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A Hierarchical Feature and Sample Selection Framework and Its Application for Alzheimer’s Disease Diagnosis
Classification is one of the most important tasks in machine learning. Due to feature redundancy or outliers in samples, using all available data for training a classifier may be suboptimal. For example, the Alzheimer’s disease (AD) is correlated with certain brain regions or single nucleotide polym...
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| Опубликовано в: : | Sci Rep |
|---|---|
| Главные авторы: | , , , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Nature Publishing Group
2017
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5372170/ https://ncbi.nlm.nih.gov/pubmed/28358032 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/srep45269 |
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