Ranking and selecting clustering algorithms using a meta-learning approach

Proceedings of the International Joint Conference on Neural Networks

Volumn , Issue , 2008, Pages 3729-3735

  De Souto, Marcilio C P ^a   Prudêncio, Ricardo B C ^b   Soares, Rodrigo G F ^b   De Araujo, Daniel S A ^a   Costa, Ivan G ^c   Ludermir, Teresa B ^b   Schliep, Alexander ^c  

^a FEDERAL UNIVERSITY OF RIO GRANDE DO NORTE   (Brazil)

^b FEDERAL UNIVERSITY OF PERNAMBUCO   (Brazil)

^c MAX PLANCK INSTITUTE FOR MOLECULAR GENETICS   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

DATA REDUCTION; FLOW OF SOLIDS; GENE EXPRESSION; LEARNING ALGORITHMS; LEARNING SYSTEMS; NEURAL NETWORKS; SUPPORT VECTOR MACHINES;

ALGORITHM SELECTIONS; CANCER GENE EXPRESSIONS; CASE STUDIES; EXPERT USERS; LEARNING APPROACHES; MICROARRAY DATA SETS; REGRESSION SUPPORT VECTOR MACHINES;

CLUSTERING ALGORITHMS;

EID: 56349090074     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2008.4634333     Document Type: Conference Paper

References (54)

