wanghongjun
Research Associate
Supervisor of Master's Candidates
- Master Tutor
- Education Level:PhD graduate
- Degree:Doctor of engineering
- Business Address:犀浦3号教学楼31529
- Professional Title:Research Associate
- Alma Mater:四川大学
- Supervisor of Master's Candidates
- School/Department:计算机与人工智能学院
- Discipline:Electronic Information
Software Engineering
Computer Application Technology
Contact Information
- PostalAddress:
- Email:
- Paper Publications
基于隐含变量的聚类集成模型
- Impact Factor:3.993
- DOI number:10.3724/SP.J.1001.2009.03431
- Affiliation of Author(s):西南交通大学
- Journal:软件学报
- Key Words:聚类集成 隐含变量 聚类集成模型 MCMC(Markov chain Monte Carlo)
- Abstract:聚类集成能成为机器学习活跃的研究热点,是因为聚类集成能够保护私有信息,分布式处理数据和对知识进行重用,此外,噪声和孤立点对结果的影响较小.主要工作包括:第一,分析了把每一个基聚类器看成是原数据的一个属性这种处理方式的优越性发现按此方法建立起来的聚类集成算法就具有良好的扩展性和灵活性;第二,在此基础之上,建立了latent variable cluster ensemble(LVCE)概率模型进行聚类集成,并且给出了LVCE模型的Markov chain Monte Carlo(MCMC)算法.实验结果表明,LVCE模型的MCMC算法能够进行聚类集成并且达到良好的效果.同时可以体现数据聚类的紧密程度.
- Co-author:李志蜀,chengyang,周鹏,周维
- First Author:wanghongjun
- Indexed by:Academic papers
- Document Code:3604839
- Discipline:Engineering
- First-Level Discipline:Computer Science and Technology
- Volume:20
- Issue:4
- Page Number:825-833
- Translation or Not:no
- Date of Publication:2009-04-15