What is the default transfer function for fitnet?

I've been trying to find out what the default network configuration settings for the fitnet function are. It's not clear exactly which of the many transfer functions were used and the documentation of the function is not explicit.

What is MATLAB's default transfer function when I use:

   train(fitnet(N), x, y)

Is it sgn? Is it tanh? What is that activation function?

Answer 1

[Greg Heath]

tansig (AKA tanh)

Thank you for formally accepting my answer

Greg

[Kevin Amaral]

Thank you for your response, Greg. Could you tell me where you determined this from? Again, as I said the documentation is not explicit or I may have missed where it has been said.

I'd like to be very sure that I'm not misrepresenting the network structure I'm using as I will be reporting on it to others for the sake of repeatability. Unfortunately, "run this experiment code in MATLAB" will not appropriately qualify.

Sorry for the delay in getting back to you on this.

Answer 2

[KAE]

Greg, do you happe to know where in the documentation it says that tansig is the default?

I can only find how to list all the available functions,

help nntransfer

or get info on tansig itself,

doc tansig

but neither states that it is the default, and if you don't already have a network in memory, I am not sure how to look this up, and think there must be a secret stash of documentation that I don't know about.

[Tilak Nanavati]

I thnk this might help.

Follow these steps:

net = fitnet;
net.layers{1}

Doing this you'll able to see something like this:

The "transferFcn" indicates the transfer function.

Neural Network Layer
 
              name: 'Hidden'
        dimensions: 10
       distanceFcn: (none)
     distanceParam: (none)
         distances: []
           initFcn: 'initnw'
       netInputFcn: 'netsum'
     netInputParam: (none)
         positions: []
             range: [10x2 double]
              size: 10
       topologyFcn: (none)
       transferFcn: 'tansig'
     transferParam: (none)
          userdata: (your custom info)

Answer 3

[KSSV]

net = fitnet(N) ;

Check net, it will be a class of network. In that type net.Layers{i}, where i = 1,2...if you have only one hidden layer. In that you can fin the activation function and other details.

Answer 4

[Greg Heath]

%If you want to know network details, just remove ending semicolons on a succession of commands

 net = fitnet

%Then scrolling down see the layers term?

layers: {2x1 cell array of 2 layers}

% Therefore, continuing command by command

hiddenlayerproperties = net.layers{1}

outputlayerproperties = net.layers{2}

Hope this helps

Thank you for formally accepting my answer

Greg