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A Novel Information-Theoretic Approach for Variable Clustering and Predictive Modeling Using Dirichlet Process Mixtures
In the era of big data, there are increasing interests on clustering variables for the minimization of data redundancy and the maximization of variable relevancy. Existing clustering methods, however, depend on nontrivial assumptions about the data structure. Note that nonlinear interdependence amon...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Nature Publishing Group
2016
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5155267/ https://www.ncbi.nlm.nih.gov/pubmed/27966581 http://dx.doi.org/10.1038/srep38913 |