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题名:
svm based decision analysis and its granular-based solving
作者: Yang Tian ; Lu Xinjie ; Liao Zaifei ; Liu Wei ; Wang Hongan
会议文集: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
会议名称: International Conference on Computational Science and Its Applications, ICCSA 2009
会议日期: 37436
出版日期: 2009
会议地点: Seoul, Korea, Republic of
关键词: Computer science ; Decision making ; Decision theory ; Granular computing
出版地: Germany
ISSN: 3029743
ISBN: 3642024564
部门归属: (1) Graduate University, Chinese Academy of Sciences, Beijing, China; (2) Institute of Software, Chinese Academy of Sciences, Beijing, China; (3) State Key Lab. of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing, China
主办者: University of Perugia; Monash University; University of Calgary; La Trobe University; Soongsil University
英文摘要: This paper proposes an approach to decision analysis for complex industrial process without enough knowledge of input-output model, which is based on the two-class SVM method. It first proposes a SVM Based Decision Analysis Model to improve the accuracy of determinant of whether a decision is acceptable/ unacceptable by verifying the soft margin of a SVM. This makes it only allow misclassification of only one class in a two-class classification. Then a granular-based approach is presented to solving this model. It is proved that this granular approach can reach an upper bound of the original SVM model. An algorithm then is presented to determine whether a decision is acceptable. According to our analysis and experiments, the two types of SVM have better accuracy on judging its target class then traditional SVM, and the granular-based SVM solving can reduce the running time. © 2009 Springer Berlin Heidelberg.
内容类型: 会议论文
URI标识: http://ir.iscas.ac.cn/handle/311060/8408
Appears in Collections:人机交互技术与智能信息处理实验室_会议论文

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Recommended Citation:
Yang Tian,Lu Xinjie,Liao Zaifei,et al. svm based decision analysis and its granular-based solving[C]. 见:International Conference on Computational Science and Its Applications, ICCSA 2009. Seoul, Korea, Republic of. 37436.
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