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Allow predictions for multiple fields per model #1712
It would be nice if you could specify multiple fields to make predictions for.
This will require a change to the CLAModel to support multiple classifier regions. It currently supports only one with the region name "Classifier":
Additionally, the OPF and description.py format will need to be updated to support multiple fields to predict. It require some changes to metrics or swarming so it knows which field (or fields?) to use for optimization.
There are two implementations of the classifier, so we will need a task in nupic.core for the C++ implementation.
OPF is setup in an OO way to support different model features. Is it possible to implement this feature as a subclass of CLAModel or perhaps as a separate independent model type? This would avoid disrupting or complicating the (already overly complex) clamodel.py. The factory would be used to instantiate the correct class type and after that everything else should just work.