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学历：博士研究生毕业
学位：工学博士学位
办公地点：犀浦3号教学楼31529
毕业院校：四川大学
学科：电子信息. 软件工程. 计算机应用技术
所在单位：计算机与人工智能学院
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Hybrid Genetic Model for Clustering Ensemble
影响因子：8.139
DOI码：10.1016/j.knosys.2021.107457
所属单位：西南交通大学
发表刊物：Knowledge-Based Systems
刊物所在地：NETHERLANDS
关键字：ClusteringClustering ensembleGenetic algorithmHybrid genetic model
摘要：Clustering ensemble has received considerable research interest and led to a proliferation of studies, since it has great capabilities to combine multiple base clusters to generate a more robust and stable consensus result. Genetic algorithms are optimization methods which can search heuristically by simulating the natural evolution process with highly parallel and adaptive characteristics. However, to our knowledge, there are very few existing methods using a genetic model to solve clustering ensemble problems. In this paper, a novel hybrid genetic model for clustering ensemble (HGMCE) is proposed innovatively, and the corresponding objective function is designed. Each base clustering is regarded as a new attribute of data, and the result of clustering ensemble can be evaluated by the objective function. Then the proposed model can be inferred with the optimization, combination, and transcendence of base clustering results step by step, which makes it possible to maintain the diversity of the population and provides more possibilities to avoid falling into the local optimal solution. Furthermore, an algorithm named HGCEA corresponding to the proposed model is designed to solve the clustering ensemble problem. To evaluate the potential of HGCEA, extensive experiments are carried out on ten real datasets, including comparison with clustering groups and clustering ensemble groups. The results of accuracy and normalized mutual information demonstrate the superiority of the proposed algorithm in integrating effective clustering over the state-of-the-art.
合写作者：YinghuiZhang,PingDenga,TianruiLi
第一作者：Wenlu Yang
论文类型：学术论文
通讯作者：Hongjun Wang
论文编号：20213710877787
学科门类：工学
一级学科：计算机科学与技术
卷号：Volume 231
期号：107457
页面范围：1-12
ISSN号：0950-7051
是否译文：否
发表时间：2021-09-02