The Optimal Machine Learning-Based Missing Data Imputation for the Cox Proportional Hazard Model

An adequate imputation of missing data would significantly preserve the statistical power and avoid erroneous conclusions. In the era of big data, machine learning is a great tool to infer the missing values. The root means square error (RMSE) and the proportion of falsely classified entries (PFC) a...

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Detalles Bibliográficos
Autores principales: Guo, Chao-Yu, Yang, Ying-Chen, Chen, Yi-Hau
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Public Health
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8289437/
https://www.ncbi.nlm.nih.gov/pubmed/34291028
http://dx.doi.org/10.3389/fpubh.2021.680054

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8289437/
https://www.ncbi.nlm.nih.gov/pubmed/34291028
http://dx.doi.org/10.3389/fpubh.2021.680054

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