Simultaneous clustering of objects and variables, Analyse des données et Informatique, pp.187-203, 1979. ,
Revue des méthodes pour la classification jointe des lignes et des colonnes d'un tableau, Journal de la Société Française de Statistique, vol.156, issue.3, pp.27-51, 2015. ,
Biclustering of expression data, Proceedings of the International Conference on Intelligent Systems for Molecular Biology, pp.93-103, 2000. ,
Information-theoretic co-clustering, Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '03, pp.89-98, 2003. ,
DOI : 10.1145/956750.956764
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.13.9802
Categorization of classification Her Majesty's Stationery Office, In Mathematics and Computer Science in Biology and Medicine, pp.115-125, 1965. ,
Latent Block Model for Contingency Table, Communications in Statistics - Theory and Methods, vol.24, issue.3, pp.416-425, 2010. ,
DOI : 10.1016/j.csda.2007.09.007
URL : https://hal.archives-ouvertes.fr/hal-00447792
Clustering with block mixture models, Pattern Recognition, vol.36, issue.2, pp.463-473, 2003. ,
DOI : 10.1016/S0031-3203(02)00074-2
Clustering of contingency table and mixture model, European Journal of Operational Research, vol.183, issue.3, pp.1055-1066, 2007. ,
DOI : 10.1016/j.ejor.2005.10.074
Block clustering with Bernoulli mixture models: Comparison of different approaches, Computational Statistics & Data Analysis, vol.52, issue.6, pp.3233-3245, 2008. ,
DOI : 10.1016/j.csda.2007.09.007
Co-Clustering, 2013. ,
DOI : 10.1002/9781118649480
URL : https://hal.archives-ouvertes.fr/hal-00933301
Classification and Clustering, Journal of Marketing Research, vol.18, issue.4, 1975. ,
DOI : 10.2307/3151350
Violin plots : A box plot-density trace synergism, The American Statistician, vol.52, issue.2, pp.181-184, 1998. ,
DOI : 10.2307/2685478
Model based clustering for mixed data : clustmd Advances in Data Analysis and Classification, pp.155-169, 2016. ,
Co-clustering Analysis of Weblogs Using Bipartite Spectral Projection Approach, pp.398-407, 2010. ,
DOI : 10.1007/978-3-642-15393-8_45
very little work has been done to perform co-clustering on mixed type data In this article, we extend the use of latent bloc models to co-clustering in the case of mixed data (continuous and binary variables) We then evaluate the effectiveness of our extention on simulated data and we discuss its potential limits ,