Article

Impact of missing data correlated with labels to be predicted in neurodegeneration classification tasks

2025-01-24

Abstract excerpt

We introduce a new subtype of ‘Missing Not at Random’ (MNAR) data, where the missingness is correlated with the labels ( y ) to be predicted, termed (y)-dependent MNAR . We demonstrate that this subtype can significantly bias the estimation of performance metrics in typical machine learning tasks. Unbiased error estimation is crucial in predictive modeling to accurately assess model performance, identify potenti...

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Literature Corpus work: c716f9ab-82f6-5a8c-80f7-f0f62e72cc71
DOI: 10.1101/2025.01.23.634117

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