Change in fitness function

Hi,

In a feedforward neural network, I have :

x = Inputs a = Outputs y = f(a) z = Targets

I want to do :

mse = sum((y-z)²)/length(y)

How can I do it in matlab please. Thanks

Answer 1

[Greg Heath]

Faulty notation. Typical usage is input x, target t, output y . See the documentation examples for the regression/curve-fitting function FITNET.

See PATTERNNET for classification/pattern-recognition documentation examples.

Both functions call FEEDFORWARDNET which never has to be explicitly used.

 help fitnet
 doc fitnet

 [x, t] = simplefit_dataset;
 net    = fitnet(10);
 net    = train(net,x,t);
 view(net)
 y      = net(x);
 perf   = perform(net,t,y)      % Unscaled number doesn't tell you much

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% An expanded modification. Search the NEWSGROUP and ANSWERS using

 greg fitnet

% Ending semicolons removed from selected commands so that results are automatically printed to the screen

 [ x, t ] = simplefit_data; 
 [ I N ]  = size(x)
 [ O N ]  = size(t)
  figure(1) 
  plot(x,t) % Smooth curve with two local max and mins suggest at least 4 hidden nodes (H>=4)

% MATLAB Default trn/val/tst data division ratio is 0.7/0.15/0.15

Ntrn    = N-2*round(0.15*N)  % Default No. of training examples
Ntrneq  = Ntrn*O             % No of training equations
net     = fitnet;            % Uses default of one hidden layer with H = 10 hidden nodes
Nw      = (I+1)*H+(H+1)*O    % Nw = 31 unknown weights to estimate (Nw <= Ntrneq?)

 [ net tr y e ] = train(net,x,t);
 % y = net(x);
 % e = t-y;
 NMSE = mse(e)/var(t,1)        % Normalized mean-square-error  ( NMSE < 0.01 ?)
 R2   = 1 -NMSE                % Fraction of target variance modeled by the net (R2 > 0.99 ?)

Hope this helps.

Thank you for formally accepting my answer

Greg % See Wikipedia/Rsquared

[taytob]

Thank you Greg for your answer, Your tutorials are good and can be useful but I did not find my solution.

I will try another way with right notation

if performance function of neural network can be: net.performFcn = 'mse'

How can I change de variables used in mse :

I need to change :

mse = sum((y-t)²)/length(t)

to :

mse = sum((a-t)²)/length(t)

with a = f(y)

I hope that it is more understandable.