Breaking the curse of dimensionality: hierarchical Bayesian network model for multi-view clustering

DOI10.1007/s10472-021-09749-zOpenAlexW3159528373MaRDI QIDQ824998

Hasna Njah, Walid Mahdi, Salma Jamoussi

Publication date: 17 December 2021

Published in: Annals of Mathematics and Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10472-021-09749-z

zbMATH Keywords

high-dimensional datahierarchical Bayesian networklatent modelmulti-view clustering

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Probabilistic graphical models (62H22)

Cites Work

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• Model-based multidimensional clustering of categorical data
• Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
• Causation, prediction, and search
• On Using Principal Components Before Separating a Mixture of Two Multivariate Normal Distributions
• A Survey on Latent Tree Models and Applications
• Discussion of ``Influential features PCA for high dimensional clustering