Trois nouvelles méthodes de classification automatique de données symboliques de type intervalle
Chavent, M. ; De Carvalho, F. de A. T. ; Lechevallier, Y. ; Verde, R.
Revue de Statistique Appliquée, Tome 51 (2003), p. 5-29 / Harvested from Numdam
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@article{RSA_2003__51_4_5_0,
     author = {Chavent, Marie and De Carvalho, F. de A. T. and Lechevallier, Yves and Verde, R.},
     title = {Trois nouvelles m\'ethodes de classification automatique de donn\'ees symboliques de type intervalle},
     journal = {Revue de Statistique Appliqu\'ee},
     volume = {51},
     year = {2003},
     pages = {5-29},
     language = {fr},
     url = {http://dml.mathdoc.fr/item/RSA_2003__51_4_5_0}
}

Chavent, M.; De Carvalho, F. de A. T.; Lechevallier, Y.; Verde, R. Trois nouvelles méthodes de classification automatique de données symboliques de type intervalle. Revue de Statistique Appliquée, Tome 51 (2003) pp. 5-29. http://gdmltest.u-ga.fr/item/RSA_2003__51_4_5_0/

[AUB94] Aubin J.-P. (1994), Initiation à l'analyse appliquée, Masson. | MR 1271774 | Zbl 0809.90002

[BRE 84] Breiman L., Friedman J., Olshen R., Stone C. (1984), Classification and regression trees, Chapman Hall. | MR 726392

[BOC 00] BOCK H. H., DIDAY E. (eds.) (2000), Analysis of Symbolic Data, Exploratory methods for extracting statistical information from complex data. Studies in Classification, Data Analysis and Knowledge Organisation, Springer-Verlag. | MR 1792132 | Zbl 0978.62003

[CEL 89] Celeux G., Diday E., Govaert, G. Lechevallier Y., Ralam-Bondrainy H. (1989), Classification Automatique des Données. Bordas, Paris.

[CHA 97] Chavent M. (1997), Analyse des Données Symboliques. Une méthode divisive de classification. Thèse de l'Université de PARIS-IX Dauphine.

[DCA 94] De Carvalho F.A.T. (1994), Proximity coefficients between Boolean symbolic objects, in New Approaches in Classification and Data Analysis, Diday et al. (Eds.), Springer Verlag, Heidelberg, 387-394. | MR 1415847

[DCA 98] De Carvalho F.A.T. (1998), Extension based proximities between Boolean symbolic objects, in Data Science, Classification and Related Methods, Hayashi, C. et al. (eds.), Springer-Verlag, Tokyo, 370-378. | Zbl 0894.62006

[DCS 98] De Carvalho F.A.T., Souza R.M.C. (1998), Statistical proximity functions of Boolean symbolic objects based on histograms. In : Rizzi, A., Vichi, M., Bock, H.-H. (Eds.) : Advances in Data Science and Classification, Springer-Verlag, Heidelberg, 391- 396 | MR 1675089 | Zbl 1052.62533

[DCA 00] De Carvalho F.A.T., Anselmo C.A.F., Souza, R.M.C.R. (2000), Symbolic approach to classify large data sets, in : Data Analysis, Classification, and Related Methods, Kiers, H.A.L. et al. (Eds.), Springer, 375-380. | Zbl 1102.62308

[DVL 99] De Carvalho F.A.T., Verde, R. et Lechevallier Y. (1999), A dynamical clustering of symbolic objects based on a context dependent proximity measure. In : Bacelar-Nicolau, H., Nicolau, F.C. and Janssen, J. (Eds.) : Proc. IX International Symposium - ASMDA'99. LEAD, Univ. de Lisboa, 237-242.

[DID 71] Diday E. (1971), Le méthode des Nuées dynamiques, in Revue de Statistique Appliquée, 19, 2, 19-34. | Numdam

[DID 88] Diday E. (1988), The symbolic approach in clustering and related methods of data analysis : The basic choice. In Proc. IFCS-97, Bock, H.-H. (Eds), Springer-Verlag, Heidelberg, 673-684.

[DID 98] Diday E. (1998), Symbolic Data Analysis : a Mathematical Framework and Tool for Data Mining, in New Andvances in Data Science and Classification, Rizzi, A. et al. (eds.), Springer -Verlag, Heidelberg, 409-416. | Zbl 1052.68615

[DIS 76] Dida Y.E. AND Simon J.C. (1976), Clustering Analysis. In : Fu, K. S. (Eds.) : Digital Pattern Recognition. Springer-Verlag, Heidelberg, 47-94. | Zbl 0331.62043

[DID 80] Diday E., Govaert G., Lechevallier Y. et Sidi J. (1980), Clustering in pattern recognition, NATO Advanced study Institute on Digital Image Processing and Analysis, Bonas. Available at INRIA-Rocquencourt. | Zbl 0503.68065

[ICY 94] Ichino, M., Yaguchi H. (1994), Generalized Minkowsky Metrics for Mixed Feature Type Data Analysis. IEEE Transactions System, Man and Cybernetics 24, 698-708. | MR 1280804

[IYD 96] Ichino M., Yaguchi H., Diday E. (1996), A fuzzy symbolic pattern classifier, in : Ordinal and Symbolic Data Analysis, Diday, E. et al. (Eds.), Springer, 92-102. | Zbl 0896.68124

[LEC 97] Lechevallier Y. (1997), Classification non supervisée, in Statistique et méthodes neuronales, Thiria, Lechevallier et al. (Eds.), Dunod, Chap. 10,171- 189.

[LER 79] Leredde H. (1979), La méthode des pôles d'attraction - La méthode des pôles d'agrégation. Thèse de Diplôme de docteur de 3e cycle. Université Paris VI, 106-116.

[MIC 80] Michalski R.S. (1980), Knowledge acquisition through conceptual clustering : A theoretical framework and an algorithm for partitioning data into conjunctive concepts. A special Issue on Knowledge Acquisition and Induction. Policy Analysis and Information Systems, 3. | MR 599671

[MDS 81] Michalski R.S., Diday E., Stepp R.E. (1981), A recent advance in data analysis : Clustering Objects into classes characterized by conjunctive concepts. In : Kanal L. N. and Rosenfeld A. (Eds.) : Progress in pattern recognition. North-Holland, 33-56.

[VDL 00] Verde R., De Carvalho F.A.T., Lechevallier Y. (2000), A Dynamical Clustering Algorithm for Multi-Nominal Data. In : H.A.L. Kiers, J.-P. Rasson, P.J.F. Groenen and M. Schader (Eds.) : Data Analysis, Classification, and Related Methods, Springer-Verlag, Heidelberg, 387-394. | MR 1848204 | Zbl 1026.62069

[VDL 01] Verde R., DE Carvalho F.A.T., Lechevallier Y. (2001), A dynamical clustering algorithm for symbolic data. Tutorial Symbolic Data Analysis, GfK1 Conference, Munich.