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  2014, Vol. 27 Issue (9): 847-855    DOI:
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Research on Selective Clustering Ensemble Algorithm Based onNormalized Mutual Information and Fractal Dimension
WU Xiao-Xuan, NI Zhi-Wei, NI Li-Ping, ZHANG Chen
1.School of Management, Hefei University of Technology, Hefei 230009
2.Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei 230009

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Abstract  Traditional clustering ensemble algorithm can not eliminate the influence of inferior quality clustering members and is also characterized with lower clustering accuracy. To solve the problems, a selective clustering ensemble algorithm based on fractal dimension is proposed. Firstly, the proposed algorithm is used to realize incremental clustering and can find arbitrary shape clustering. Then, according to the selection strategy of weight values based on normalized mutual information, the proposed algorithm selects high quality clustering members to realize integration by using weighted co-association matrix and get the final clustering results. The experimental results show that compared to the traditional clustering ensemble algorithm, the proposed algorithm improves the clustering quality and has good extensibility.
Key wordsSelective Clustering Ensemble, Fractal Dimension, Normalized Mutual Information      Selection Strategy, Co-association matrix     
Received: 11 July 2013     
ZTFLH: TP311.13  
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WU Xiao-Xuan
NI Zhi-Wei
NI Li-Ping
ZHANG Chen
Cite this article:   
WU Xiao-Xuan,NI Zhi-Wei,NI Li-Ping等. Research on Selective Clustering Ensemble Algorithm Based onNormalized Mutual Information and Fractal Dimension[J]. , 2014, 27(9): 847-855.
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http://manu46.magtech.com.cn/Jweb_prai/EN/      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2014/V27/I9/847
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