How can I set the normalization of the performance parameter in training a neural network?

hey, I am using the neural network toolbox. I am training a feedforward network with two outputs. The two have different dimension I need to normalize the performance parameter (mean squared error) to let them have the same 'weight' during the training. I do it with this line:

net.performParam.normalization = 'normalized';

The problem is that after the train if I go to chek the value of that parameter (net.performParam) it results as 'none', meaning it did not set 'normalized', and I cannot understand if it worked. how can I solve this problem? here I report the code in question:

net=feedforwardnet;
net=configure(net,x,t);
trainFcn = 'trainlm';
hiddenLayerSize = 22;
net = feedforwardnet(hiddenLayerSize,trainFcn);
net.performParam.normalization = 'normalized';
net.performFcn = 'mse';
[net,tr] = train(net,x,t);

[Greg Heath]

 1. ALWAYS BEGIN WITH DOCUMENTATION EXAMPLES

 a. For classification/pattern-recognition 
    help patternnet
    doc patternnet

 b. For regression/curve-fitting
    help fitnet
    doc fitnet

 c. Both call feedforwardnet with appropriate default 
settings

2. Since these can be improved check the NEWSGROUP using

 greg quickies

3.Finally, for more serious work, search BOTH NEWSGROUP and ANSWERS using

                                HITS
                        NEWSGROUP  ANSWERS
a. patternet Hmin Hmax     4        35

or

 b.fitnet Hmin Hmax        12        42

Answer 1

[Kamuran Turksoy]

net.performParam.normalization does not have an option of 'normalized'. It has three options:

 'none' (default: no normalization), 'standard' or 'percent'.

In your code you would get error if you switch the below two lines:

 net.performParam.normalization = 'normalized';
 net.performFcn = 'mse';

to

 net.performFcn = 'mse';
 net.performParam.normalization = 'normalized';

Since the default option of mse is 'none', when you define mse after performParam.normalization you overwrite it to be none.

Try this

 net.performFcn = 'mse';
 net.performParam.normalization = 'percent' or 'standard';

Check the link below for more information:

https://www.mathworks.com/help/nnet/ref/mse.html

[Greg Heath]

Why are you changing anything except the number of hidden nodes???

The other default values suffice 99.99% of the time

Greg

[Marco Giuliani]

You are totally right Kamuran, I figured it out later using the code. I was using 'normalized' instead of 'standard' because I was using a 2011 version of matlab (and at that time the options were 'normalized' or 'percent'). By the way Greg, you need to set that option in case you have more than one output with different units. In that case, the bigger (numerically) will have an higher impact in the measure of the mse.

Answer 2

[Greg Heath]

1. You do not have to worry about normalizaion. It is a default.

2. Accept all defaults except the number of hidden nodes.

3. Create an outer for loop over hidden nodes h = Hmin:dH:Hmax

4. Create an inner loop over Ntrials configurations for random initial weights

5. Search for some of my examples

                                 HITS
                       NEWSGROUP     ANSWERS

 FITNET Hmin Hmax        12            41

Hope this helps

THANK YOU FOR FORMALLY ACCEPTING MY ANSWER

GREG