Label-shift vs concept-drift experiments and a lightweight logit-offset adapter for prevalence shift in binary classification.
python machine-learning calibration auc resampling binary-classification concept-drift imbalanced-data precision-recall cost-sensitive-learning label-shift effective-sample-size dataset-shift prior-shift experiment-reproducibility
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Updated
Oct 6, 2026 - Python