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Censoring Unbiased Regression Trees and Ensembles
This paper proposes a novel paradigm for building regression trees and ensemble learning in survival analysis. Generalizations of the CART and Random Forests algorithms for general loss functions, and in the latter case more general bootstrap procedures, are both introduced. These results, in combin...
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| 出版年: | J Am Stat Assoc |
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| 主要な著者: | , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2018
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6561730/ https://ncbi.nlm.nih.gov/pubmed/31190691 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/01621459.2017.1407775 |
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