I am trying to build predictive models for 2 outputs given approximately 10 input variables.
I understand that I would first look at the simplest model, such as a multivariate linear regression, then to build neural networks (e.g. 1 hidden layer) and progressively move on to deeper hierarchies.
I have 2 questions:
1) Consider the 3 neural network architectures below: Each model attempts to predict 2 outputs given a bunch of predictors (input, independent variables). Which would be ideal?
2) How do I decide on which is the best neural network? I have currently performed NetTrain on my data and am curious how to evaluate performance metrics within Mathematica.
Appreciate your advice.