Block clustering of Binary Data with Gaussian Co-variables
Applications
2018-12-21 v1 Statistics Theory
Statistics Theory
Abstract
The simultaneous grouping of rows and columns is an important technique that is increasingly used in large-scale data analysis. In this paper, we present a novel co-clustering method using co-variables in its construction. It is based on a latent block model taking into account the problem of grouping variables and clustering individuals by integrating information given by sets of co-variables. Numerical experiments on simulated data sets and an application on real genetic data highlight the interest of this approach.
Cite
@article{arxiv.1812.08520,
title = {Block clustering of Binary Data with Gaussian Co-variables},
author = {Serge Iovleff and Seydou Syllla and Cheikh Loucoubar},
journal= {arXiv preprint arXiv:1812.08520},
year = {2018}
}