Alexandra asked . 2021-08-04

Can I initialize feedforward net with 'midpoint'?

Hello! I am testing different topologies of the multilayer perceptron in order to get the best one and I would like to avoid randomness in intial conditions in this case: therefore I would like to have all the networks the similar if not the same initial conditions.

However, as I have learnt feedforwardnet has built in Nguyen-Widrow initialization algorithm which delivers each time different result. I also found out that it is possible to set manually the initialization algorithm I want (for example 'midpoint'), however, I am having difficulties to do it for the network, where I change the topology and consequently number of links, weights and biases.

Maybe there is a way to change existing initialization algorithm to another one for the whole network at once?

initialization , neural network , feedforwardnet

Expert Answer

Kshitij Singh answered . 2024-12-20 18:48:51

1. It doesn't matter how MATLAB initializes your net. You can always override the initialization using

 help setwb
 doc setwb
 type setwb

2. Initializations are not random. They are pseudo-random. That means if you save the state of the rng, the initialization can be duplicated.

3. What different topologies are you considering? You do know that a single hidden layer MLP is a universal approximator? The only reason to use two or more hidden layers is to reduce the total number of unknown weights and thresholds. For a given training set size, the design is more stable and better able to generalize to nontraining data the fewer the number of unknown weights.

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