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You are not wrong! An entire subclass of anomaly detection can basically be reduced to: forecast the next data point and then measure the forecast error when th
by diab0lic 2y ago
You are not wrong! An entire subclass of anomaly detection can basically be reduced to: forecast the next data point and then measure the forecast error when the data point arrives.
- deleted 2y ago[deleted]
- fnordpiglet 2y agoWell it doesn’t really require a forecast - variance based anomaly detection doesn’t make an assertion of the next point but that its maximum change is within some band. Such models usually can’t be used to make a forecast other than the banding bounds.
- diab0lic 2y agoThat would be a different subclass of anomaly detection solutions.