The way the following usage has been covered (from the documentation), it is only possible to use detect() for detecting anomalies within the time series that it has been trained with. How do we save a trained model and pass new incoming data to the detector?
def detect_anomaly(series, threshold, mag_window, score_window, sensitivity, detect_mode, batch_size):
detector = SpectralResidual(series=series, threshold=threshold, mag_window=mag_window, score_window=score_window,
sensitivity=sensitivity, detect_mode=detect_mode, batch_size=batch_size)
return detector.detect()
The way the following usage has been covered (from the documentation), it is only possible to use
detect()for detecting anomalies within the time series that it has been trained with. How do we save a trained model and pass new incoming data to the detector?