计算机技术、生物医学工程 |
|
|
|
|
加权成对约束投影半监督聚类 |
潘俊1,孔繁胜1,王瑞琴2 |
1.浙江大学 计算机科学与技术学院,浙江 杭州 310027; 2.温州大学 物理与电子信息工程学院,浙江 温州 325035 |
|
Semi-supervised clustering with weighted pairwise constraints projection |
PAN Jun1, KONG Fan-sheng1, WANG Rui-qin2 |
1.College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China; 2. College of Physics and Electronic Information Engineering, Wenzhou University, Wenzhou 325035, China |
[1] ZHU Xiaojin. Semisupervised learning literature survey [R].Computer Science TR 1530, USA, University of Wisconsin: Department of Computer Sciences, 2008. [2] 李昆仑,曹铮,曹丽苹等. 半监督聚类的若干新进展[J].模式识别与人工智能, 2009, 22(5):735-742. LI Kunlun, CAO Zheng, Cao Liping, et al. Some developments on semisupervised clustering [J]. Pattern Recognition and Artificial Intelligence, 2009, 22(5): 735-742. [3] WAGSTAFF K, CARDIE C, ROGERS S, et al. Constrained kmeans clustering with background knowledge[C]∥Proceedings of the 18th International Conference on Machine Learning. Williamstown: Morgan Kaufmann Press, 2001: 577-584. [4] LI Zhengguo, LIU Jianzhuang, TANG Xiaoou. Pairwise constraint propagation by semidefinite programming for semisupervised classification [C]∥Proceedings of the 25th International Conference on Machine Learning. New York: ACM Press, 2008: 576-583. [5] XING E P, NG A Y, JORDAN M I, et al. Distance metric learning with application to clustering with sideinformation[C]∥Advances in Neural Information Processing Systems 15. Cambridge: MIT Press, 2003:505-512. [6] 肖宇,于剑. 基于近邻传播算法的半监督聚类[J].软件学报, 2008, 19(11): 2803-2813. XIAO Yu, YU Jian. SemiSupervised Clustering Based on Affinity Propagation [J]. Journal of Software, 2008, 19(11): 2803-2813. [7] QI Guojun, TANG Jinhui, Zha Zhengjun, et al. An efficient sparse metric learning in highdimensional space via 1penalized logdeterminant regularization.[C]∥ Proceedings of the 26th International Conference on Machine Learning. New York: ACM Press, 2009: 841-848. [8] BASU S, BILENKO M, MOONEY R. A probabilistic framework for semisupervised clustering. [C]∥Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Seattle: ACM Press, 2004:59-68. [9] BILENKO M, BASU S, MOONEY R. Integrating constraints and metric learning in semisupervised clustering[C]∥Proceedings of the 21st International Conference on Machine Learning. Banff: ACM Press, 2004: 81-88. [10] BARHILLEL A, HERTZ T, SHENTAL N, et al. Learning distance functions using equivalence relations. [C]∥Proceedings of the 20th International Conference on Machine Learning. Washington: Morgan Kaufmann Publishers, 2003:11-18. [11] TANG Wei, XIONG Hui, ZHONG Shi, et al. Enhancing semisupervised clustering: a feature projection perspective [C]∥Proceedings of the 13th ACM SIGKDD Internal Conference on Knowledge Discovery and Data Mining. New York: ACM Press, 2007:707-716. [12] ZHANG Daoqiang, ZHOU Zhihua, CHEN Songcan. Semisupervised dimensionality reduction [C] ∥Proceedings of the 7th SIAM International Conference on Data Mining. Minneapolis: [s. n.] 2007:629-634. [13] 韦佳,彭宏. 基于局部与全局保持的半监督维数约减方法[J].软件学报, 2008,19(11):51-60. WEI Jia, PENG Hong. A semisupervised dimensionality reduction method based on local and global preserving [J]. Journal of Software, 2008, 19(11): 2833-2842. [14] 朱凤梅,张道强.张量图像上的半监督降维算法[J].模式识别与人工智能,2009,22(4):574-580. ZHU Fengmei, ZHANG Daoqiang. Semisupervised dimensionality reduction algorithm of tensor image [J]. Pattern Recognition and Artificial Intelligence, 2009, 22(4): 574-580. [15] BASU S. Semisupervised clustering: probabilistic models, algorithms and experiments [D]. Austin: University of Texas at Austin, 2005. [16] WAGSTAFF K, CARDIE C. Clustering with instancelevel constraints [C]∥Proceedings of the 17th International Conference on Machine Learning. Stanford: Morgan Kaufmann Publishers, 2000:1103-1110. [17] 邓超,郭茂祖.基于Tritraining和数据剪辑的半监督聚类算法[J] .软件学报, 2008,19(3):663-673. DENG Chao, GUO Maozu. Tritraining and data editing based semisupervised clustering algorithm [J]. Journal of Software, 2008, 19(3): 663-673. [18] BLAKE C, MERZ J. UCI repository of machine learning databases[DB/OL]. [2010-02-26]. http:∥archive.ics.uci.edu/ml/ [19] GEORGHIADES A S, BELHUMEUR P N, KEIEGMAN D J. Fro |
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
|
Shared |
|
|
|
|
|
Discussed |
|
|
|
|