Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-05T08:36:17.457Z Has data issue: false hasContentIssue false

Classification croisée et modèles

Published online by Cambridge University Press:  15 August 2002

Y. Bencheikh*
Affiliation:
Institut de Mathematiques, Université Ferhat Abbas de Setif, Setif 19000, Algérie.
Get access

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.

Type
Research Article
Copyright
© EDP Sciences, 1999

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)