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Random Forests for Genomic Data Analysis
Random forests (RF) is a popular tree-based ensemble machine learning tool that is highly data adaptive, applies to “large p, small n” problems, and is able to account for correlation as well as interactions among features. This makes RF particularly appealing for high-dimensional genomic data analy...
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| 主要な著者: | , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2012
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3387489/ https://ncbi.nlm.nih.gov/pubmed/22546560 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.ygeno.2012.04.003 |
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