Hello everybody,
Related to some research I'm doing, I need to devise a way to get high-order (multistep) cellular activation predictions out of the TM algorithm. As I understand it, the TM algorithm only outputs cellular activation predictions for the very next time step. I know there exists a bunch of support for getting multistep scalar or class predictions but that's not what I'm after here. One thing I was thinking was feeding the predictions that come out of the TM algorithm right back into the TM's input. This would be like assuming the predictions were 100% correct and then seeing what cells would get put in a predictive state next if those first order predictions were 100% correct. This could be repeated n times to get n high-order cellular activation predictions. Thoughts? Best, Brody --- [Visit Topic](https://discourse.numenta.org/t/getting-high-order-predictions-of-cellular-activations/3000/1) or reply to this email to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discourse.numenta.org/email/unsubscribe/44617f6f28f2d4cc4252519080bf67e7abc6da6062797c05276b59c580e8fcf4).
