Trois nouvelles méthodes de classification automatique de données symboliques de type intervalle
M. Chavent; F. de A. T. De Carvalho; Y. Lechevallier; R. Verde
Revue de Statistique Appliquée (2003)
- Volume: 51, Issue: 4, page 5-29
- ISSN: 0035-175X
Access Full Article
topHow to cite
topChavent, M., et al. "Trois nouvelles méthodes de classification automatique de données symboliques de type intervalle." Revue de Statistique Appliquée 51.4 (2003): 5-29. <http://eudml.org/doc/106540>.
@article{Chavent2003,
author = {Chavent, M., De Carvalho, F. de A. T., Lechevallier, Y., Verde, R.},
journal = {Revue de Statistique Appliquée},
language = {fre},
number = {4},
pages = {5-29},
publisher = {Société française de statistique},
title = {Trois nouvelles méthodes de classification automatique de données symboliques de type intervalle},
url = {http://eudml.org/doc/106540},
volume = {51},
year = {2003},
}
TY - JOUR
AU - Chavent, M.
AU - De Carvalho, F. de A. T.
AU - Lechevallier, Y.
AU - Verde, R.
TI - Trois nouvelles méthodes de classification automatique de données symboliques de type intervalle
JO - Revue de Statistique Appliquée
PY - 2003
PB - Société française de statistique
VL - 51
IS - 4
SP - 5
EP - 29
LA - fre
UR - http://eudml.org/doc/106540
ER -
References
top- [AUB94] Aubin J.-P. (1994), Initiation à l'analyse appliquée, Masson. Zbl0809.90002MR1271774
- [BRE 84] Breiman L., Friedman J., Olshen R., Stone C. (1984), Classification and regression trees, Chapman Hall. Zbl0541.62042MR726392
- [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. Zbl0978.62003MR1792132
- [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-IXDauphine.
- [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. MR1415847
- [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. Zbl0894.62006
- [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 Zbl1052.62533MR1675089
- [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. Zbl1102.62308
- [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.
- [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. Zbl1052.68615
- [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. Zbl0331.62043
- [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. Zbl0503.68065
- [ICY 94] Ichino, M., Yaguchi H. (1994), Generalized Minkowsky Metrics for Mixed Feature Type Data Analysis. IEEE Transactions System, Man and Cybernetics24, 698-708. MR1280804
- [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. Zbl0896.68124
- [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. MR599671
- [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. Zbl1026.62069MR1848204
- [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. Zbl1026.62069
Citations in EuDML Documents
top- Áurea Sousa, Helena Bacelar-Nicolau, Fernando C. Nicolau, Osvaldo Silva, Clustering of Symbolic Data based on Affinity Coefficient: Application to a Real Data Set
- Aïcha El Golli, Fabrice Rossi, Brieuc Conan-Guez, Yves Lechevallier, Une adaptation des cartes auto-organisatrices pour des données décrites par un tableau de dissimilarités
NotesEmbed ?
topTo embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.