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A Selective Review on Random Survival Forests for High Dimensional Data
Over the past decades, there has been considerable interest in applying statistical machine learning methods in survival analysis. Ensemble based approaches, especially random survival forests, have been developed in a variety of contexts due to their high precision and non-parametric nature. This a...
Tallennettuna:
| Julkaisussa: | Quant Biosci |
|---|---|
| Päätekijät: | , |
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
2017
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| Aiheet: | |
| Linkit: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6364686/ https://ncbi.nlm.nih.gov/pubmed/30740388 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.22283/qbs.2017.36.2.85 |
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