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Feature selection for high-dimensional temporal data
BACKGROUND: Feature selection is commonly employed for identifying collectively-predictive biomarkers and biosignatures; it facilitates the construction of small statistical models that are easier to verify, visualize, and comprehend while providing insight to the human expert. In this work we exten...
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| Опубликовано в: : | BMC Bioinformatics |
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| Главные авторы: | , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
BioMed Central
2018
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5778658/ https://ncbi.nlm.nih.gov/pubmed/29357817 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-018-2023-7 |
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