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

Christophe Biernacki; Alexandre Lourme

Conference papers

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

Christophe Biernacki ^{1, 2} Alexandre Lourme ³

1 LPP - Laboratoire Paul Painlevé - UMR 8524

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

3 UB - Université de Bordeaux

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).

Document type :

Conference papers

Domain :

Statistics [stat] / Methodology [stat.ME]

Complete list of metadata

Cited literature [3 references] Display Hide Download

https://hal.archives-ouvertes.fr/hal-01420657
Contributor : Christophe Biernacki <>
Submitted on : Thursday, December 22, 2016 - 3:05:27 PM
Last modification on : Friday, November 27, 2020 - 2:18:02 PM

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

Annex

Identifiers

Collections

Citation

Export

Metrics

169

32

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

Annex

Identifiers

Collections

Citation

Export

Share

Metrics

169

32