Model selection for Gaussian latent block clustering with the integrated classification likelihood
type: Item
instance of: scholarly article
published in: Advances in Data Analysis and Classification. ADAC
volume: 12
issue: 3
page(s): 489-508
publication date: 2014-02-09T00:00:00Z
publication date: 2018-12-05T00:00:00Z
author: Aurore Lomet
author: Gérard Govaert
author: Yves Grandvalet
title: Model selection for Gaussian latent block clustering with the integrated classification likelihood
zbMATH Open document ID: 1416.62349
Mathematics Subject Classification ID: 62H30
Mathematics Subject Classification ID: 62F15
zbMATH DE Number: 6989227
zbMATH Keywords: co-clustering
zbMATH Keywords: latent block model
zbMATH Keywords: model selection
zbMATH Keywords: continuous data
zbMATH Keywords: integrated classification likelihood
zbMATH Keywords: BIC
describes a project that uses: BayesDA
MaRDI profile type: Publication
full work available at URL: s11634-013-0161-3
OpenAlex ID: W2057245283
cites work: Q3174147
cites work: An improvement of the NEC criterion for assessing the number of clusters in a mixture model
cites work: Exact and Monte Carlo calculations of integrated likelihoods for the latent class model
cites work: How Many Clusters? Which Clustering Method? Answers Via Model-Based Cluster Analysis
cites work: Q4807438
cites work: Q4886783
cites work: Bloc voting in the United States senate
cites work: Estimation and selection for the latent block model on categorical data
cites work: Convergence of the groups posterior distribution in latent or stochastic block models
cites work: Finite mixture models
cites work: Block clustering with Bernoulli mixture models: comparison of different approaches
cites work: Q4363930
cites work: Q2732653
cites work: Two-mode multi-partitioning
cites work: Selecting among multi-mode partitioning models of different complexities: a comparison of four model selection criteria
cites work: PAC-Bayesian analysis of co-clustering and beyond
cites work: Block clustering with collapsed latent block models
DOI: 10.1007/S11634-013-0161-3
Recommended article: Model selection and clustering in stochastic block models based on the exact integrated complete data likelihood
Recommended article: Block-Wise Variable Selection for Clustering Via Latent States of Mixture Models
Recommended article: Estimation and model selection for model-based clustering with the conditional classification likelihood
Recommended article: Block Bernoulli Parsimonious Clustering Models
Recommended article: Bayesian inference of clustering and multiple Gaussian graphical models selection
Recommended article: Hierarchical clustering with discrete latent variable models and the integrated classification likelihood
Recommended article: Block clustering with Bernoulli mixture models: comparison of different approaches
Recommended article: Likelihood-based model selection for stochastic block models
description: scientific article; zbMATH DE number 6989227