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Application of Random Forest Survival Models to Increase Generalizability of Decision Trees: A Case Study in Acute Myocardial Infarction
Background. Tree models provide easily interpretable prognostic tool, but instable results. Two approaches to enhance the generalizability of the results are pruning and random survival forest (RSF). The aim of this study is to assess the generalizability of saturated tree (ST), pruned tree (PT), an...
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| Publicado no: | Comput Math Methods Med |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Hindawi Publishing Corporation
2015
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4698527/ https://ncbi.nlm.nih.gov/pubmed/26858773 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2015/576413 |
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