期刊文献+
任意字段
题名或关键词
题名
关键词
文摘
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息

聚类组合研究的新进展 被引量：3

Latest development of clustering ensemble
下载PDF
导出
摘要 作为目前聚类分析的新兴研究热点,聚类组合方法能将两种或多种聚类方法集成起来以改善其性能。从聚类多样性和共识函数两方面综述了最新研究进展,探讨将神经网络组合的思想用于聚类组合。最后指出了将来可能的研究方向。 As a novel research hotspot of clustering analysis currently,clustering ensemble can improve the performance of data clustering by combining two or muhiple clustering algorithms.Some latest research results on clustering diversity and consensus function are reviewed,and a clustering ensemble method inspired by neural network ensemble is presented.Finally the future research issues are discussed.
作者 杨燕 靳蕃 KAMEL Mohamed
机构地区 西南交通大学信息科学与技术学院 加拿大滑铁卢大学电子与计算机工程系
出处 《计算机工程与应用》 CSCD 北大核心 2008年第11期142-144,共3页 Computer Engineering and Applications
基金 四川省重大基础研究子项目(the Key Basic Application Foundation of Sichuan Province under Grant No.04JY029-001-4)
关键词 聚类组合 多样性分量 共识函数 神经网络组合 Clustering ensemble diversity component consensus function neural network ensemble
分类号 TP311 [自动化与计算机技术—计算机软件与理论]
  • 相关文献

参考文献25

  • 1Leiseh F.Bagged clustering.Working Papers SFB adaptive information systems and modeling in economics and management science [R]. 1999.
  • 2Dudoit S,Fridlyand J.Bagging to improve the accuracy of a clustering procedure[J].Bioinformatics, 2003,19 ( 9 ) : 1090-1099.
  • 3Fischer B,Buhmann J M.Path-based clustering for grouping of smooth curves and texture segmentation[J].IEEE Trans on Pattern Analysis and Machine Intelligence,2003,25(4):513-518.
  • 4Topchy A,Jain A K,Punch W.Clustering ensembles:models of consensus and weak partitions [J].IEEE Trans on Pattern Analysis and Machine Intelligence, 2005,27( 12 ) : 1866-1881.
  • 5阳琳贇,王文渊.聚类融合方法综述[J].计算机应用研究,2005,22(12):8-10. 被引量：28
  • 6Topehy A,Jain A K,Punch W.Combining multiple weak clusterings[C]//Proc of IEEE Intl Conf on Data Mining,Melbourne,FL, 2003 : 331-338.
  • 7Minaei-bidgoli B,Topchy A,Punch W F.A comparison of resampling methods for clustering ensembles[C]//Proc of Intl Conf on MLMTA' 04,2004: 939-945.
  • 8Strehl A,Ghosh J.CIuster ensembles-a knowledge reuse framework for combining multiple partitions[J].Machine Learning Research, 2002,3 : 583-617.
  • 9Fred A L N,Jain A K.Data clustering using evidence aceumulation[C]//Proc of the 16th ICPR'02, Quebec City, 2002: 276-280.
  • 10Yang Y,Kamel M.An aggregated clustering approach using multiant colonies algorithms[J]. Pattern Recognition, 2006,39 ( 7 ) : 1278-1289.

二级参考文献24

  • 1R O Duda, P E Hart, D G Stork. Pattern Classification (2nd Edition) [M]. New York: Wiley, 2001. 454-458.
  • 2A Strehl, J Ghosh. Cluster Ensembles: A Knowledge Reuse Framework for Combining Multiple Partitions[J]. Journal of Machine Learning Research, 2003, 3(3): 583-617.
  • 3A L Fred. Finding Consistent Clusters in Data Partitions[C]. Proceedings of the 2nd International Workshop on Multiple Classifier Systems, Volume 2096 of Lecture Notes in Computer Science, Springer, 2001. 309-318.
  • 4A Topchy, A K Jain, W Punch. A Mixture Model for Clustering Ensembles [C]. Proceedings of the 4th SIAM International Conference on Data Mining, 2004. 379-390.
  • 5B Minaei-Bidgoli, A Topchy, W F Punch. A Comparison of Resampling Methods for Clustering Ensembles [C]. Intl. Conf. on Machine Learning, Models, Technologies and Applications(MLMTA 2004), 2004. 939-945.
  • 6B Minaei-Bidgoli, A Topch, W F Punch. Ensembles of Partitions via Data Resampling [C]. Proceedings International Conference on Information Technology, Coding and Computing(ITCC 2004),Volume 2, 2004. 188-192.
  • 7S Dudoit, J Fridlyand. Bagging to Improve the Accuracy of a Clustering Procedure [J]. Bioinformatics, 2003, 19(9): 1090-1099.
  • 8B Fischer, J M Buhmann. Path-based Clustering for Grouping of Smooth Curves and Texture Segmentation [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003, 25(4): 513-518.
  • 9A Topchy, A K Jain, W F Punch. Combining Multiple Weak Cluste-rings [C]. Proceedings of the 3rd IEEE International Conference on Data Mining(ICDM03), 2003. 331-338.
  • 10X Z Fern, C E Brodley. Random Projection for High Dimensional Data Clustering: A Cluster Ensemble Approach [C]. Proceedings of the 20th International Conference on Machine Learning, 2003. 186-193.

共引文献27

同被引文献79

  • 1宫改云,高新波,伍忠东.FCM聚类算法中模糊加权指数m的优选方法[J].模糊系统与数学,2005,19(1):143-148. 被引量：81
  • 2阳琳贇,王文渊.聚类融合方法综述[J].计算机应用研究,2005,22(12):8-10. 被引量：28
  • 3张自豪,马方立,裴峥.地空通信干扰信号的K-均值聚类识别[C]//2013年全国无线电应用与管理学术会议,北京:电子工业出版社,2013,11:106-111.
  • 4Jain A K. Data clustering: 50 years beyond K-means [ J ]. Pattern Recognition Letters,2010,31 (8) :651-666.
  • 5Romesburg C. Cluster analysis for researchers [ M ]. [ S. 1. ] : Lalu. tom, 2004.
  • 6Chakrabarti D, Kum~ R, Tomkins A. Evolutionary clustering[ C]// P~c of the 12th ACM S1GKDD International Conference on Know- ledge Discovery and Data Mining. 2006.
  • 7Strehl A, Ghosh J. Cluster ensembles-a knowledge reuse framework for combining partitions [ J ]. Joumal of Machine Learning Re- search ,2002,3( 3 ) :583-617.
  • 8Chi Yun, Song Xiaodan, Zhou Dengyong, et al. On evolutionary spectral clustering[ J]. ACM Trans on Knowledge Discovery from Data, 2009,3(4) : 1701-1730.
  • 9Xu K S, Kliger M, Hero A O. Evolutionary spectral clustering with adaptive torgetting factor[ C ]//Proc of IEEE International Conference oil Acoustics Speech and Signal Processing. 2010:2174- 2177.
  • 10Wang Yi, Liu Shixia, Feng Jianhua, et al. Mining naturally smooth evolution of clusters from dynamic data[ C]//Proc of SIAM Confe- rence on Data Mining. 2007 : 125-134.

引证文献3

计算机工程与应用
2008年 第11期

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部