How to Show the Weight or Bias in a Neural Network?

How to show the weight/bias from every layer in my neural network? I am doing a feedforward neural network with 2 hidden layers. Furthermore, how to determine how many hidden layers should I use in a neural network? Currently I have 3 inputs and 1 output. When I want to increase the hidden layer to 3, an error occurred saying that I have not sufficient of input for 3 hidden layers.

[Shani]

I am trying to create a neural network, would you have any notes that I can use to aid me with that at all? please

Answer 1

[Greg Heath]

1. If the input/output transformation function is reasonably well behaved, 1 hidden layer is sufficient. The resulting net is a universal approximator.

2. However, if you need a ridiculously high number of hidden nodes, H, ( especially if the number of unknown weights Nw = (I+1)*H+(H+1)*O approaches or exceeds the number of training equations Ntrneq = Ntrn*O), you can reduce the total number of nodes by introducing a second hidden layer.

 [ I Ntrn ] = size(trninput) 

 [ O Ntrn  ] = size(trntarget)

3. Nevertheless, it is usually better to stick with 1 hidden layer and use a validation stopping subset (the default) and/or a regularized objective function (an option of mse: help mse) or a regularization training function (help trainbr)

4. Sometimes a ridiculously high number of weights is the result of using a ridiculously high number of inputs. So, it may be worthwhile to consider input subset selection before resorting to a second hidden layer.

For a single hidden layer

 weights = getwb(net)
         = [ Iw(:); b1(:); Lw(:); b2(:) ]

where

 Iw = cell2net(net.IW)
 b1  = cell2mat(net.b(1))
 Lw = cell2mat(net.Lw)
 b2 = cell2mat(net.b(2))

You can try an example if you want to see how getwb orders weights with 2 hidden layers.

Hope this helps.

Thank you for formally accepting my answer

Greg

[Sai Kumar Dwivedi]

The explanation you gave on your 2nd point

   (I+1)*H+(H+1)*O < Ntrn*O

Is this some kind of heuristic or does it have mathematical background?

[Aswany]

what about a neural network with 7 number of hidden layers?

Answer 2

[Manu R]

Neural net objects in MATLAB have fields you can access to determine layer weights and biases.

Suppose:

mynet = feedforwardnet % Just a toy example, without any training
weights = mynet.LW
biases = mynet.b

   % weight and bias values:
   %
   %             IW: {2x1 cell} containing 1 input weight matrix
   %             LW: {2x2 cell} containing 1 layer weight matrix
   %              b: {2x1 cell} containing 2 bias vectors

[Kai Hao Then]

There should be numbers showing the weights and bias. The link you have shown me doesn't provide the way to show the weights and biases but the information only. Is there any other way?

[Rahul]

Display "weights" in this example and it will show numbers.

Answer 3

[Rahul]

or open "weights" in the Workspace.