I was trying to apply oja’s rule with toy data, but I can’t seem to find any examples where the input to two different ensembles is data as opposed to a function.
The only examples I could find were these (which hopefully clarify what I mean): https://github.com/s72sue/std_neural_nets/blob/master/classification/3-class_classification.ipynb
However when I attempt to create a simplified version, I keep getting the following error:
----> 9 return [input_ex[t], input_ex[t], input_ex[t],input_ex[t]]
only integers, slices (
:), ellipsis (
...), numpy.newaxis (
None) and integer or boolean arrays are valid indices
As a future follow up, is it possible to have weights learn via backprop (DL) and local rules? Would I have to use the deepRL version?
Anyway, any help is appreciated,