Comparing variable and feature selection strategies for prediction - protocol of a simulation study in low-dimensional transplantation data.

The integration of machine learning methodologies has become prevalent in the development of clinical prediction models, often suggesting superior performance compared to traditional statistical techniques. Within the scope of low-dimensional datasets, encompassing both classical and machine learnin...

詳細記述

書誌詳細

主要な著者:	Linard Hoessly, Jaromil Frossard, Simon Schwab, Frédérique Chammartin, Alexander Leichtle, Peter Werner Schreiber, Dionysios Neofytos, Michael Koller, with the Swiss Transplant Cohort Study (STCS)
フォーマット:	Artigo
言語:	Inglês
出版事項:	Public Library of Science (PLoS) 2025-01-01
シリーズ:	PLoS ONE
オンライン･アクセス:	https://doi.org/10.1371/journal.pone.0328696
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