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High‐dimensional feature selection in competing risks modeling: A stable approach using a split‐and‐merge ensemble algorithm
Variable selection is critical in competing risks regression with high‐dimensional data. Although penalized variable selection methods and other machine learning‐based approaches have been developed, many of these methods often suffer from instability in practice. This paper proposes a novel method...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
John Wiley and Sons Inc.
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10087963/ https://www.ncbi.nlm.nih.gov/pubmed/35934836 http://dx.doi.org/10.1002/bimj.202100164 |