Unifying Data Units and Models in Statistics: ...
Document type :
Communication dans un congrès avec actes
Title :
Unifying Data Units and Models in Statistics: Focus on (Co-)Clustering
Author(s) :
Biernacki, Christophe [Auteur]
MOdel for Data Analysis and Learning [MODAL]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Lourme, Alexandre [Auteur]
Université de Bordeaux [UB]
MOdel for Data Analysis and Learning [MODAL]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Lourme, Alexandre [Auteur]
Université de Bordeaux [UB]
Conference title :
Workshop on Model-based Clustering and Classification (MBC2)
City :
Catania
Country :
Italie
Start date of the conference :
2016-09-05
HAL domain(s) :
Statistiques [stat]/Méthodologie [stat.ME]
English abstract : [en]
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 ...
Show more >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).Show less >
Show more >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).Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
Source :
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