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When to Retrain after Drift: A Data-Only Test of Post-Drift Data Size Sufficiency
Sudden concept drift makes previously trained predictors unreliable, yet deciding when to retrain and what post-drift data size is sufficient is rarely addressed. We propose CALIPER - a detector- and model-agnostic, data-only test that estimates the post-drift data size required for stable retrainin
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