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Fast approximate inference for variable selection in Dirichlet process mixtures, with an application to pan-cancer proteomics
The Dirichlet Process (DP) mixture model has become a popular choice for model-based clustering, largely because it allows the number of clusters to be inferred. The sequential updating and greedy search (SUGS) algorithm (Wang & Dunson, 2011) was proposed as a fast method for performing approxim...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7614016/ https://www.ncbi.nlm.nih.gov/pubmed/31829970 http://dx.doi.org/10.1515/sagmb-2018-0065 |