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Applications of a Novel Clustering Approach Using Non-Negative Matrix Factorization to Environmental Research in Public Health
Often data can be represented as a matrix, e.g., observations as rows and variables as columns, or as a doubly classified contingency table. Researchers may be interested in clustering the observations, the variables, or both. If the data is non-negative, then Non-negative Matrix Factorization (NMF)...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2016
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4881134/ https://www.ncbi.nlm.nih.gov/pubmed/27213413 http://dx.doi.org/10.3390/ijerph13050509 |