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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...

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Библиографические подробности
Опубликовано в: :Quant Biosci
Главные авторы: Wang, Hong, Li, Gang
Формат: Artigo
Язык:Inglês
Опубликовано: 2017
Предметы:
Online-ссылка: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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