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Fast adaboost algorithm based on weight constraints
Yuan S(袁双); Lv CX(吕赐兴)
作者部门信息服务与智能控制技术研究室
会议名称2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)
会议日期June 8-12, 2015
会议地点Shenyang, China
会议录名称2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)
出版者IEEE
出版地Piscataway, NJ, USA
2015
页码825-828
收录类别EI ; CPCI(ISTP)
EI收录号20161402187818
WOS记录号WOS:000380502300157
产权排序1
ISSN号2379-7711
ISBN号978-1-4799-8730-6
关键词Adaboost Weight Constraint Feature Space Weight Update
摘要This paper presents a fast Adaboost algorithm based on weight constraints, which can shorten the training time when dealing with a larger training data set. In the algorithm, the sample feature space is divided into several groups. Considering that the number of groups and sample dimension feature space are closely related, when the feature space dimension exceeds the number set group, the sample according to the set threshold array searches. Meanwhile, considering the sample weights update related to the number of misclassification samples, sample weights update adds to the number of misclassification, limiting its next iteration of the weights, thereby effectively preventing excessive weight adaptation phenomenon. Experiment shows that the algorithm achieves better results on UCI datasets.
语种英语
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文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/17372
专题信息服务与智能控制技术研究室
作者单位1.Dept. of Information Services and Intelligent Control, Shenyang Institute of Automation Chinese Academy of Sciences, Shenyang, China
2.Dept. of Information Services and Intelligent Control, University of Chinese Academy of Sciences, Beijing, China
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GB/T 7714
Yuan S,Lv CX. Fast adaboost algorithm based on weight constraints[C]. Piscataway, NJ, USA:IEEE,2015:825-828.
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