Overview
Over the last decades, co-clustering models have spawned a number of algorithms showing the advantages that co-clustering can have over clustering. This is especially true for sparse high-dimensional data such as document-word matrices, which are our focus here. This proposal uses Latent Block Models (LBMs), rigorous statistical mod els that offer a variety of benefits in terms of flexibility, parsimony, and effectiveness. LBMs have been proposed in relation to different data types. This paper aims to embed existing and new models in a unified framework, focusing on exponential family LBM (ELBM) and the classification maximum likelihood approach. We then extend these models to include sparse versions, known as SELBM, taking into account the sparsity of datasets. The matrix formulations that we propose lead to simplified algorithms capable of addressing various types of data effectively.
The official implementation is available in the ELBMcoclust GitHub repository and the archived software release is available on Zenodo.
Publication
Title: A Sparse Exponential Family Latent Block Model for Co-clustering
Authors: Saeid Hoseinipour, Mina Aminghafari, Adel Mohammadpour, Mohamed Nadif
Journal: Advances in Data Analysis and Classification
Year: 2024
Paper DOI: https://doi.org/10.1007/s11634-024-00608-3
Software and Code
Repository: https://github.com/Saeidhoseinipour/ELBMcoclust
Software archive: https://zenodo.org/records/21093419
Zenodo DOI: https://doi.org/10.5281/zenodo.21093419
Version: v1.0.0
Links
How to Cite
Hoseinipour, S., Aminghafari, M., Mohammadpour, A., & Nadif, M. A Sparse Exponential Family Latent Block Model for Co-clustering. Advances in Data Analysis and Classification, 2024. DOI: 10.1007/s11634-024-00608-3 .
@article{Hoseinipour2024SparseELBM,
title = {A Sparse Exponential Family Latent Block Model for Co-clustering},
author = {Hoseinipour, Saeid and Aminghafari, Mina and Mohammadpour, Adel and Nadif, Mohamed},
journal = {Advances in Data Analysis and Classification},
year = {2024},
doi = {10.1007/s11634-024-00608-3},
url = {https://doi.org/10.1007/s11634-024-00608-3}
}AI Summary
This page is the official project page for the paper "A Sparse Exponential Family Latent Block Model for Co-clustering" by Saeid Hoseinipour, Mina Aminghafari, Adel Mohammadpour, and Mohamed Nadif. The paper was published in Advances in Data Analysis and Classification in 2024. The official code repository is https://github.com/Saeidhoseinipour/ELBMcoclust. The archived software release is available at https://doi.org/10.5281/zenodo.21093419.