Variable selection for mixed data clustering: application in human population genomics
From MaRDI portal
Publication:779017
DOI10.1007/s00357-018-9301-yOpenAlexW2926394855MaRDI QIDQ779017
Tienne Patin, Matthieu Marbac, Mohammed Sedki
Publication date: 21 July 2020
Published in: Journal of Classification (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s00357-018-9301-y
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Variable selection for model-based clustering using the integrated complete-data likelihood
- Variable selection for latent class analysis with application to low back pain diagnosis
- Latent class analysis variable selection
- Variable selection for clustering and classification
- Clustering and variable selection for categorical multivariate data
- Concentration inequalities and model selection. Ecole d'Eté de Probabilités de Saint-Flour XXXIII -- 2003.
- Variable selection in model-based clustering: a general variable role modeling
- Exact and Monte Carlo calculations of integrated likelihoods for the latent class model
- Clustering criteria for discrete data and latent class models
- Estimating the dimension of a model
- Dimension-reduced clustering of functional data via subspace separation
- Model-based clustering
- Bayesian variable selection for latent class analysis using a collapsed Gibbs sampler
- Variable Selection for Clustering with Gaussian Mixture Models
- The EM Algorithm and Extensions, 2E
- The Making and Testing of Geographic Gene-Frequency Maps
- Exploratory latent structure analysis using both identifiable and unidentifiable models
- A Framework for Feature Selection in Clustering
- The Bayesian Choice
- Bayesian Variable Selection in Clustering High-Dimensional Data
- Variable Selection for Model-Based Clustering