Problem about taking optimum performance of neural network output for pattern classification
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Hello, I am using MATLAB 2012a. I am doing 2 class classification using patternnet MATLAB for Biosignal , I am worried about the following items:
a) In the program , How can I set Initial weight and bias of input and hidden layer manually ? I am getting some abnormal/unconsistent result.
b) How i can plot MSE vs no iteraton up to 1000. I want see MSE is constant even after converge at certain iteration.?
c) How I can set optimum number of hidden neuron in the hidden layer?
d) Also, How I can do the 10 fold cross validation for the above data to get optimum error? anybody has clues/videos/ideas?
Thanks a lot.
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