Hi Yesim,

That post from MSE is very old. The "HiddenLayers" sub-option for Predict has been removed. In that example "HiddenLayers" -> {4, 3, 3} means 3 fully connected linear layers with output vector sizes of 4, 3, 3.

If you want complete control over the NN then I suggest not using Predict with Method -> "NeuralNetwork". Instead build the network using specific layers in NetChain and NetGraph and then NetTrain. Each layer type has parameters that can be controlled and there are a lot of customization options for NetTrain. You will have to study the documentation.

NetChain[{4, 3, 3}] (* Equivalent to "HiddenLayers" -> {4, 3, 3} *)

You have not provided any details about the problem you are trying to solve so it is hard to provide more specific advice.

Hello Rohit,

As far as I understand, the layers given in Information["*Layer"] are layers trained for a specific task. What I am doing is training my own NN. MMA is "magically" generating me results (more or less correct) with parameters I neither know, nor have control over.

Information about hidden layers, activation functions, etc. being used in NN are important if one needs other people to repreduce the results by other means, such as TensorFlow, sklearn, etc.

Hi Yesim,

Hidden layer is not a vey useful concept. Every layer between the input and the output is a "hidden layer". WL supports many different layer types that can be used as "hidden layers"

Information["*Layer"]

They each have different attributes/parameters that can be customized.

Take a look at this overview document.