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Support Vector Hazards Machine: A Counting Process Framework for Learning Risk Scores for Censored Outcomes
Learning risk scores to predict dichotomous or continuous outcomes using machine learning approaches has been studied extensively. However, how to learn risk scores for time-to-event outcomes subject to right censoring has received little attention until recently. Existing approaches rely on inverse...
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| Published in: | J Mach Learn Res |
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| Main Authors: | , , |
| Format: | Artigo |
| Language: | Inglês |
| Published: |
2016
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| Subjects: | |
| Online Access: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5210213/ https://ncbi.nlm.nih.gov/pubmed/28066157 |
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