Self-organizing map based on hausdorff distance for interval-valued data

Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics

Volumn , Issue , 2011, Pages 1747-1752

  Hajjar, Chantal ^a,b   Hamdan, Hani ^a  

^a SUPELEC   (France)

^b LEBANESE UNIVERSITY   (Lebanon)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING METHODS; HAUSDORFF DISTANCE; INTERVAL DATA; INTERVAL-VALUED DATA; METEOROLOGICAL STATION; REAL INTERVALS; SELF ORGANIZING;

CONFORMAL MAPPING; CYBERNETICS; GEOMETRY;

SELF ORGANIZING MAPS;

EID: 83755186798     PISSN: 1062922X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICSMC.2011.6083924     Document Type: Conference Paper

References (21)

1. P. Cazes, A. Chouakria, E. Diday, and Y. Schektman, "Extension de l'analyse en composantes principales à des données de type intervalle,"Revue de Statistique Appliquée, vol. XIV, no. 3, pp. 5-24, 1997.
2. A. Chouakria, "Extension des méthodes d'analyse factorielle à des données de type intervalle," Ph.D. dissertation, Université Paris 9 Dauphine, 1998.
3. L. Billard and E. Diday, "Regression analysis for interval-valued data," in Data Analysis, Classification, and Related Methods, Proc. IFCS'2000, Namur, Belgium, H. Kiers, P. Groenen, J.-P. Rasson, and S. M., Eds. Springer Verlag, 11-14 July 2000.
4. F. Rossi and B. Conan-Guez, "Multi-layer perceptron on interval data," in Classification, Clustering, and Data Analysis, K. Jajuga, A. Sokolowski, and H. H. Bock, Eds. Berlin, Germany: Springer, 2002, pp. 427-436.
5. M. Chavent and Y. Lechevallier, "Dynamical clustering of interval data: Optimization of an adequacy criterion based on hausdorff distance," in Classification, Clustering and Data Analysis, K. Jajuga, A. Sokolowski, and H. H. Bock, Eds. Berlin, Germany: Springer, 2002, pp. 53-60,
6. also in the proceedings of IFCS2002, Poland.
7. M. Barnsley, Fractals Everywhere, Second Edition. Academic Press, 1993.
8. M. Chavent, "Analyse des données symboliques. une méthode divisive de classification," Ph.D. dissertation, Université de PARIS-IX Dauphine, 1997.
9. H. H. Bock, "Clustering methods and Kohonen maps for symbolic data,"Journal of the Japanese Society of Computational Statistics, vol. 15, no. 2, pp. 217-229, 2003.
10. ème Journées de Statistique, SFdS, Lyon, France, 2-6 juin 2003, pp. 549-552.
11. -, "Modélisation et classification de données imprécises," in CIMNA'03, premier congrès international sur les modélisations numériques appliquées, Beyrouth, Liban, 14-15 novembre 2003, pp. 16-19.
12. -, "Mixture model clustering of uncertain data," in IEEE International Conference on Fuzzy Systems, Reno, Nevada, USA, 22-25 may 2005, pp. 879-884.
13. -, "CEM algorithm for imprecise data. Application to flaw diagnosis using acoustic emission," in IEEE International Conference on Systems, Man and Cybernetics, The Hague, The Netherlands, 10-13 october 2004, pp. 4774-4779.
14. -, "Int-EM-CEM algorithm for imprecise data. Comparison with the CEM algorithm using monte carlo simulations," in IEEE International Conference on Cybernetics and Intelligent Systems, Singapore, 1-3 december 2004, pp. 410-415.
15. M. Chavent, "An hausdorff distance between hyper-rectangles for clustering interval data," in Classification, Clustering and Data Mining Applications, D. Banks, L. House, F. R. McMorris, P. Arabie, and W. Gaul, Eds. Springer, 2004, pp. 333-340.
16. R. M. C. R. De Souza and F. A. T. De Carvalho, "Clustering of interval data based on city-block distances," Pattern Recognition Letters, vol. 25, no. 3, pp. 353-365, 2004.
17. R. M. C. R. De Souza, F. A. T. De Carvalho, C. P. Tenrio, and Y. Lechevallier, "Dynamic cluster methods for interval data based on mahalanobis distances," in Proceedings of the 9th Conference of the International Federation of Classification Societies. Chicago, USA: Springer-Verlag, July 2004, pp. 351-360.
18. A. El Golli, B. Conan-Guez, and F. Rossi, "Self-organizing maps and symbolic data," JSDA Electronic Journal of Symbolic Data Analysis, vol. 2, no. 1, 2004.
19. T. Kohonen, Self Organization and Associative Memory, Second Edition. Springer Verlag, 1984.
20. -, Self-Organizing Maps, Third Edition. Springer, 2001.
21. M. Chavent, F. De Carvalho, Y. Lechevallier, and R. Verde, "Trois nouvelles mthodes de classification automatique de donnes symboliques de type intervalle," Revue de statistique appliquée, vol. 51, no. 4, pp. 5-29, 2003.