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题名: Classification rule mining based on ant colony optimization algorithm
作者: Jin P(金鹏) ; Zhu YL(朱云龙) ; Hu KY(胡琨元) ; Li SF(李素粉)
作者部门: 先进制造技术实验室
会议名称: International Conference on Intelligent Computing (ICIC)
会议日期: August 16-19, 2006
会议地点: Kunming, China
会议主办者: IEEE Computat Intelligence Soc, Int Neural Network Soc, Natl Sci Fdn China
会议录: INTELLIGENT CONTROL AND AUTOMATION
会议录出版者: SPRINGER-VERLAG
会议录出版地: BERLIN
出版日期: 2006
页码: 654-663
收录类别: SCI ; CPCI(ISTP)
ISSN号: 0170-8643
ISBN号: 3-540-37255-5
摘要: Classification rule mining is an important function of data mining, and is applied in many data analysis tasks. The classification rule mining algorithm based-on ant colony optimization (ACO) is researched in this paper. Some improvements are implemented based on existing research to enhance classification predictive accuracy and simplicity of rules. Multi-population parallel strategy is proposed, the cost-based discretization method is adopted, and parameters in the algorithm are adjusted step by step. With these improvements, performance of the algorithm is advanced, and classification predictive accuracy is enhanced. Finally, SIMiner, a self-development data mining software system based on swarm intelligence, is applied to experiment on six data sets taken from UCI Repository on Machine Learning. The results illuminate the algorithm proposed in this paper has better performance in predictive accuracy and simplicity of rules.
语种: 英语
产权排序: 1
WOS记录号: WOS:000240383400082
Citation statistics:
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/8164
Appears in Collections:工业信息学研究室_先进制造技术研究室_会议论文

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Recommended Citation:
金鹏; 朱云龙; 胡琨元; 李素粉.Classification rule mining based on ant colony optimization algorithm.见:SPRINGER-VERLAG.INTELLIGENT CONTROL AND AUTOMATION,BERLIN,2006,654-663
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