Add to ORKGInternational audienceA model-based coclustering algorithm for ordinal data is presented. This algorithm relies on the latent block model using the BOS model (Biernacki and Jacques, 2015, Stat. Comput.) for ordinal data and a SEM-Gibbs algorithm for inference. Numerical experiments on simulated data illustrate the efficiency of the inference strategy
International audienceThe dataset that motivated this work is a psychological survey on women affect...
International audienceThree-way data can be seen as a collection of two-way matrices, as we can meet...
The literature on cluster analysis has a long and rich history in several different fields. In this ...
International audienceA model-based coclustering algorithm for ordinal data is presented. This algor...
International audienceA model-based coclustering algorithm for ordinal data is presented. Thisalgori...
Ordinal data are used in a lot of domains, especially when measurements are collected from persons b...
International audienceThis paper is about the co-clustering of ordinal data. Such data are very comm...
International audienceCo-clustering is a data mining technique used to extract the underlying block ...
International audienceWe design the first univariate probability distribution for ordinal data which...
We present here model-based co-clustering methods, with a focus on the latent block model (LBM). We ...
International audienceOrdinal data are used in many domains, especially when measurements are collec...
Cluster or co-cluster analyses are important tools in a variety of scientific areas. The introductio...
A finite mixture model to simultaneously cluster the rows and columns of two-mode ordinal data matr...
A finite mixture model to simultaneously cluster the rows and columns of a two-mode ordinal data mat...
National audienceCo-clustering aims to identify block patterns in a data table, from a joint cluster...
International audienceThe dataset that motivated this work is a psychological survey on women affect...
International audienceThree-way data can be seen as a collection of two-way matrices, as we can meet...
The literature on cluster analysis has a long and rich history in several different fields. In this ...
International audienceA model-based coclustering algorithm for ordinal data is presented. This algor...
International audienceA model-based coclustering algorithm for ordinal data is presented. Thisalgori...
Ordinal data are used in a lot of domains, especially when measurements are collected from persons b...
International audienceThis paper is about the co-clustering of ordinal data. Such data are very comm...
International audienceCo-clustering is a data mining technique used to extract the underlying block ...
International audienceWe design the first univariate probability distribution for ordinal data which...
We present here model-based co-clustering methods, with a focus on the latent block model (LBM). We ...
International audienceOrdinal data are used in many domains, especially when measurements are collec...
Cluster or co-cluster analyses are important tools in a variety of scientific areas. The introductio...
A finite mixture model to simultaneously cluster the rows and columns of two-mode ordinal data matr...
A finite mixture model to simultaneously cluster the rows and columns of a two-mode ordinal data mat...
National audienceCo-clustering aims to identify block patterns in a data table, from a joint cluster...
International audienceThe dataset that motivated this work is a psychological survey on women affect...
International audienceThree-way data can be seen as a collection of two-way matrices, as we can meet...
The literature on cluster analysis has a long and rich history in several different fields. In this ...