Specify a drift detector — drift

Creates an inert detector specification (analogous to a parsnip model spec). Nothing is computed until fit() is called on a baseline period.

Usage

drift_detector(method = "ddm", ..., seed = NULL, keep = 10000)

Arguments

method: Name of a registered detection method, e.g. "ddm".
...: Method hyperparameters overriding the defaults (e.g. min_instances = 50 for "ddm"). Unknown parameters and values outside a parameter's valid range error. A few hyperparameters are thresholds on the signal's own scale rather than dimensionless, notably epsilon_prime for "seed", whose default (0.01) suits a 0/1 error stream; on a numeric stream of a different magnitude, scale it to match.
seed: NULL (default) or a single whole number. When set, the detector draws from its own private random stream, carried inside the fitted object: results are reproducible, do not depend on how the stream is split into batches, and the session's global RNG is left untouched. Only "kswin" and "seqdrift2" are stochastic. With NULL they draw from the global RNG, so call set.seed() yourself for reproducibility.
keep: Number of most recent annotated rows retained in the fitted object's history (default 10000), bounding memory and the cost of each advance() on long-running streams. Totals in glance() and drift points in tidy() are tracked separately and stay exact whatever keep is. Inf keeps everything and 0 keeps nothing; both warn.

Value

A drift_detector specification object.

Warning and drift flags

Every detector annotates each observation with .warning and .drift under one contract. NA: the detector cannot judge this observation yet — it is warming up, which also happens again right after a detected drift resets it. FALSE: the detector is active and has not flagged drift as of this observation; note that "adwin", "seed" and "seqdrift2" run their test only on a clock or at block boundaries, so between tests they carry the previous verdict forward. TRUE: it flagged drift here. Detectors with no warning level ("ewma", "page_hinkley", "cusum", "kswin", "adwin", "seed", "seqdrift2", "fhddms", "mddm_a", "mddm_g", "mddm_e") always give .warning = NA. Use which(.drift) or dplyr::filter(.drift), which skip NA; any(.drift) needs na.rm = TRUE.

Examples

drift_detector("ddm", min_instances = 50)
#> Drift Detector Specification (ddm)
#>   min_instances: 50
#>   warning_level: 2
#>   out_control_level: 3
#>   keep: 10000