On comparing two sequences of numbers and its applications to clustering analysis

Information Sciences

Volumn 179, Issue 8, 2009, Pages 1025-1039

  Campello, R J G B ^a   Hruschka, E R ^a  

^a UNIVERSITY OF SÃO PAULO   (Brazil)

Author keywords

Clustering analysis; Goodman Kruskal index; Kendall's index; Pearson Product Moment index; Sensitivity analysis; Spearman's index

Indexed keywords

APPLICATIONS;

CLUSTERING ANALYSIS; GOODMAN-KRUSKAL INDEX; KENDALL'S INDEX; PEARSON PRODUCT-MOMENT INDEX; SPEARMAN'S INDEX;

SENSITIVITY ANALYSIS;

EID: 59349105139     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2008.11.028     Document Type: Article

References (31)

1. Anderberg M.R. Cluster Analysis for Applications (1973), Academic Press
2. Baldi P., and Brunak S. Bioinformatics: The Machine Learning Approach. second ed. (2001), MIT Press
3. Campello R.J.G.B., and Hruschka E.R. A fully sensitive correlation measure for data mining. WIT Transactions on Information and Communication Technologies 40 (2008) 35-41
4. R.J.G.B. Campello, E.R. Hruschka, V.S. Alves, On the efficiency of evolutionary fuzzy clustering, Journal of Heuristics, in press, doi:10.1007/s10732-007-9059-6.
5. Cao D.N., and Krzysztof J.C. GAKREM: a novel hybrid clustering algorithm. Information Sciences 178 (2008) 4205-4227
6. Casella G., and Berger R.L. Statistical Inference. second ed. (2001), Duxbury Press
7. Cormen T.H., Leiserson C.E., Rivest R.L., and Stein C. Introduction to Algorithms. second ed. (2001), MIT Press
8. Daniels H.E. The relation between measures of correlation in the universe of sample permutations. Biometrika 33 (1944) 129-135
9. Everitt B.S., Landau S., and Leese M. Cluster Analysis. fourth ed. (2001), Arnold
10. Fowlkes E.B., and Mallows C.L. A method for comparing two hierarchical clusterings. Journal of the American Statistical Association 78 (1983) 553-569
11. Goodman L.A., and Kruskal W.H. Measures of association for cross-classifications. Journal of the American Statistical Association 49 (1954) 732-764
12. Goodman L.A., and Kruskal W.H. Measures of Association for Cross Classifications (1979), Springer-Verlag
13. Halkidi M., Batistakis Y., and Vazirgiannis M. On clustering validation techniques. Journal of Intelligent Information Systems 17 (2001) 107-145
14. Hartigan J.A. Clustering Algorithms (1975), John Wiley and Sons
15. Hruschka E.R., Campello R.J.G.B., and de Castro L.N. Evolving clusters in gene-expression data. Information Sciences 176 (2006) 1898-1927
16. E.R. Hruschka, R.J.G.B. Campello, A.A. Freitas, A.C.P.L.F. de Carvalho, A survey of evolutionary algorithms for clustering. IEEE Transactions on Systems, Man and Cybernetics - C, in press.
17. Hruschka E.R., Castro L.N., and Campello R.J.G.B. Clustering gene-expression data: a hybrid approach that iterates between k-means and evolutionary search. In: Grosan C., Abraham A., and Ishibuchi H. (Eds). Hybrid Evolutionary Algorithms (2007), Springer
18. Hubert L., and Arabie P. Comparing partitions. Journal of Classification 2 (1985) 193-218
19. Hubert L., and Schultz J. Quadratic assignment as a general data analysis strategy. British Journal of Mathematical and Statistical Psychology 29 (1976) 190-241
20. Jain A.K., and Dubes R.C. Algorithms for Clustering Data (1988), Prentice Hall
21. Jiang D., Tang C., and Zhang A. Cluster analysis for gene-expression data: a survey. IEEE Transactions Knowledge and Data Engineering 16 (2004) 1370-1386
22. Kaufman L., and Rousseeuw P. Finding Groups in Data (1990), Wiley
23. Kendall M.G., and Gibbons J.D. Rank Correlation Methods (1990), Edward Arnold
24. Kleinberg J., and Tardos E. Algorithm Design (2005), Addison Wesley
25. Knudsen S. A Biologists Guide to Analysis of DNA Microarray Data (2002), Wiley-Liss
26. J.B. MacQueen. Some methods of classification and analysis of multivariate observations, in: Proc. Fifth Berkeley Symp. on Mathematical Statistics and Probability, 1967, pp. 281-297.
27. Milligan G.W., and Cooper M.C. An examination of procedures for determining the number of clusters in a data set. Psychometrika 50 2 (1985) 159-179
28. Pearson K. Mathematical contributions to the theory of evolution. III regression, heredity and panmixia. Philosophical Transactions of the Royal Society of London Series A 187 (1896) 253-318
29. Rand W.M. Objective criteria for the evaluation of clustering methods. Journal of the American Statistical Association (1971) 846-850
30. Stekel D. Microarray Bioinformatics (2003), Cambridge University Press
31. Strickert M., and Seiffert U. Correlation-based data representation. In: Biehl M., Hammer B., Verleysen M., and Villmann T. (Eds). Similarity-based Clustering and its Application to Medicine and Biology (2007), IBFI, Schloss Dagstuhl, Germany