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Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions
We propose a novel method for multiple clustering, which is useful for analysis of high-dimensional data containing heterogeneous types of features. Our method is based on nonparametric Bayesian mixture models in which features are automatically partitioned (into views) for each clustering solution....
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| Publicado no: | PLoS One |
|---|---|
| Main Authors: | , , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Public Library of Science
2017
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5648298/ https://ncbi.nlm.nih.gov/pubmed/29049392 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0186566 |
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