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From here to infinity: sparse finite versus Dirichlet process mixtures in model-based clustering
In model-based clustering mixture models are used to group data points into clusters. A useful concept introduced for Gaussian mixtures by Malsiner Walli et al. (Stat Comput 26:303–324, 2016) are sparse finite mixtures, where the prior distribution on the weight distribution of a mixture with K comp...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer Berlin Heidelberg
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6448299/ https://www.ncbi.nlm.nih.gov/pubmed/31007770 http://dx.doi.org/10.1007/s11634-018-0329-y |