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So let's say you have determined the optimal number of layers/neurons for your neural network. When it comes time to re-train your network with new data values (the inputs are the same, just newer data for the inputs), would the optimal number of layers/neurons need to be determined again, or would the previous numbers be sufficient for re-training?

I do not have formal training in neural networks and I don't have a background in statistics, but from the answers in the post How to set the number of neurons and layers in neural networks I get the strong indication layers/neurons describe the complexity of the relationships between the inputs/outputs and I can surmise that as long as those relationships hold in the new data, determining the optimal layers/neurons is not needed before re-training, but I'd like some more experienced opinions or facts.

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