PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Selecting models focussing on the modeller's purpose
Jean-Patrick Baudry, Gilles Celeux and Jean-Michel Marin
In: COMPSTAT2008, August 2009, Porto.

Abstract

Model selection is a difficult task for which it is often profitable to take into account the modeller point of view. Hidden structure models are a good example for which this point of view can be dealt with in a simple way. In the model-based clustering context, we present model selection criteria focussing on the clustering purpose. Their rationale and theoretical features are given and their practical behavior in comparison with classical penalized likelihood criteria is discussed from numerical experiments.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:4907
Deposited By:Gilles Celeux
Deposited On:24 March 2009