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Unifying Data Units and Models in Statistics: Focus on (Co-)Clustering

Christophe Biernacki 1, 2 Alexandre Lourme 3
2 MODAL - MOdel for Data Analysis and Learning
Inria Lille - Nord Europe, LPP - Laboratoire Paul Painlevé - UMR 8524, METRICS - Evaluation des technologies de santé et des pratiques médicales - ULR 2694, Polytech Lille - École polytechnique universitaire de Lille, Université de Lille, Sciences et Technologies
Abstract : In this talk, we highlight that it is possible to embed data unit selection into a classical model selection principle. We introduce the problem in a regression context before to focus on the model-based clustering and co-clustering context, for data of different kinds (continuous, categorical).
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Contributor : Christophe Biernacki <>
Submitted on : Thursday, December 22, 2016 - 3:05:27 PM
Last modification on : Friday, November 27, 2020 - 2:18:02 PM


  • HAL Id : hal-01420657, version 1



Christophe Biernacki, Alexandre Lourme. Unifying Data Units and Models in Statistics: Focus on (Co-)Clustering. Workshop on Model-based Clustering and Classification (MBC2), Sep 2016, Catania, Italy. ⟨hal-01420657⟩



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