自动ML死亡率预测算法的易感性,以模拟COVID大流行引起的模型漂移

Simone Maria Kagerbauer1,2, Bernhard Ulm3,4, Armin Horst Podtschaske3

  • 1Department of Anaesthesiology and Intensive Care Medicine, School of Medicine, Technical University of Munich, Munich, Germany. simone.kagerbauer@uni-ulm.de.

概括

机器学习 (ML) 模型在COVID大流行期间因数据漂移而退化. 简单的训练修改并不能防止性能损失,这突显了对ML模型的持续监测的需要.

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