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Journal Articles Journal of Statistical Software Year : 2017

blockcluster: An R Package for Model Based Co-Clustering

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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Dates and versions

hal-01093554 , version 1 (10-12-2014)

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Parmeet Bhatia, Serge Iovleff, Gérard Govaert. blockcluster: An R Package for Model Based Co-Clustering. Journal of Statistical Software, 2017, 76 (9), pp.24. ⟨10.18637/jss.v076.i09⟩. ⟨hal-01093554⟩
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