计算机应用研究2012，Vol.29Issue(11)：4031-4034,4.DOI:10.3969/j.issn.1001-3695.2012.11.007
选择性聚类融合新方法研究
New algorithm for selective clustering ensemble
摘要
Abstract
Traditional selective clustering ensemble doesn' t eliminate the inferior quality' influence and the accuracy of clustering is not high. In order to solve these problem, this paper proposed a new selective clustering ensemble algorithm. He algorithm , used clustering validity evaluation to evaluate all available clustering ensemble partitions and selected the best quality as reference partition. Secondly, it defined selection strategy via the quality and diversity. Lastly, this paper proposed setting weights to ensemble members according to the significance of attribute in tolerance relation theory. The experimental results show that the new algorithm is effective and clustering performance can be significantly improved.关键词
选择性聚类融合/参照成员/选择策略/属性重要性加权Key words
selective clustering ensemble/ reference partition/ selection strategy/ weight of significance of attribute分类
信息技术与安全科学引用本文复制引用
刘丽敏,樊晓平,廖志芳..选择性聚类融合新方法研究[J].计算机应用研究,2012,29(11):4031-4034,4.基金项目
国家科技支撑计划资助项目(2012BAH08B00) （2012BAH08B00）
国家"863"计划资助项目(2007AA022008) （2007AA022008）
