Incremental updating approximations in confidential dominance relation based rough set

被引:0
作者
Gou G.-L. [1 ,2 ,3 ]
Wang G.-Y. [2 ]
机构
[1] School of Information Science and Technology, Southwest Jiaotong University, Chengdu
[2] Big Data Mining and Applications Center, Chongqing Institute of Green and Intelligent Technology of Chinese Academy of Science, Chongqing
[3] School of Computer Science and Engineering Chongqing University of Technology, Chongqing
来源
Kongzhi yu Juece/Control and Decision | 2016年 / 31卷 / 06期
关键词
Approximations; Confidential dominance relation; Incremental updating; Rough sets;
D O I
10.13195/j.kzyjc.2015.0684
中图分类号
学科分类号
摘要
Confidential dominance relation based rough set is a model of incomplete ordered information processing, computation of approximations of which is a core issue. In real-life applications, the attribute set is dynamically changed. According to the variation of the attribute set, confidential dominance and dominated class are firstly calculated. Then the principles of incremental updating approximations are discussed when some attributes are added or deleted. Furthermore, incremental approaches and algorithms in the confidential dominance relation based on rough set are proposed. Finally, the experiments on UCI datasets developed on Matlab are designed to evaluate the performance of the proposed incremental updating method and non-incremental updating method. The results show that the proposed algorithms are effective and feasible under the variation of the attribute set. © 2016, Editorial Office of Control and Decision. All right reserved.
引用
收藏
页码:1027 / 1031
页数:4
相关论文
共 12 条
[1]  
Pawlak Z., Skowron A., Rudiments of rough sets, Information Sciences, 177, 1, pp. 3-27, (2007)
[2]  
Gou G.L., Wang G.Y., Li J., Et al., Confidential dominance relation based rough approximation model, Control and Decision, 29, 7, pp. 1325-1329, (2014)
[3]  
Wang L., Li T.R., Liu Q., Et al., A matrix-based approach for maintenance of approximation under the variation of object set, J of Computer Research and Development, 50, 9, pp. 1992-2004, (2013)
[4]  
Chan C.C., A rough set approach to attribute generalization in data mining, Information Science, 107, 97, pp. 169-176, (1998)
[5]  
Liu S.H., Sheng Q.J., Shi Z.Z., A new method for fast computing positive region, J of Computer Research and Development, 40, 5, pp. 637-642, (2003)
[6]  
Zheng Z., Wang G., RRIA: A rough set and rule tree-based incremental knowledge acquisition algorithm, Fundamenta Informaticae, 59, 3, pp. 299-313, (2004)
[7]  
Li T., Ruan D., Gerret W., Et al., A rough set based characteristic relation approach for dynamic attribute generalization in data mining, Knowledgebased Systems, 20, 5, pp. 485-494, (2007)
[8]  
Yang X.B., Wu C., Fu F., Updating approximate concept of rough set resulting from inserting or deleting attributes in incomplete information system, J of Jiangsu University of Science and Technology: Natural Science Ed, 19, 6, pp. 65-69, (2005)
[9]  
Li S., Li T., Liu D., Incremental updating approximations in dominance-based rough sets approach under the variation of the attribute set, Knowledge-Based Systems, 40, pp. 17-26, (2013)
[10]  
Shi W.R., Li W.W., Jia X.Y., Improvement of dominance discernibility matrix and incremental computation of core, Application Research of Computers, 25, 7, pp. 2050-2052, (2008)