Classification croisée et modèles

Abstract

The relations between automatic clustering methods and inferentiel statistical models have mostely been studied when the data involves only one set. We propose to study these relations in the caseof data involving two sets. We shall look at cross clustering methods assuggested by Govaert [6]; we show that these methods, like the simple clusteringmethods, can be considered as a clustering approach of a mixture model. Weintroduce the notion of crossed mixture from a concret example and define thenotions of likelihood and associated clustered likelihood. Then, we study therelations which exist between the crossed mixture models and simple models and weshow that these relations are completely similar to those which exist betweenthe crossed clustering methods and simple clustering methods.