blockcluster: An R Package for Model Based Co-Clustering

Parmeet Bhatia 1 Serge Iovleff 2, 1 Gérard Govaert 3
1 MODAL - MOdel for Data Analysis and Learning
LPP - Laboratoire Paul Painlevé - UMR 8524, Université de Lille, Sciences et Technologies, Inria Lille - Nord Europe, CERIM - Santé publique : épidémiologie et qualité des soins-EA 2694, Polytech Lille - École polytechnique universitaire de Lille
Abstract : Simultaneous clustering of rows and columns, usually designated by bi-clustering, co-clustering or block clustering, is an important technique in two way data analysis. A new standard and efficient approach have been recently proposed based on latent block model [Govaert and Nadif (2003)] which takes into account the block clustering problem on both the individual and variables sets. This article presents our R package for co-clustering of binary, contingency and continuous data blockcluster based on these very models. In this document, we will give a brief review of the model-based block clustering methods, and we will show how the R package blockcluster can be used for co-clustering.
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Submitted on : Wednesday, December 10, 2014 - 5:46:31 PM
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  • HAL Id : hal-01093554, version 1


Parmeet Bhatia, Serge Iovleff, Gérard Govaert. blockcluster: An R Package for Model Based Co-Clustering. 2014. ⟨hal-01093554⟩



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