Skip to Main content Skip to Navigation
Conference papers

Pitfalls in Mixtures from the Clustering Angle

Christophe Biernacki 1, 2 Gwenaelle Castellan 2 Stephane Chretien 3 Benjamin Guedj 1 Vincent Vandewalle 1, 4 
1 MODAL - MOdel for Data Analysis and Learning
LPP - Laboratoire Paul Painlevé - UMR 8524, Université de Lille, Sciences et Technologies, Inria Lille - Nord Europe, METRICS - Evaluation des technologies de santé et des pratiques médicales - ULR 2694, Polytech Lille - École polytechnique universitaire de Lille
Abstract : Slides of this talk are both a review and a prospective work about degeneracy, label switching and spurious in a model-based clustering context. Originality is to deal with these topics from a dynamical point of view on the EM algorithm, and other related algorithms.
Document type :
Conference papers
Complete list of metadata
Contributor : Christophe Biernacki Connect in order to contact the contributor
Submitted on : Wednesday, December 21, 2016 - 5:40:10 PM
Last modification on : Tuesday, April 19, 2022 - 10:11:08 AM


  • HAL Id : hal-01419755, version 1



Christophe Biernacki, Gwenaelle Castellan, Stephane Chretien, Benjamin Guedj, Vincent Vandewalle. Pitfalls in Mixtures from the Clustering Angle. Working Group on Model-Based Clustering Summer Session, Jul 2016, Paris, France. ⟨hal-01419755⟩



Record views


Files downloads