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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Detalles Bibliográficos
Autores principales: Yosefian, Iman, Mosa Farkhani, Ehsan, Baneshi, Mohammad Reza
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2015
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4698527/
https://www.ncbi.nlm.nih.gov/pubmed/26858773
http://dx.doi.org/10.1155/2015/576413

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4698527/
https://www.ncbi.nlm.nih.gov/pubmed/26858773
http://dx.doi.org/10.1155/2015/576413

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