1. A. Kalousis, J. Gama, and M. Hilario, "On data and algorithms understanding inductive performance," Machine Learning, vol. 54, no. 3, pp. 275-312, 2004.
2. C. Giraud-Carrier, R. Vilalta, and P. Brazdil, "Introduction to the special issue on meta-learning," Machine Learning, vol. 54, no. 3, pp. 187-193, 2004.
3. R. Vilalta and Y. Drissi, "A perspective view and survey of metalearning," Journal of Artificial Intelligence Review, vol. 18, no. 2, pp. 77-95, 2002.
4. R. B. C. Prudêncio and T. B. Ludermir, "Meta-learning approaches to selecting time series models," Neurocomputing, vol. 61, pp. 121-137, 2004.
5. S. Monti, P. Tamayo, J. Mesirov, and T. Golub, "Consensus clustering: a resampling-based method for class discovery and visualization of gene expression microarray data," Machine Learning, vol. 52, pp. 91-118, 2003.
6. J. Quackenbush, "Computational analysis of cDNA microarray data," Nature Reviews, vol. 6, no. 2, pp. 418-428, 2001.
7. D. Slonim, "From patterns to pathways: gene expression data analysis comes of age," Nature Genetics, vol. 32, pp. 502-508, 2002.
8. P. D'haeseleer, "How does gene expression clustering work?" Nat Biotech, vol. 23, no. 12, pp. 1499-1501, Dec. 2005. [Online]. Available: http://dx.doi.org/10.1038/nbt1205-1499
9. R. Engels and C. Theusinger, "Using a data metric for preprocessing advice for data mining applications," in Proceedings of the 13th European Conference on Artificial Intelligence (ECAI-98), H. Prade, Ed. John Wiley & Sons, 1998, pp. 430-434.
10. P. Brazdil, C. Soares, and J. da Costa, "Ranking learning algorithms: Using IBL and meta-learning on accuracy and time results," Machine Learning, vol. 50, no. 3, pp. 251-277, 2003.
11. D. Aha, "Generalizing from case studies: A case study," in Proceedings of the 9th International Workshop on Machine Learning. Morgan Kaufmann, 1992, pp. 1-10.
12. A. Kalousis and M. Hilario, "Representational issues in metalearning," in Proceedings of the 20th International Conferente on Machine Learning, 2003, pp. 313-320.
13. R. B. C. Prudêncio, T. B. Ludermir, and F. A. T. de Carvalho, "A modal symbolic classifier to select time series models," Pattern Recognition Letters, vol. 25, no. 8, pp. 911-921, 2004.
14. R. Leite and P. Brazdil, "Predicting relative performance of classifiers from samples," in Proceedings of the 22nd International Conference on Machine Learning, 2005.
15. A. Kalousis and T. Theoharis, "Noemon: Design, implementation and performance results of an intelligent assistant for classifier selection," Intelligent Data Analysis, vol. 3, no. 5, pp. 319-337, 1999.
16. A. Kalousis and M. Hilario, "Feature selection for meta-learning," Lecture Notes in Computer Science, vol. 2035, pp. 222-233, 2001.
17. C. Koepf, C. C. Taylor, and J. Keller, "Meta-analysis: Data characterisation for classification and regression on a meta-level," in Proceedings of the International Symposium on Data Mining and Statistics, 2000.
18. H. Bensusan and K. Alexandros, "Estimating the predictive accuracy of a classifier," in Proceedings of the 12th European Conference on Machine Learning, 2001, pp. 25-36.
19. B. Pfahringer, H. Bensusan, and C. Giraud-Carrier, "Meta-learning by landmarking various learning algorithms," in Proceedings of the 17th International Conference on Machine Learning, ICML'2000. San Francisco, California: Morgan Kaufmann, 2000, pp. 743-750.
20. G. Tsoumakas, D. Vrakas, N. Bassiliades, and I. Vlahavas, "Lazy adaptive multicriteria planning," in Proceedings of the 16th European Conference on Artificial Intelligence, ECAI04, 2004, pp. 693-697.
