the research of extracting minimal decision rules from the decision table in rough sets

ISCAS OpenIR

	the research of extracting minimal decision rules from the decision table in rough sets
	Pan Wei; Huang Yijia; Wang Yangsheng; Yang Hongji
	2011
会议名称	2010 International Conference on Frontiers of Manufacturing and Design Science, ICFMD2010
会议录名称	Applied Mechanics and Materials
页码	3948-3953
会议日期	December 11, 2010 - December 12, 2010
会议地点	Chongqing, China
收录类别	EI
ISSN	1660-9336
ISBN	9783037850046
部门归属	(1) Beijing Engineering Research Center of High Reliable Embedded System Capital Normal University 100048 Beijing China; (2) Institute of Automation Chinese Science Academies Beijing 100080 China; (3) Software Technology Research Laboratory De Montfort University Leicester LE1 9BH United Kingdom
摘要	Analyzes the traditional methods of extracting decision rules in Rough Sets, defines the concept of the decision dependability and proposes a novel algorithm of extracting short decision rules. Only the length of decision rules is extended when the current decision rules can't classify all the samples in the decision table. At the same time, three methods are proposed to reduce the computational complexity: 1) defines the concept of bound coefficient, 2) only classify the samples with the same decision values at a time thus averting the time-consuming classification of the equivalence classes with different decision values, 3) defines the Remain set and only classify the samples in the Remain set, so the computational complexity will decrease proportional with the reduction of the samples in the Remain set. Above-mentioned methods can be used directly for incomplete information systems and have great practicability. © (2011) Trans Tech Publications.; Analyzes the traditional methods of extracting decision rules in Rough Sets, defines the concept of the decision dependability and proposes a novel algorithm of extracting short decision rules. Only the length of decision rules is extended when the current decision rules can't classify all the samples in the decision table. At the same time, three methods are proposed to reduce the computational complexity: 1) defines the concept of bound coefficient, 2) only classify the samples with the same decision values at a time thus averting the time-consuming classification of the equivalence classes with different decision values, 3) defines the Remain set and only classify the samples in the Remain set, so the computational complexity will decrease proportional with the reduction of the samples in the Remain set. Above-mentioned methods can be used directly for incomplete information systems and have great practicability. © (2011) Trans Tech Publications.
关键词	Algorithms Computational Complexity Equivalence Classes Manufacture Rough Set Theory
主办者	Control Engineering and Information Science Research Association; Int. Front. Sci. Technol. Res. Assoc.; Trans Tech Publications; Chongqing Xueya Conferences Catering Co.,Ltd; Chongqing University of Technology
语种	英语
内容类型	会议论文
URI标识	http://ir.iscas.ac.cn/handle/311060/16309
专题	中国科学院软件研究所
推荐引用方式 GB/T 7714	Pan Wei,Huang Yijia,Wang Yangsheng,et al. the research of extracting minimal decision rules from the decision table in rough sets[C],2011:3948-3953.