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Optimal clustering under uncertainty
Classical clustering algorithms typically either lack an underlying probability framework to make them predictive or focus on parameter estimation rather than defining and minimizing a notion of error. Recent work addresses these issues by developing a probabilistic framework based on the theory of...
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| Publicado no: | PLoS One |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Public Library of Science
2018
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6168142/ https://ncbi.nlm.nih.gov/pubmed/30278063 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0204627 |
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