Discrimination et régression par une méthode neuromimétique et par la méthode de segmentation CART : application à différentes données et comparaison des résultats
Revue de Statistique Appliquée, Tome 44 (1996) no. 4, pp. 19-40. 
@article{RSA_1996__44_4_19_0,
     author = {Nakache, J.-P. and Vilain, J. and Fertil, B.},
     title = {Discrimination et r\'egression par une m\'ethode neuromim\'etique et par la m\'ethode de segmentation {CART} : application \`a diff\'erentes donn\'ees et comparaison des r\'esultats},
     journal = {Revue de Statistique Appliqu\'ee},
     pages = {19--40},
     publisher = {Soci\'et\'e de Statistique de France},
     volume = {44},
     number = {4},
     year = {1996},
     language = {fr},
     url = {http://www.numdam.org/item/RSA_1996__44_4_19_0/}
}
TY  - JOUR
AU  - Nakache, J.-P.
AU  - Vilain, J.
AU  - Fertil, B.
TI  - Discrimination et régression par une méthode neuromimétique et par la méthode de segmentation CART : application à différentes données et comparaison des résultats
JO  - Revue de Statistique Appliquée
PY  - 1996
SP  - 19
EP  - 40
VL  - 44
IS  - 4
PB  - Société de Statistique de France
UR  - http://www.numdam.org/item/RSA_1996__44_4_19_0/
LA  - fr
ID  - RSA_1996__44_4_19_0
ER  - 
%0 Journal Article
%A Nakache, J.-P.
%A Vilain, J.
%A Fertil, B.
%T Discrimination et régression par une méthode neuromimétique et par la méthode de segmentation CART : application à différentes données et comparaison des résultats
%J Revue de Statistique Appliquée
%D 1996
%P 19-40
%V 44
%N 4
%I Société de Statistique de France
%U http://www.numdam.org/item/RSA_1996__44_4_19_0/
%G fr
%F RSA_1996__44_4_19_0
Nakache, J.-P.; Vilain, J.; Fertil, B. Discrimination et régression par une méthode neuromimétique et par la méthode de segmentation CART : application à différentes données et comparaison des résultats. Revue de Statistique Appliquée, Tome 44 (1996) no. 4, pp. 19-40. http://www.numdam.org/item/RSA_1996__44_4_19_0/

Breiman L., Friedman J.H., Ohlsen R.A., Stone C.J., Classification and Regression Trees. Belmont, 1984. | Zbl

Burke H.B., Rosen D.B., Goodman P.H., Comparing Artificial neural networks to other statistical methods for medical outcome prodiction. In proceeding : IEEE Int. Conference on Neural Networks, Orlando, F1, p. 2213, 1994.

CART, A software classification and regression trees. Yorshire Ct. Lafayette, California: California Statistical Software, inc., 1984. | MR

Celeux J.P., Nakache J.-P., Analyse discriminante sur variables qualitatives. Polytechnica Ed, 1994.

Cichocki A., Unbehauen R., Neural Networks for Optimization and Signal Processing, p. 526. Stuttgart: Wiley, J. & Sons Ltd & Teubner, B.G., 1993. | Zbl

Coustere C., Fertil B., Un nouvel outil pour l'analyse de données : les réseaux de neurones. Applications en microbiologie, Bulletin de la société Française de Microbiologie 7, 10, 1992.

Davalo E., Naim P., Des réseaux de neurones, 2 édition, p. 232. Paris: Editions Eyrolles, 1993.

Fertil B., Vilain J., Multiple Learning Sessions to Improve Predictions and Evaluate Reliability of Neural Networks. In proceeding : 4th International conference on Artificial Neural Networks, Sorrento, Italy, 1994, p. 1323.

Flamant Y., Lacaine F., Hay J.M., Maillard J.N., Syndromes douloureux aigus de l'abdomen. Aide au diagnostic par ordinateur, Nouvelle Presse Médicale 10, 3367, 1981.

Gallinari P., Thiria S., Badran F., Fogelman-Soulie F., On the relations between discriminant analysis and multilayer perceptrons, in Neural Networks (USA), vol. 4, n°3, p. 349 -69, 1991.

Gernoth K.A., Clark J.W., Neural networks that learn to predict probabilities : Global models of nuclear stability and decay, Neural Networks 8, 291, 1995.

Gueguen A., Nakache J.-P., Méthode de discrimination basée sur la construction d'un arbre de décision binaire, Rev. Stat. Appl., 36, 19, 1988. | Numdam

Gueguen A., Nicolau J., Nakache J.-P., Utilisation des réseaux probabilistes en analyse discriminante sur variables qualitatives, Rev. Stat. Appl., 1996. | Numdam

Harrison D., Rubinfeld D.L., Hedonic prices and the demand for clean air, J. Envir. Econ. and Management 5, 81, 1978. | Zbl

Jepson B., Collins A., Evans A., Post-neural network procedure to determine expected prediction values and their confidence limits, Neural Computing & applications 1, 224, 1993.

