MATLAB: Neural Network performance generalization

Question

Hi to everybody! I´ve been trainning a neural network with above 9000 samples. My "divideParam" have been 50%/25%/25% for trainning, validation and test. After the trainning, regression plots show it is better than 0.999 for both of them. But, when I simulate my network with new input that the network "has not seen before",its performance fall down dramatically, becoming unacceptable. I wonder what´s the matter, and how can I check if it´s possible to improve the network or this kind of procedure (ANN), it´s not appropiate for this problem. Thanks for all!

Answer 1

Either

your new data cannot be assumed to be a random sample from the same probability distribution as the trn/val/tst data

Or (much less likely)

you have too many hidden nodes and have memorized the training data.

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Hope this helps.

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Greg