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Classification of high dimensional biomedical data based on feature selection using redundant removal
High dimensional biomedical data contain tens of thousands of features, accurate and effective identification of the core features in these data can be used to assist diagnose related diseases. However, there are often a large number of irrelevant or redundant features in biomedical data, which seri...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Public Library of Science
2019
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6456288/ https://www.ncbi.nlm.nih.gov/pubmed/30964868 http://dx.doi.org/10.1371/journal.pone.0214406 |