Analysis of consensus partition in cluster ensemble

Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004

Volumn , Issue , 2004, Pages 225-232

  Topchy, Alexander P ^a   Law, Martin H C ^a   Jain, Anil K ^a   Fred, Ana L ^b  

^a Michigan State University   (United States)

^b INSTITUTO SUPERIOR TÉCNICO   (Portugal)

Author keywords

[No Author keywords available]

Indexed keywords

CONSENSUS SOLUTIONS; DATA CLUSTERING; PLURALITY VOTING; STOCHASTIC PARTITION GENERATION;

ALGORITHMS; DATA REDUCTION; DATABASE SYSTEMS; INFORMATION RETRIEVAL; LEARNING SYSTEMS; MATHEMATICAL MODELS;

DATA MINING;

EID: 19544373948     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2004.10100     Document Type: Conference Paper

References (15)

1. A. Dembo and O. Zeitouni. Large Deviations Techniques and Applications. Jones and Bartlett Publishers, 1993.
2. M. Demirekler and H. Altincay. Plurality voting based multiple classifier systems: Statistically independent with respect to dependent classifier sets. Pattern Recognition, 35:2365-2379, 2002.
3. S. Dudoit and J. Fridlyand. Bagging to improve the accuracy of a clustering procedure. Bioinformatics, 19(9): 1090-1099, 2003.
4. B. Fischer and J. M. Buhmann. Bagging for path-based clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(11): 1411-1415, 2003.
5. A. Fred. Finding consistent clusters in data partitions. In Multiple Classifier Systems, volume LNCS 2096, pages 309-318. Springer, 2001.
6. A. Fred and A. K. Jain. Data clustering using evidence accumulation. In Proc. of Sixteenth International Conference on Pattern Recognition, pages IV:276-280, 2002.
7. A. Fred and A. K. Jain. Robust data clustering. In Proc. of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pages II-128-133, 2003.
8. A. K. Jain and R. C. Dubes. Algorithms for Clustering Data. Prentice Hall, 1988.
9. G. Karypis and V. Kumar. A fast and high quality multilevel scheme for partitioning irregular graphs. SIAM Journal of Scientific Computing, 20(1):359-392, 1998.
10. X. Lin, S. Yacoub, J. Burns, and S. Simske. Performance analysis of pattern classifier combination by plurality voting. Pattern Recognition Letters, 24(12): 1959-1969, Aug. 2003.
11. M. Meila. Comparing clusterings by the variation of information. In Proc. of Computational Learning Theory, pages 173-187, 2003.
12. J. Munkres. Algorithms for the assignment and transportation problems. J. SIAM, 5:32-38, Mar. 1957.
13. A. Strehl and J. Ghosh. Cluster ensembles - a knowledge reuse framework for combining multiple partitions. Journal of Machine Learning Research, 3:583-617, December 2002.
14. A. Topchy, A. Jain, and W. Punch. A mixture model for clustering ensembles. In Proc. SIAM Data Mining, pages 379-390, 2004.
15. A. Topchy, A. K. Jain, and W. Punch. Combining multiple weak clusterings. In Proc. IEEE International Conference on Data Mining, pages 331-338, 2003.