In our current architecture, you can only choose one predicted field to make predictions for per model. So if you are attempting to create live predictions for each sensor on the device, you would need 8 models, one for each sensor stream.
I may have to look at this in order to limit the processing, but for now HTM.java doesn’t have this limitation. HTM.java instead creates 8 classifiers and you can access their Classifications by field name from the Inference object that comes out of the end of the Network.
I would like to ask a Numenta engineer whether I should limit this because it will create a Classifier for every field by default?