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| the research of extracting minimal decision rules from the decision table in rough sets | |
| Pan Wei; Huang Yijia; Wang Yangsheng; Yang Hongji | |
| 2011 | |
| Conference Name | 2010 International Conference on Frontiers of Manufacturing and Design Science, ICFMD2010 |
| Source | Applied Mechanics and Materials |
| Pages | 3948-3953 |
| Conference Date | December 11, 2010 - December 12, 2010 |
| Conference Place | Chongqing, China |
| 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 |
| 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.; 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. |
| Keyword | Algorithms Computational Complexity Equivalence Classes Manufacture Rough Set Theory |
| 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 |
| Language | 英语 |
| Content Type | 会议论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/16309 |
| Collection | 中国科学院软件研究所 |
| Recommended Citation 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. |
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