Questions about real time predictions from an incoming stream of data.

[rajdeep-biswas]

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()

[ChunhanLi]

@rajdeep-biswas Hi, may I ask whether you get the answer or solution to this question now? I have same concern here and hope you can give me some suggestions.

[rajdeep-biswas]

@ChunhanLi, unfortunately no, I just moved on to other better maintained open source options such as Prophet and PyOD.