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
International audienceThree-way data can be seen as a collection of two-way matrices, as we can meet...
International audienceA model-based coclustering algorithm for ordinal data is presented. This algor...
The simultaneous grouping of rows and columns is an important technique that is increasingly used in...
Simultaneous clustering of rows and columns, usually designated by bi-clustering, coclustering or bl...
Simultaneous clustering of rows and columns, usually designated by bi-clustering, co-clustering or b...
Co-clustering aims to identify block patterns in a data table, from a joint clustering of rows and c...
International audienceCo-clustering is a data mining technique used to extract the underlying block ...
We present here model-based co-clustering methods, with a focus on the latent block model (LBM). We ...
International audienceCo-clustering is a data mining technique used to extract the underlying block ...
Cluster or co-cluster analyses are important tools in a variety of scientific areas. The introductio...
International audienceMany of the datasets encountered in statistics are two-dimensional in nature a...
National audienceCo-clustering aims to identify block patterns in a data table, from a joint cluster...
Abstract: One of the major problems in clustering is the need of specifying the optimal number of cl...
Model-based co-clustering can be seen as a particularly valuable extension of model-based clustering...
Co-clustering (also known as biclustering), is an important extension of cluster analysis since it a...
International audienceThree-way data can be seen as a collection of two-way matrices, as we can meet...
International audienceA model-based coclustering algorithm for ordinal data is presented. This algor...
The simultaneous grouping of rows and columns is an important technique that is increasingly used in...
Simultaneous clustering of rows and columns, usually designated by bi-clustering, coclustering or bl...
Simultaneous clustering of rows and columns, usually designated by bi-clustering, co-clustering or b...
Co-clustering aims to identify block patterns in a data table, from a joint clustering of rows and c...
International audienceCo-clustering is a data mining technique used to extract the underlying block ...
We present here model-based co-clustering methods, with a focus on the latent block model (LBM). We ...
International audienceCo-clustering is a data mining technique used to extract the underlying block ...
Cluster or co-cluster analyses are important tools in a variety of scientific areas. The introductio...
International audienceMany of the datasets encountered in statistics are two-dimensional in nature a...
National audienceCo-clustering aims to identify block patterns in a data table, from a joint cluster...
Abstract: One of the major problems in clustering is the need of specifying the optimal number of cl...
Model-based co-clustering can be seen as a particularly valuable extension of model-based clustering...
Co-clustering (also known as biclustering), is an important extension of cluster analysis since it a...
International audienceThree-way data can be seen as a collection of two-way matrices, as we can meet...
International audienceA model-based coclustering algorithm for ordinal data is presented. This algor...
The simultaneous grouping of rows and columns is an important technique that is increasingly used in...