Attribute Reduction Method Based on Sample Extraction and Priority

[1] Pawlak Z, Rough sets. International Journal of Computer and Information Science, 1982, 11(5), pp. 341–356. PawlakZ Rough sets International Journal of Computer and Information Science 1982 11 5 341 356 10.1007/BF01001956 Search in Google Scholar

[2] Bera, S., Roy, S.K. Fuzzy Rough Soft Set and Its Application to Lattice. Granular Computing, 2020, 5, pp. 217–223. BeraS. RoyS.K. Fuzzy Rough Soft Set and Its Application to Lattice Granular Computing 2020 5 217 223 10.1007/s41066-018-00148-0 Search in Google Scholar

[3] Sun, B., Ma, W., Chen, X. et al. Multigranulation Vague Rough Set over Two Universes and Its Application to Group Decision Making. Soft Computing, 2019, 23, pp. 8927–8956. SunB. MaW. ChenX. Multigranulation Vague Rough Set over Two Universes and Its Application to Group Decision Making Soft Computing 2019 23 8927 8956 10.1007/s00500-018-3494-1 Search in Google Scholar

[4] Chelly Dagdia, Z., Zarges, C., Beck, G. et al. A Scalable and Effective Rough Set Theory-based Approach for Big Data Pre-processing. Knowledge and Information Systems,2020, 62, pp. 3321–3386. Chelly DagdiaZ. ZargesC. BeckG. A Scalable and Effective Rough Set Theory-based Approach for Big Data Pre-processing Knowledge and Information Systems 2020 62 3321 3386 10.1007/s10115-020-01467-y Search in Google Scholar

[5] Wafo Soh, C., Njilla, L.L., Kwiat, K.K. et al. Learning Quasi-identifiers for Privacy-preserving Exchanges: a Rough Set Theory Approach. Granular Computing, 2020, 5, pp. 71–84. Wafo SohC. NjillaL.L. KwiatK.K. Learning Quasi-identifiers for Privacy-preserving Exchanges: a Rough Set Theory Approach Granular Computing 2020 5 71 84 10.1007/s41066-018-0127-0 Search in Google Scholar

[6] Wong S K M, Ziarko W, Optimal decision rules in decision table. Bulletin of Polish Academy of Sciences, 1985, 33(11–12), pp. 693–696. WongS K M ZiarkoW Optimal decision rules in decision table Bulletin of Polish Academy of Sciences 1985 33 11–12 693 696 Search in Google Scholar

[7] Liu W J, Gu Y D, Feng Y B, et al., An improved attribute reduction algorithm of decision table. Pattern Recognition and Artificial Intelligence, 2004, 17(1), pp. 119–123. LiuW J GuY D FengY B An improved attribute reduction algorithm of decision table Pattern Recognition and Artificial Intelligence 2004 17 1 119 123 Search in Google Scholar

[8] Du J L, Chi Z X, Zhai W, An improved algorithm for reduction of knowledge based on significance of attribution. Mini-Micro System, 2003, 24(6), pp. 976–978. DuJ L ChiZ X ZhaiW An improved algorithm for reduction of knowledge based on significance of attribution Mini-Micro System 2003 24 6 976 978 Search in Google Scholar

[9] Li Hua, Research on the Model and Algorithms of Rough Set for Multi-label Data. Ph.D. thesis, Shanxi University, Taiyuan, China, 2017. LiHua Research on the Model and Algorithms of Rough Set for Multi-label Data Ph.D. thesis, Shanxi University Taiyuan, China 2017 Search in Google Scholar

[10] Hart P, The condensed nearest neighbor rule. IEEE Transaction on Information Theory, 1968, 14(5), pp. 515–516. HartP The condensed nearest neighbor rule IEEE Transaction on Information Theory 1968 14 5 515 516 10.1109/TIT.1968.1054155 Search in Google Scholar

[11] Gates G W, The reduced nearest neighbor rule. IEEE Transactions on Information Theory, 1972, 18(3), pp. 431–433 GatesG W The reduced nearest neighbor rule IEEE Transactions on Information Theory 1972 18 3 431 433 10.1109/TIT.1972.1054809 Search in Google Scholar

[12] Brighton H, Mellish C, Advances in instance selection for instance-based learning algorithms. Data Mining and Knowledge Discovery, 2002, 6(2), pp. 153–172. BrightonH MellishC Advances in instance selection for instance-based learning algorithms Data Mining and Knowledge Discovery 2002 6 2 153 172 10.1023/A:1014043630878 Search in Google Scholar

[13] Wang Xizhao, Wang Tingting, Zhai Junhai, An Attribute Reduction Algorithm Based on Instance Selection. Journal of Computer Research and Development, 2012, 49(11), pp. 2305–2310. WangXizhao WangTingting ZhaiJunhai An Attribute Reduction Algorithm Based on Instance Selection Journal of Computer Research and Development 2012 49 11 2305 2310 Search in Google Scholar

[14] JI Su-Qin, SHI Hong-Bo, Lv Ya-Li, An Attribute Reduction Algorithm Based on Granular Computing and Discernibility. Pattern Recognition and Artificial Intelligence, 2015, 28(4), pp. 327–334. JISu-Qin SHIHong-Bo LvYa-Li An Attribute Reduction Algorithm Based on Granular Computing and Discernibility Pattern Recognition and Artificial Intelligence 2015 28 4 327 334 Search in Google Scholar

[15] Yang Yanyan, Rough Set Based Mechanisms and Algorithms for Incremental Attribute Reduction. Ph.D. thesis, North China Electric Power University, Beijing, China, 2017. YangYanyan Rough Set Based Mechanisms and Algorithms for Incremental Attribute Reduction Ph.D. thesis, North China Electric Power University Beijing, China 2017 Search in Google Scholar

[16] Pan Wei. Rough Sets Model with Entropy for Multi-criteria Ordernal Decision System. Ph.D. thesis, University of Electronic Science and Technology of China, Chengdu, China, 2017. PanWei Rough Sets Model with Entropy for Multi-criteria Ordernal Decision System Ph.D. thesis, University of Electronic Science and Technology of China Chengdu, China 2017 Search in Google Scholar

[17] Jin ping, Zong Yu, Jiang He, et al., Muti-space FCM Algorithm. Computer Engineering and Applications, 2007, 43(28), pp. 162–165. Jinping ZongYu JiangHe Muti-space FCM Algorithm Computer Engineering and Applications 2007 43 28 162 165 Search in Google Scholar

[18] Zhang Wenxiu, Wu Weizhi, Liang Jiye, et al., Rough Set Theory and Method. Beijing: Science Press, 2001. ZhangWenxiu WuWeizhi LiangJiye Rough Set Theory and Method Beijing Science Press 2001 Search in Google Scholar