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Low-cost scalable discretization, prediction, and feature selection for complex systems
Finding reliable discrete approximations of complex systems is a key prerequisite when applying many of the most popular modeling tools. Common discretization approaches (e.g., the very popular K-means clustering) are crucially limited in terms of quality, parallelizability, and cost. We introduce a...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
American Association for the Advancement of Science
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6989146/ https://www.ncbi.nlm.nih.gov/pubmed/32064328 http://dx.doi.org/10.1126/sciadv.aaw0961 |