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《Computer Engineering and Design》 2010-01
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Ensemble clustering method based on Bagging

LI Shan,ZHANG Hua-xiang(School of Information Science and Engineering,Shandong Normal University,Jinan 250014,China)  
A Bagging-based ensemble methods using a new data sampling technology to keep the diversity and correlation of sub-sample is proposed,and then component learner is generated by using an improved K-means algorithm,the different clustering results of dataset is deal with according to mutual information,finally the distance between disputable object and the clustering center is computed and them is put to new clustering.The experiments on UCI machine learning benchmark data sets show that this method better improve the clustering performance.
【Fund】: 山东省中青年科学家科研奖励基金项目(2006BS01020);; 山东省高新技术自主创新工程专项计划基金项目(2007ZZ17);; 山东省自然科学基金项目(Y2007G16);; 山东省科技攻关计划基金项目(2008GG10001015);; 山东省教育厅科技计划基金项目(J07YJ04)
【CateGory Index】: TP18
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