Dimension-Calibrated Unexplained Mass: An Interpretable Drift Statistic for Contamination Monitoring in Data Streams
Drift detectors that work tend not to explain themselves, and drift detectors that explain themselves tend to fail in high dimension. We close that gap for Gaussian mixture models (GMMs): each fitted component is a named "regime," and the fraction of a stream window matching no regime -- its unexplained mass -- is a drift signal that is simultaneously its own explanation. We identify why this statistic collapses in high dimension and repair it. Under a correct component a normal point in d dimensions lies about sqrt(d) sigma from the mean, so once d exceeds 9 essentially every point exceeds a fixed 3-sigma radius: window-level ROC-AUC is exactly 0.50 on Satellite (d=36) and Optdigits (d=6...
| Authors | Behnam Asadi |
|---|---|
| Primary category | cs.LG |
| Published | 18 July 2026 |
| Last updated at source | 12 August 2026 |
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