Thank you for joining the forum.
Something you need to understand is that time is relative to an HTM system (and to all biological intelligence). How far back the TM remember will depend on many things, including the input data interval & permanence increment / decrement values. You can find a lot of these params in the TM API docs. If you are using the BacktrackingTM, there are more params you can use to control this, like maxAge, globalDecay, maxInfBacktrack, maxLrnBacktrack, etc. These are useful for time series anomaly detection.
But the most important thing to keep in mind is how you are encoding time in the input with regards to the interval data flows into the system. If you are
We can’t currently identify the exact sequences that are causing the predictions / anomaly indications without some form of pooling. For lots of discussion on this, see Exploring the "Repeating Inputs" problem.