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SCCM : Stream Cruise Control Method for Automated Drift Detection and Adaptation

arXiv · AI, language, vision and robotics · article · Sep 8, 2026 · UTC

Real-world datasets often exhibit evolving distributions, known as concept drift. Ignoring drift degrades predictive performance, while reliance on fixed hyperparameters further limits model adaptability under changing conditions. Adaptive learning addresses this challenge by continuously updating models online, allowing them to incrementally adjust and remain effective as data distributions evolve. This paper presents the Stream Cruise Control Method (SCCM), a comprehensive framework for drift detection and adaptation in online regression. SCCM enables automated adaptation through early-respo

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Evidence & attribution

arXiv · AI, language, vision and robotics · 2026-09-08T20:33:17.000Z

First collected: 2026-09-20T19:52:05.078Z. This is not the publication date.