Comparing clusterings in space

ICML 2010 - Proceedings, 27th International Conference on Machine Learning

Volumn , Issue , 2010, Pages 231-238

  Coen, Michael H ^a   Ansari, M Hidayath ^a   Fillmore, Nathanael ^a  

^a UNIVERSITY OF WISCONSIN MADISON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERINGS; COMPARISON TECHNIQUES; DATA SETS; NUMBER OF CLUSTERS; OPTIMIZATION THEORY; PATHOLOGICAL CONDITIONS; SPATIAL LAYOUT;

LEARNING SYSTEMS; SITE SELECTION;

FAILURE ANALYSIS;

EID: 77956554587     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (16)

1. Ba, Khanh Do, Nguyen, Huy L., Nguyen, Huy N., and Rubinfeld, Ronitt. Sublinear time algorithms for earth mover's distance. arXiv abs/0904-0292, 2009.
2. Bae, Eric, Bailey, James, and Dong, Guozhu. Clustering similarity comparison using density profiles. In Proc. of the 19th Australian Joint Conf on Artificial Intelligence, pp. 342-351. Springer LNCS, 2006.
3. Ben-Hur, A., Elisseeff, A., and Guyon, I. A stability based method for discovering structure in clustered data. In Pacific Symp. on Biocomputing, 2002.
4. Coen, Michael H. Self-supervised acquisition of vowels in american english. In AAAI, 2006.
5. Dueck, D. and Frey, B, J. Non-metric affinity propagation for unsupervised image categorization. IEEE ICCV, 0:1-8, 2007.
6. Fowlkes, E.B. and Mallows, C.L. A method for comparing two hierarchical clusterings. Journal of the American Statistical Association, 78:553-569, 1983.
7. Hillier, F.S. and Lieberman, G.J. Introduction to Mathematical Programming. McGraw-Hill, 1995.
8. Hubert, L. and Arabie, P. Comparing partitions. Journal of Classification, 2:193-218, 1985.
9. Levina, E. and Bickel, P. The earth mover's distance is the mallows distance: Some insights from statistics. In ICCV, 2001.
10. Meilǎ, Marina. Comparing clusterings: an axiomatic view. In ICML, 2005.
11. Rachev, S. T. and Ruschendorf, L. Mass Transportation Problems: Volume I: Theory (Probability and its Applications). Springer, 1998.
12. Rand, W. M. Objective criteria for the evaluation of clustering methods. J. Amer. Statist. Assoc., pp. 846-850, 1971.
13. Shirdhonkar, S. and Jacobs, D.W. Approximate earth movers distance in linear time. In CVPR, 2008.
14. van Dongen, S. Performance criteria for graph clustering and markov cluster experiments. Technical report, National Research Institute for Mathematics and Computer Science in the Netherlands, 2000.
15. Zelnik-Manor, L and Perona, P. Self-tuning spectral clustering. In NIPS, 2004.
16. Zhou, D., Li, J., and Zha, H. A new mallows distance based metric for comparing clusterings. In ICML, 2005.