MATLAB: Change in fitness function

fitness functionMATLABneural networktutorial

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

Best Answer

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
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