After some serious search online I could not find any real world example of using HTM for anomaly detection.
By “real world dataset” I mean a standard, public, well tested, annotated dataset - for example this.
By “example” I mean a .py of notebook that presents how to take data, preprocess it, configure the SP and TM, training and getting at least decent results.
I am aware that there is the hotgym.py example in the git repo, but I seems that doing the same pipeline and configs with real world datasets just seems to not work properly.
I would extremely appreciative of someone could share a link for such example of even better a .py/JN of such an example.
BTW I am using HTM.Core since I wand python 3.