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Model-based Cluster and Discriminant Analysis with the MIXMOD software

Christophe Biernacki 1 Gilles Celeux 1 Gérard Govaert Florent Langrognet
1 SELECT - Model selection in statistical learning
LMO - Laboratoire de Mathématiques d'Orsay, Inria Saclay - Ile de France
Abstract : The mixmod (mixture modelling) software fits mixture models to a given data set with a density estimation, a clustering or a discriminant analysis purpose. A large variety of algorithms to estimate the mixture parameters are proposed (EM, Classification EM, Stochastic EM) and it is possible to combine them to lead to different strategies in order to get a sensible maximum of the likelihood (or complete-data likelihood) function. mixmod is currently focused on multivariate Gaussian mixtures and fourteen different Gaussian models can be considered according to different assumptions on the component variance matrix eigenvalue decomposition. Moreover, different information criteria for choosing a parsimonious model (the number of mixture components, for instance), some of them favoring either a cluster analysis or a discriminant analysis view point, are included. Written in C++, mixmod is interfaced with Scilab and Matlab. The software, the statistical documentation and also the user guide are available on the internet at the following address:
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Contributor : Rapport de Recherche Inria <>
Submitted on : Friday, May 19, 2006 - 6:24:51 PM
Last modification on : Wednesday, October 14, 2020 - 4:00:29 AM
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  • HAL Id : inria-00069878, version 1



Christophe Biernacki, Gilles Celeux, Gérard Govaert, Florent Langrognet. Model-based Cluster and Discriminant Analysis with the MIXMOD software. [Research Report] RT-0302, INRIA. 2005, pp.20. ⟨inria-00069878⟩



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