I checked the documentation and the forum messages but I still have some points about the role of the classifier I’m not sure I have understood.
As I understood, the role of the classifier is mostly to interpret the activation pattern coming from the Temporal Memory region (that is, in some ways, convert it to a dense representation that we can use outside the HTM). But as I see we also use it to make associations between the current activation pattern and future values at different time steps. Why do we use the classifier to make predictions ? I thought it was the role of the temporal memory to make predictions about the next activation pattern at time step t+1. I’m confused because when using the classifier, I have the impression to bypass what the Temporal Memory region is already doing for the next time step.
My second question is : can we use the classifier to interpret only the activation and prediction patterns returned by the Temporal Memory region, without predicting the next time steps ? If we initialize it with 0 for the steps parameter, do we have an interpretation of what the Temporal Memory is currently returning at time step t ?