NONLINEAR MAPPING BY CONSTRAINED CO-CLUSTERING

Rodolphe Priam, Mohamed Nadif, Gérard Govaert

2012

Abstract

The latent block model is an efficient alternative to the mixture model for modelling a dataset when the number of rows or columns of the data matrix studied is large. For analyzing and reducing the spaces of a matrix, the methods proposed in the litterature are most of the time with their foundation in a non-parametric or a mixture model approach. We present an embedding of the projection of co-occurrence tables in the Poisson latent block mixture model. Our approach leads to an efficient way to cluster and reduce this kind of data matrices.

Paper Citation

in Harvard Style

Priam R., Nadif M. and Govaert G. (2012). NONLINEAR MAPPING BY CONSTRAINED CO-CLUSTERING . In Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-8425-98-0, pages 63-68. DOI: 10.5220/0003764800630068

in Bibtex Style

@conference{icpram12,
author={Rodolphe Priam and Mohamed Nadif and Gérard Govaert},
title={NONLINEAR MAPPING BY CONSTRAINED CO-CLUSTERING},
booktitle={Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2012},
pages={63-68},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003764800630068},
isbn={978-989-8425-98-0},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - NONLINEAR MAPPING BY CONSTRAINED CO-CLUSTERING
SN - 978-989-8425-98-0
AU - Priam R.
AU - Nadif M.
AU - Govaert G.
PY - 2012
SP - 63
EP - 68
DO - 10.5220/0003764800630068