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What is the bug?
Anomaly detection results also display past values when we have cases where we detected late anomalies.
The past_values is the actual input that triggered an anomaly. If past_values is not null, then the attributions or expected values are from a past input. This however can cause some incorrect situation on our visualization because it would attribute an anomaly that happened two intervals ago (T-2) to the current time, it also would mean that if current value is also anomalous (T-0) we will see that anomaly displayed later on T+2 for example.
What is the bug?
Anomaly detection results also display past values when we have cases where we detected late anomalies.
The
past_values
is the actual input that triggered an anomaly. If past_values is not null, then the attributions or expected values are from a past input. This however can cause some incorrect situation on our visualization because it would attribute an anomaly that happened two intervals ago (T-2) to the current time, it also would mean that if current value is also anomalous (T-0) we will see that anomaly displayed later on T+2 for example.explanation of late anomalies can be found here: https://opensearch.org/docs/latest/observing-your-data/ad/result-mapping/
How can one reproduce the bug?
Do you have any additional context?
Add any other context about the problem.
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