21. A. K. Jain and R. C. Dubes, Algorithms for clustering data. Prentice Hall, 1988.
22. R. Xu and D. Wunsch, "Survey of clustering algorithms," IEEE Transactions on Neural Networks, vol. 16, no. 3, pp. 645-678, 2005.
23. L. Ertoz, M. Steinbach, and V. Kumar, "A new shared nearest neighbor clustering algorithm and its applications," in Workshop on Clustering High Dimensional Data and its Applications, 2002, pp. 105-115.
24. J. A. M. Adya, F. Collopy and M. Kennedy, "Automatic identification of time series features for rule-based forecasting." International Journal of Forecasting, vol. 17, no. 2, pp. 143-157, 2001.
25. D. Michie, D. J. Spiegelhalter, and C. C. Taylor, Eds., Machine Learning, Neural and Statistical Classification. Ellis Horwood, 1994.
26. R. A. Johnson and D. W. Wichern, Applied Multivariate Statistical Analysis, fifth edition ed. Prentice Hall, 2002.
27. C.-C. Chang and C.-J. Lin, LIBSVM: a library for support vector machines, 2001, software available at http://www.csie.ntu.edu.tw/ cjlin/libsvm.
28. G. W. Milligan and M. C. Cooper, "A study of standardization of variables in cluster analysis," Journal of Classification, vol. 5, pp. 181-204, 1988.
29. S. Ramaswamy, P. Tamayo, R. Rifkin, S. Mukherjee, C. H. Yeang, M. Angelo, C. Ladd, M. Reich, E. Latulippe, J. P. Mesirov, T. Poggio, W. Gerald, M. Loda, E. S. Lander, and T. R. Golub, "Multiclass cancer diagnosis using tumor gene expression signatures." Proc Natl Acad Sci U S A, vol. 98, no. 26, pp. 15 149-15 154, Dec 2001. [Online]. Available: http://dx.doi.org/10.1073/ pnas.211566398
30. K. Stegmaier, K. N. Ross, S. A. Colavito, S. OMalley, B. R. Stockwell, and T. R. Golub, "Gene expression-based high-throughput screening(ge-hts) and application to leukemia differentiation," Nature Genetics, vol. 36, no. 3, pp. 257-263, 2004.
31. A. A. Alizadeh, M. B. Eisen, R. E. Davis, C. Ma, I. S. Lossos, A. Rosenwald, J. C. Boldrick, H. Sabet, T. Tran, X. Yu, J. I. Powell, L. Yang, G. E. Marti, T. Moore, J. Hudson, L. Lu, D. B. Lewis, R. Tibshirani, G. Sherlock, W. C. Chan, T. C. Greiner, D. D. Weisenburger, J. O. Armitage, R. Warnke, R. Levy, W. Wilson, M. R. Grever, J. C. Byrd, D. Botstein, P. O. Brown, and L. M. Staudt, "Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling," Nature, vol. 403, pp. 503-511, 2000.
32. S. A. Armstrong, J. E. Staunton, L. B. Silverman, R. Pieters, M. L. den Boer, M. D. Minden, S. E. Sallan, E. S. Lander, T. R. Golub, and S. J. Korsmeyer, "Mll translocations specify a distinct gene expression profile that distinguishes a unique leukemia." Nat Genet, vol. 30, no. 1, pp. 41-47, Jan 2002. [Online]. Available: http://dx.doi.org/10.1038/ng765
33. A. Bhattacharjee, W. G. Richards, J. Staunton, C. Li, S. Monti, P. Vasa, C. Ladd, J. Beheshti, R. Bueno, M. Gillette, M. Loda, G. Weber, E. J. Mark, E. S. Lander, W. Wong, B. E. Johnson, T. R. Golub, D. J. Sugarbaker, and M. Meyerson, "Classification of human lung carcinomas by mrna expression profiling reveals distinct adenocarcinoma subclasses." Proc Natl Acad Sci U S A, vol. 98, no. 24, pp. 13 790-13 795, Nov 2001. [Online]. Available: http://dx.doi.org/10.1073/pnas.191502998
34. M. Bittner, P. Meltzer, Y. Chen, Y. Jiang, E. Seftor, M. Hendrix, M. Radmacher, R. Simon, Z. Yakhini, A. Ben-Dor, N. Sampas, E. Dougherty, E. Wang, F. Marincola, C. Gooden, J. Lueders, A. Glatfelter, P. Pollock, J. Carpten, E. Gillanders, D. Leja, K. Dietrich, C. Beaudry, M. Berens, D. Alberts, and V. Sondak, "Molecular classification of cutaneous malignant melanoma by gene expression profiling." Nature, vol. 406, no. 6795, pp. 536-540, Aug 2000. [Online]. Available: http://dx.doi.org/10.1038/35020115
