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)...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2016-05-01
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| Series: | International Journal of Environmental Research and Public Health |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1660-4601/13/5/509 |