MATLAB: Neural Network tool box

Deep Learning Toolboxduplicate postneural network

my pattern P size is 180*15 and target T size is 15*15.
   Create a network : mynet=newff(P,T,[80],{'logsig' 'logsig'},'traingdx'); 
  train it : mynet=train(mynet,P,T);
However I get different result at different time of executing the script. is it the nature of neural network???

Best Answer

Default trn/val/tst data division and initial weights are random. To duplicate runs you have to initialize the RNG to the same initial state as before
 help rng
 doc rng
WARNING: YOUR PROBLEM IS VERY, VERY ILL-POSED
 [ I N ] = size(P )            % [ 180 15 ]
 [ O N ] = size(T)             % [ 15 15  ]
 Ntrn    = N -2*round(0.15*N)  % DEFAULT: 11 training (2 validation and 2 test) examples
 Ntrneq  = Ntrn*O              % 165 training equations
 H       = 80                  % 80 hidden nodes
 Nw      = (I+1)*H+(H+1)*O     % 181*80+81*15 = 15,695 unknown weights
1. You are trying to define an I= 180 dimensional space with only Ntrn = 11 training examples. 11 examples define at most a 10 dimensional space. Even if you used all 15 examples for training, you could only define, at most, a 14 dimensional space.
2. It is desirable to have MANY MORE training examples than twice the dimensionality of the input space. SUGGESTION: Get more examples and/or reduce the dimensionality of your input by projecting your inputs onto a smaller dimensional basis.
3. You are seeking accurate estimates of 15,695 unknown weights with only 165 training equations.
4. Ideally
 a. N >> I,O
 b. Ntrneq >> Nw  <==>  H << Hub = -1+ceil((Ntrneq-O)/(I+O+1))
If you explain in more detail P,I, T and O, perhaps we can give you better advice and relevant references.
Hope this helps.
Thank you for formally accepting my answer
Greg
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