Evaluation of Feature Selection Methods for Preserving Machine Learning Performance in the Presence of Temporal Dataset Shift in Clinical Medicine.

Joshua Lemmon,Lin Lawrence Guo,Jose Posada,Stephen R Pfohl,Jason Fries,Scott Lanyon Fleming,Catherine Aftandilian,Nigam Shah,Lillian Sung

Methods of information in medicine（2023）

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摘要

While model retraining can mitigate the impact of temporal dataset shift on parsimonious models produced by L1 and ROAR, new methods are required to proactively improve temporal robustness.

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关键词

dataset shift,machine learning,clinical outcomes,feature selection

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