| Consistency of Random Survival Forests. | |
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MedLine Citation:
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PMID: 20582150 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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We prove uniform consistency of Random Survival Forests (RSF), a newly introduced forest ensemble learner for analysis of right-censored survival data. Consistency is proven under general splitting rules, bootstrapping, and random selection of variables-that is, under true implementation of the methodology. Under this setting we show that the forest ensemble survival function converges uniformly to the true population survival function. To prove this result we make one key assumption regarding the feature space: we assume that all variables are factors. Doing so ensures that the feature space has finite cardinality and enables us to exploit counting process theory and the uniform consistency of the Kaplan-Meier survival function. |
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Authors:
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Hemant Ishwaran; Udaya B Kogalur |
Publication Detail:
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Type: JOURNAL ARTICLE |
Journal Detail:
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Title: Statistics & probability letters Volume: 80 ISSN: 0167-7152 ISO Abbreviation: - Publication Date: 2010 Jul |
Date Detail:
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Created Date: 2010-6-28 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101317307 Medline TA: Stat Probab Lett Country: - |
Other Details:
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Languages: ENG Pagination: 1056-1064 Citation Subset: - |
Affiliation:
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Cleveland Clinic. |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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| Grant Support | |
ID/Acronym/Agency:
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UL1 RR024989-01//NCRR NIH HHS; UL1 RR024989-02//NCRR NIH HHS |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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