MATLAB: Neural network how to orgnize the data

Question

I have a problem with nn classification ,I have 19 different classes , each class has 20 features and each feature has 200 samples(it could be more in future), how should I orgnize the input matrix ? is it 20 x (200*19) or (20 *19) x 200 , and the target 1 x (200 * 19) is that right ? or should I use eye() as I read in some answers? another question is how to decide the most appropirate number of hidden layers(middle layers not input and output) and number of nerouns in each layer ? the last thing .. neural network provide different results each run .. is it possible to save the best run net configration and use it later to provide the same or approximated results ??

thanks in advance

Answer 1

[ I N ] = size(input) % [20 200 ]

[ O N ] = size(target) % [ 19 200 ]

If you made a mistake and each class has 200 samples then

[ I N ] = size(input) % [20 1800 ]

[ O N ] = size(target) % [ 19 1800 ]

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Hope this helps

Greg