35. M. Bredel, C. Bredel, D. Juric, G. R. Harsh, H. Vogel, L. D. Recht, and B. I. Sikic, "Functional network analysis reveals extended gliomagenesis pathway maps and three novel myc-interacting genes in human gliomas." Cancer Res, vol. 65, no. 19, pp. 8679-8689, Oct 2005. [Online]. Available: http://dx.doi.org/10.1158/0008-5472.CAN05-1204
36. X. Chen, S. T. Cheung, S. So, S. T. Fan, C. Barry, J. Higgins, K.-M. Lai, J. Ji, S. Dudoit, I. O. Ng, M. van de Rijn, D. Botstein, and P. O. Brown, "Gene expression patterns in human liver cancers," Mol. Biol. Cell, vol. 13, no. 6, pp. 1929-1939, 2002. [Online]. Available: http://www.molbiolcell.org/cgi/content/abstract/13/6/1929
37. D. Chowdary, J. Lathrop, J. Skelton, K. Curtin, T. Briggs, Y. Zhang, J. Yu, Y. Wang, and A. Mazumder, "Prognostic gene expression signatures can be measured in tissues collected in rnalater preservative." J Mol Diagn, vol. 8, no. 1, pp. 31-39, Feb 2006.
38. L. Dyrskjt, T. Thykjaer, M. Kruhffer, J. L. Jensen, N. Marcussen, S. Hamilton-Dutoit, H. Wolf, and T. F. Orntoft, "Identifying distinct classes of bladder carcinoma using microarrays." Nat Genet, vol. 33, no. 1, pp. 90-96, Jan 2003. [Online]. Available: http://dx.doi.org/10.1038/ng1061
39. M. E. Garber, O. G. Troyanskaya, K. Schluens, S. Petersen, Z. Thaesler, M. Pacyna-Gengelbach, M. van de Rijn, G. D. Rosen, C. M. Perou, R. I. Whyte, R. B. Altman, P. O. Brown, D. Botstein, and I. Petersen, "Diversity of gene expression in adenocarcinoma of the lung." Proc Natl Acad Sci U S A, vol. 98, no. 24, pp. 13 784-13 789, Nov 2001. [Online]. Available: http://dx.doi.org/10.1073/pnas.241500798
40. T. R. Golub, D. K. Slonim, P. Tamayo, C. Huard, M. Gaasenbeek, J. P. Mesirov, H. Coller, M. L. Loh, J. R. Downing, M. A. Caligiuri, C. D. Bloomfield, and E. S. Lander, "Molecular classification of cancer: class discovery and class prediction by gene expression monitoring." Science, vol. 286, no. 5439, pp. 531-537, Oct 1999.
41. G. J. Gordon, R. V. Jensen, L.-L. Hsiao, S. R. Gullans, J. E. Blumenstock, S. Ramaswamy, W. G. Richards, D. J. Sugarbaker, and R. Bueno, "Translation of microarray data into clinically relevant cancer diagnostic tests using gene expression ratios in lung cancer and mesothelioma." Cancer Res, vol. 62, no. 17, pp. 4963-4967, Sep 2002.
42. J. Khan, J. S. Wei, M. Ringnr, L. H. Saal, M. Ladanyi, F. Westermann, F. Berthold, M. Schwab, C. R. Antonescu, C. Peterson, and P. S. Meltzer, "Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks." Nat Med, vol. 7, no. 6, pp. 673-679, Jun 2001. [Online]. Available: http://dx.doi.org/10.1038/89044
43. P. Laiho, A. Kokko, S. Vanharanta, R. Salovaara, H. Sammalkorpi, H. Jrvinen, J.-P. Mecklin, T. J. Karttunen, K. Tuppurainen, V. Davalos, S. Schwartz, D. Arango, M. J. Mkinen, and L. A. Aaltonen, "Serrated carcinomas form a subclass of colorectal cancer with distinct molecular basis." Oncogene, vol. 26, no. 2, pp. 312-320, Jan 2007. [Online]. Available: http://dx.doi.org/10.1038/sj.onc.1209778
44. J. Lapointe, C. Li, J. P. Higgins, M. van de Rijn, E. Bair, K. Montgomery, M. Ferrari, L. Egevad, W. Rayford, U. Bergerheim, P. Ekman, A. M. DeMarzo, R. Tibshirani, D. Botstein, P. O. Brown, J. D. Brooks, and J. R. Pollack, "Gene expression profiling identifies clinically relevant subtypes of prostate cancer." Proc Natl Acad Sci U S A, vol. 101, no. 3, pp. 811-816, Jan 2004. [Online]. Available: http://dx.doi.org/10.1073/pnas. 0304146101
