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Title:
the research of extracting minimal decision rules from the decision table in rough sets
Author: Pan Wei ; Huang Yijia ; Wang Yangsheng ; Yang Hongji
Source: Applied Mechanics and Materials
Conference Name: 2010 International Conference on Frontiers of Manufacturing and Design Science, ICFMD2010
Conference Date: December 11, 2010 - December 12, 2010
Issued Date: 2011
Conference Place: Chongqing, China
Keyword: Algorithms ; Computational complexity ; Equivalence classes ; Manufacture ; Rough set theory
Indexed Type: EI
ISSN: 1660-9336
ISBN: 9783037850046
Department: (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
Sponsorship: 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
Abstract: 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.
English Abstract: 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.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/16309
Appears in Collections:软件所图书馆_会议论文

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Recommended Citation:
Pan Wei,Huang Yijia,Wang Yangsheng,et al. the research of extracting minimal decision rules from the decision table in rough sets[C]. 见:2010 International Conference on Frontiers of Manufacturing and Design Science, ICFMD2010. Chongqing, China. December 11, 2010 - December 12, 2010.
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