Non-parametric clustering over user features and latent behavioral functions with dual-view mixture models

DOI10.1007/s00180-016-0668-0zbMath1417.62174arXiv1812.07360OpenAlexW2460484967MaRDI QIDQ2358914

Marie Guégan, Alberto Lumbreras, Bertrand Jouve, Julien Velcin

Publication date: 27 June 2017

Published in: Computational Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1812.07360

zbMATH Keywords

model-based clusteringmulti-view clusteringChinese restaurant process (CRP)Dirichlet process (DP)

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (1)

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Uses Software

• mclust
• R
• CODA

Cites Work

• Efficient Clustering for Orders
• Adaptive Rejection Sampling for Gibbs Sampling
• Model-Based Clustering, Classification, and Density Estimation Using mclust in R

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