Relation between Significance of Attribute Set and Single Attribute
In the research field of Rough Set, few papers concern the significance of attribute set. However, there is important relation between the significance of single attribute and that of attribute set, which should not be ignored. In this paper, we draw conclusions by case analysis that (1) the attribute set including single attributes with high significance is certainly significant, while, (2)the attribute set which consists of single attributes with low significance possibly has high significance. We validate the conclusions on discernibility matrix and the results demonstrate the contribution of our conclusions.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1073689Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1429
 Pawlak Z. Rough Sets (J). International Journal of Computer and Information Science, 1982, 11:341 .
 Pawlak Z. Rough Sets and Intelligent Data Analysis(J). Information Sciences,2002, 147(1-4): 1-12.hu
 Zdzislaw Pawlak, Andrzej Skowron. Rudiments of rough sets
[J]. Information Sciences, 177(2007) 3-27
 D.Q. Miao a, Y. Zhao b, Y.Y. Yao b, H.X. Li b,c, F.F. Xu a,b. Relative reducts in consistent and inconsistent decision tables of the Pawlak rough set model(J). Information Sciences, 179 (2009) 4140-4150.
 Yiyu Yao, Yan Zhao, Attribute reduction in decision-theoretic rough set models. Information Sciences 178 (2008) 3356-3373
 Zhu Hong. Research of Representation Formula for the Dependence Degree Among Attributes (J). COMPUTER ENGINEERING, 2005, 31(1): 174-175, 211.
 Meng Qingquan, Mei canhua. New dependability of attribute sets (J). JOURANL OF COMPUTER APPLICATIONS, 2007,27(7):1748-1750
 Zhang Wenxiu, Wu Weizhi, Liang Jijie, Li Deyu. Rough set theory and method(M). Bei Jing: Science express.2001:1.
 Jia wei Han, Micheline Kamber, Data Mining Concepts and Techniques, Publishing House of Mechanical Industry,2001.8.
 LEUNG Y, WU W Z, ZHANG W X. Knowledge acquisition in incomplete information systems: a rough set approach (J). European Joumal of Operational Research. 2006, 168(1): 164-180.
 Jiang Yun; Li Zhanhuai; Wang Yong; Zhang Longbo, A Better Classifier Based on Rough Set and Neural Network for Medical Images. Data Mining Workshops, 2006. ICDM Workshops 2006. Page(s):853 - 857.
 A.Skowron. Rough Sets in KDD. Special Invited Speaking, WCC 2000 in Beijing, Aug.2000.