I am brand new to HTM. I have been reading all about it and watched all of the videos, as well as reading through the forums. I have a good conceptual grasp , but I am struggling with how to construct a network for my problem.
Here's what I want to do. I have time ordered sequences of event data. The sequences are of various lengths with a variety of events in each, but there will be many repeated or similar sequences that correspond to a higher level category. I would like to construct an HTM network that "recognizes" when it sees a pattern that it already "knows" and is able to tag the sequence as being an instance of that pattern. When it sees an unfamiliar pattern, I'd like to know that as well,
From my reading of "On Intelligence" and "BAMI" and all the videos, this seems to be exactly what the cortical algorithm is doing. In my mind I would need some way to get at the recognized neural "label" for a recognized pattern (which I could later map to an appropriate human readable label). Unfortunately it is not at all clear to me from the examples, doc, forums, etc. how to do this using the NAPI.
So am I way off base here? If not, could someone point me to some example code or general architecture / design for accomplishing this?