteristics of intuitionistic fuzzy sets and cut sets, the equivalence class basis of Bayesian intuitionistic fuzzy rough sets is obtained, and the upper and lower approximation division method are further given, the positive, negative and boundary fields are calculated and the approximate accuracy is calculated. Finally, the effectiveness of the model is analyzed and verified, and the data with fuzzy information can be better classified on the UCI data sets.