Kass G.V., An exploratory technique for investigating large quantities of categorical data, Applied Statistics, 29, 119, 1980.

Katz A.S., Katz S., Lowe N., Fundamentals of the bootstrap based analysis of neural network's accuracy. In proceeding : WCNN, San Diego, USA, 1994, p. 673.

Le Cun Y., Learning Scheme for asymmetric threshold networks. In proceeding : Cognitiva 85, Paris, France, p. 599, 1985.

Leon M.A., Binary response forecasting : comparaison between neural networks and logistic regression analysis, in proc. of WCN 2, 244, 1994.

Liu Y., Unbiased Estimate of Generalization Error and Model Selection in Neural Network, Neural Networks 8, 215, 1995.

Martin C.E., Rogers S.K., Ruck D.W., Neural network Bayes error estimation, in proc. of IEEE ICNN 305, 1994.

Mascioli F.M.F., Martinelli G., Lazzaro D., comparison of Constructive Algorithms for Neural Networks, in proc. of ICANN 1, 731, 1994.

Masters T., Practical neural network recipes in C++, p. 493. San Diego, CA, Academic Press, Inc, 1993. | MR | Zbl

Masters T., Signal and image processing with neural networks, a C++ sourcebook. New York, Wiley & sons, inc., 1994.

Mcclelland J.L., Rumelhart D.E., Explorations in parallel distributed processing. A handbook of models, programs and exercises, p. 344. Cambridge, MA, MIT Press, 1988.

Michie D., Spiegelmalter D.J., Taylor C.C., Machine learning Neural and Statistical Classification, Ed. Ellis Horwood N.Y., 1994. | Zbl

Morgan J.A., Messenger R.C., A modal search technique for predictive nominal scale multivariate analysis, J. Amer. Statis. Ass. 67, 768, 1972.

Morgan J.A., Sonquist J.N., Problems in the analysis of survey data and a proposal, J. Amer. Statist. Ass. 58, 415, 1963. | Zbl

Nakache J.P., Golmard J.L., Gueguen A., Comparison of the performance of the conditional independence based model and the CART tree-structured discrimination model applied to a large medical data set. In proceeding : MIE 93, Jérusalem (Israël), 1993.

Nix D.A., Weigend A.S., Estimating the Mean and Variance of the Target Probability Distribution, in proc. of IEEE ICNN 55, 1994.

Paass G., Assessing predictive accuracy by the bootstrap algorithm. In proceeding, 4th International conference on Artificial Neural Networks, Sorrento, Italy, p. 823, 1994.

Perantonis S.J., Karras D.A., An efficient constrained learning algorithm with momentum acceleration, Neural Networks 8, 237, 1995.

Ripley B.D., Statistical aspects of neural networks. In : O.E. Barndorff-Nielsen, J.L. Jensen, and W.S. Kendall (ed.), Networks and Chaos - Statistical and Probabilistic Aspects, p. 40, Chapman & Hall, 1993. | Zbl

Ripley B.D., Network methods in statistics. In : F.P. Kelly (ed.), Probability, Statistics, Optimisation, a Tribute to Peter Whittle, p. 241, Wiley, 1994a. | MR | Zbl

Ripley B.D., Neural networks and flexible regression and discrimination. In : K.V. Mardia (ed.), Advances in Statistics 2, p. 39. Carfax: Abingdon, 1994b.

Ruck D.W., Rogers S.K., Kabrisky M., Oxley M.E., Suter B.W., The multilayer perceptron as an approximation to a Bayes optimal discriminant function, IEEE Transactions on Neural Networks 1, 296, 1990.

Rumelhart D.E., Hinton G.E., Williams R.J., Learning internal representations by error propagation. In : D. E. Rumelhart and J.L. McClelland (ed.), Parallel distributed processing : explorations in the microstructure of cognition, Vol. 1, Fondations, p. 318. Cambridge, MA, MIT Press, 1986.

Seroussi B., ARC et AURC, Comparison of discrimination methods; application to the acute abdominal pain diagnosis. In : D. Tfistsis (ed.), Lecture notes in médical informatics, Objective medical decision making, Vol. 28, p. 12: Springer-Verlag, 1985.

Siegel S., Nonparametric statistics for the behavioral sciences, McGraw-Hill Intern. Book Company, 1956. | Zbl

Shadmehr R., D'Argenio D.Z., A comparison of a neural network based estimator and two statistical estimators in a sparse and noisy data environment, in proc. of IJCNN 1, 289, 1990.

SPAD.N., Système portable dAnalyse des Données - procédure NEURO. Saint-Mandé, CISIA, 1993.

SPAD.S., Système Portable d'Analyse des Données - Segmentation. Saint-Mandé: CISIA, 1993.

Srivastava A.N., Weigend A.S., Computing the probability density in connectionist regression, in proc. of WCNN 2, 311, 1994.

Weisbuch G., Dynamique des systèmes complexes, p. 212. Paris, InterEditions & Editions du CNRS, 1989.