45. Y. Liang, M. Diehn, N. Watson, A. W. Bollen, K. D. Aldape, M. K. Nicholas, K. R. Lamborn, M. S. Berger, D. Botstein, P. O. Brown, and M. A. Israel, "Gene expression profiling reveals molecularly and clinically distinct subtypes of glioblastoma multiforme." Proc Natl Acad Sci U S A, vol. 102, no. 16, pp. 5814-5819, Apr 2005. [Online]. Available: http://dx.doi.org/10.1073/pnas.0402870102
46. C. L. Nutt, D. R. Mani, R. A. Betensky, P. Tamayo, J. G. Cairncross, C. Ladd, U. Pohl, C. Hartmann, M. E. McLaughlin, T. T. Batchelor, P. M. Black, A. von Deimling, S. L. Pomeroy, T. R. Golub, and D. N. Louis, "Gene expression-based classification of malignant gliomas correlates better with survival than histological classification." Cancer Res, vol. 63, no. 7, pp. 1602-1607, Apr 2003.
47. S. L. Pomeroy, P. Tamayo, M. Gaasenbeek, L. M. Sturla, M. Angelo, M. E. McLaughlin, J. Y. H. Kim, L. C. Goumnerova, P. M. Black, C. Lau, J. C. Allen, D. Zagzag, J. M. Olson, T. Curran, C. Wetmore, J. A. Biegel, T. Poggio, S. Mukherjee, R. Rifkin, A. Califano, G. Stolovitzky, D. N. Louis, J. P. Mesirov, E. S. Lander, and T. R. Golub, "Prediction of central nervous system embryonal tumour outcome based on gene expression." Nature, vol. 415, no. 6870, pp. 436-442, Jan 2002. [Online]. Available: http://dx.doi.org/10. 1038/415436a
48. J. I. Risinger, G. L. Maxwell, G. V. R. Chandramouli, A. Jazaeri, O. Aprelikova, T. Patterson, A. Berchuck, and J. C. Barrett, "Microarray analysis reveals distinct gene expression profiles among different histologic types of endometrial cancer." Cancer Res, vol. 63, no. 1, pp. 6-11, Jan 2003.
49. M. A. Shipp, K. N. Ross, P. Tamayo, A. P. Weng, J. L. Kutok, R. C. T. Aguiar, M. Gaasenbeek, M. Angelo, M. Reich, G. S. Pinkus, T. S. Ray, M. A. Koval, K. W. Last, A. Norton, T. A. Lister, J. Mesirov, D. S. Neuberg, E. S. Lander, J. C. Aster, and T. R. Golub, "Diffuse large b-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning." Nat Med, vol. 8, no. 1, pp. 68-74, Jan 2002. [Online]. Available: http://dx.doi.org/10.1038/nm0102-68
50. D. Singh, P. G. Febbo, K. Ross, D. G. Jackson, J. Manola, C. Ladd, P. Tamayo, A. A. Renshaw, A. V. D'Amico, J. P. Richie, E. S. Lander, M. Loda, P. W. Kantoff, T. R. Golub, and W. R. Sellers, "Gene expression correlates of clinical prostate cancer behavior." Cancer Cell, vol. 1, no. 2, pp. 203-209, Mar 2002.
51. A. I. Su, J. B.Welsh, L. M. Sapinoso, S. G. Kern, P. Dimitrov, H. Lapp, P. G. Schultz, S. M. Powell, C. A. Moskaluk, H. F. Frierson, and G. M. Hampton, "Molecular classification of human carcinomas by use of gene expression signatures." Cancer Res, vol. 61, no. 20, pp. 7388-7393, Oct 2001.
52. S. A. Tomlins, R. Mehra, D. R. Rhodes, X. Cao, L. Wang, S. M. Dhanasekaran, S. Kalyana-Sundaram, J. T. Wei, M. A. Rubin, K. J. Pienta, R. B. Shah, and A. M. Chinnaiyan, "Integrative molecular concept modeling of prostate cancer progression." Nat Genet, vol. 39, no. 1, pp. 41-51, Jan 2007. [Online]. Available: http://dx.doi.org/10.1038/ng1935
53. M. West, C. Blanchette, H. Dressman, E. Huang, S. Ishida, R. Spang, H. Zuzan, J. A. Olson, J. R. Marks, and J. R. Nevins, "Predicting the clinical status of human breast cancer by using gene expression profiles." Proc Natl Acad Sci U S A, vol. 98, no. 20, pp. 11 462-11 467, Sep 2001. [Online]. Available: http://dx.doi.org/10.1073/pnas.201162998
54. E.-J. Yeoh, M. E. Ross, S. A. Shurtleff, W. K. Williams, D. Patel, R. Mahfouz, F. G. Behm, S. C. Raimondi, M. V. Relling, A. Patel, C. Cheng, D. Campana, D. Wilkins, X. Zhou, J. Li, H. Liu, C.-H. Pui, W. E. Evans, C. Naeve, L. Wong, and J. R. Downing, "Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling." Cancer Cell, vol. 1, no. 2, pp. 133-143, Mar 2002.