Comparing clusterings-an information based distance

Journal of Multivariate Analysis

Volumn 98, Issue 5, 2007, Pages 873-895

  Meilǎ, Marina ^a  

^a UNIVERSITY OF WASHINGTON   (United States)

Author keywords

Agreement measures; Clustering; Comparing partitions; Information theory; Mutual information; Similarity measures

Indexed keywords

EID: 33947156744     PISSN: 0047259X     EISSN: 10957243     Source Type: Journal    
DOI: 10.1016/j.jmva.2006.11.013     Document Type: Article

References (20)

1. Anderberg M.R. Cluster Analysis for Applications (1973), Academic Press, New York, NY
2. Ben-Hur A., Elisseeff A., and Guyon I. A stability based method for discovering structure in clustered data. Pacific Symposium on Biocomputing (2002) 6-17
3. Cover T.M., and Thomas J.A. Elements of Information Theory (1991), Wiley, New York
4. Fowlkes E.B., and Mallows C.L. A method for comparing two hierarchical clusterings. J. Amer. Statist. Assoc. 78 383 (1983) 553-569
5. Hartigan J.A. Clustering Algorithms (1975), Wiley, New York, NY
6. Hubert L., and Arabie P. Comparing partitions. J. Classification 2 (1985) 193-218
7. Jain A.K., and Dubes R.C. Algorithms for Clustering Data (1988), Prentice-Hall, Englewood Cliffs, NJ
8. Larsen B., and Aone C. Fast and effective text mining using linear time document clustering. Proceedings of the Conference on Knowledge Discovery and Data Mining (1999) 16-22
9. Lloyd S.P. Least squares quantization in PCM. IEEE Trans. Inform. Theory 28 (1982) 129-137
10. MacLachlan G.J., and Bashford K.E. Mixture Models: Inference and Applications to Clustering (1988), Marcel Dekker, NY
11. Meilǎ M. Comparing clusterings-an axiomatic view. In: Wrobel S., and De Raedt L. (Eds). Proceedings of the International Machine Learning Conference (ICML) (2005), ACM Press, New York
12. Meilǎ M., and Heckerman D. An experimental comparison of modelbased clustering methods. Mach. Learning 42 1/2 (2001) 9-29
13. Mirkin B.G. Mathematical Classification and Clustering (1996), Kluwer Academic Press, Dordrecht
14. Mirkin B.G., and Cherny L.B. Measurement of the distance between distinct partitions of a finite set of objects. Automat. Remote Control 31 5 (1970) 786
15. Rand W.M. Objective criteria for the evaluation of clustering methods. J. Amer. Statist. Assoc. 66 (1971) 846-850
16. Rényi A. Probability Theory (1970), North-Holland, Amsterdam
17. Stanley R.P. Enumerative Combinatorics (1997), Cambridge University Press, Cambridge
18. Steinley D.L. Properties of the Hubert-Arabie adjusted Rand index. Psychological Methods 9 3 (2004) 386-396 (simulations of some adjusted indices and of misclassification error)
19. S. van Dongen, Performance criteria for graph clustering and Markov cluster experiments, Technical Report INS-R0012, Centrum voor Wiskunde en Informatica, 2000.
20. Wallace D.L. Comment. J. Amer. Statist. Assoc. 78 383 (1983) 569-576