Why MLOps Retraining Schedules Fail — Models Don’t Forget, They Get Shocked
We fitted the Ebbinghaus forgetting curve to 555,000 real fraud transactions and got R² = −0.31 — worse than a flat line. This result explains why calendar-based retraining fails in production and introduces a practical shock-detection approach that works in real systems.
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Source: Towardsdatascience.com
Original source: https://towardsdatascience.com/why-mlops-retraining-schedules-fail-models-dont-forget-they-get-shocked/
