pythonmachine-learningtensorflow

Multiple artificial neural networks

I am trying to set up a Multiple Artificial Neural Network as you can see here on image (a):

enter image description here

(source)

I want that each of the networks work independently on its own domain. The single networks must be built and trained for their specific task. The final decision will be make on the results of the individual networks, often called expert networks or agents.

Because of privacy, I could not share my data.

I try to set up this with Tensorflow in Python. Is it achievable, and if yes, how could I do it?

Solution

  • The way to go about this is to just take the outputs of the two networks and concatenate the resulting output tensors (and reshape them if needed) and then pass them into the final network. Take a look at here for the concatenation documentation and here for an example of taking the output from one network and feeding it into another. This should give you a place to start from.

    As for (a), it is simple, just train the networks before hand and load them when you are training the final network. Then do the concatenation on the outputs.