ما معنى Drift detector, Page–Hinkley test, adaptive windowing؟

A drift detector watches a statistic of a model in production (its errors, its gains, a feature’s distribution) and raises an alarm when the statistic’s distribution appears to have changed. The Page–Hinkley test accumulates the deviations of the monitored value below its running mean, less a tolerance $\delta$, and alarms when the sum rises more than $h$ above its running minimum (Page, 1954; Hinkley, 1971). Adaptive windowing (ADWIN) keeps a window of recent values and drops its older part whenever some split of the window into two sub-windows has means further apart than a Hoeffding-type bound at confidence $\delta$ (Bifet and Gavaldà, 2007).