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Machine learning models and over-fitting considerations
Machine learning models may outperform traditional statistical regression algorithms for predicting clinical outcomes. Proper validation of building such models and tuning their underlying algorithms is necessary to avoid over-fitting and poor generalizability, which smaller datasets can be more pro...
Autores principales: | Charilaou, Paris, Battat, Robert |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8905023/ https://www.ncbi.nlm.nih.gov/pubmed/35316964 http://dx.doi.org/10.3748/wjg.v28.i5.605 |
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