Runs the detector over the baseline data — the period where the monitored
model is considered stable — so it learns the reference ("normal") level.
The returned object is immutable: feed new batches with advance().
Usage
# S3 method for class 'drift_detector'
fit(object, data, signal, ...)Arguments
- object
A
drift_detector()specification.- data
A data frame with the baseline period, in temporal order.
- signal
Unquoted name of the signal column (0/1 errors for error-based methods such as
"ddm").- ...
Not used.
Examples
base <- sim_drift_stream(n_pre = 100, n_post = 0, seed = 1)
fit(drift_detector("ddm"), base, signal = error)
#> Fitted Drift Detector (ddm)
#> observations: 100 (100 baseline)
#> warnings: 10 | drifts: 0