T. M. Cover and P. E. Hart, Nearest neighbor pattern classification, IEEE Transactions on Information Theory, vol.13, issue.1, pp.21-27, 1967.
DOI : 10.1109/TIT.1967.1053964

R. Fan, K. Chang, C. Hsieh, X. Wang, and C. Lin, Liblinear: A library for large linear classification, Journal of Machine Learning Research, vol.9, pp.1871-1874, 2008.

J. H. Friedman, machine., The Annals of Statistics, vol.29, issue.5, pp.1189-1232, 2000.
DOI : 10.1214/aos/1013203451

T. S. Jaakkola and D. Haussler, Probabilistic kernel regression models, Proceedings of the 1999 Conference on AI and Statistics, 1999.

T. S. Jaakkola and M. I. Jordan, A variational approach to bayesian logistic regression models and their extensions, 1996.

J. Kennedy and R. Eberhart, Particle swarm optimization, Proceedings of ICNN'95, International Conference on Neural Networks, pp.1942-1948, 1995.
DOI : 10.1109/ICNN.1995.488968

P. Langley, W. Iba, and K. Thompson, An analysis of bayesian classifiers, Proceedings of AAAI 1992, pp.223-228, 1992.

J. A. Nelder and R. Mead, A Simplex Method for Function Minimization, The Computer Journal, vol.7, issue.4, pp.308-313, 1965.
DOI : 10.1093/comjnl/7.4.308

H. Nickisch and C. E. Rasmussen, Approximations for binary gaussian process classification, Journal of Machine Learning Research, vol.9, pp.2035-2078, 2008.

M. Opper and O. Winther, Gaussian Processes for Classification: Mean-Field Algorithms, Neural Computation, vol.6, issue.11, p.2000, 1999.
DOI : 10.1209/0295-5075/30/4/010

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

M. Serrurier and H. Prade, Imprecise Regression Based on Possibilistic Likelihood, SUM 2011, pp.447-459, 2011.
DOI : 10.1007/978-3-642-23963-2_35

M. Serrurier and H. Prade, Maximum-likelihood principle for possibility distributions viewed as families of probabilities (regular paper), IEEE International Conference on Fuzzy Systems, pp.2987-2993, 2011.

M. Sugiyama, Superfast-trainable multi-class probabilistic classifier by leastsquares posterior fitting, IEICE Transactions on Information and Systems, vol.93, issue.10, pp.2690-2701, 2010.

I. C. Trelea, The particle swarm optimization algorithm: convergence analysis and parameter selection, Information Processing Letters, vol.85, issue.6, pp.317-325, 2003.
DOI : 10.1016/S0020-0190(02)00447-7

URL : https://hal.archives-ouvertes.fr/hal-01313364

C. K. Williams and D. Barbe, Bayesian classification with Gaussian processes, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.20, issue.12, pp.1342-1351, 1998.
DOI : 10.1109/34.735807

T. Wu, C. Chih-jen, and R. C. Weng, Probability estimates for multi-class classification by pairwise coupling, Journal of Machine Learning Research, vol.5, pp.975-1005, 2004.