how many neurons should be in the hidden layer ?
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Hi all How are you ? I have a question : I have to implement the Back Propagation algorithm that teaches the neuronal network to recognize hand written digits:{2,3,4,8} in the program should be only one hidden layer of neurons it's input 15*15 image of digit it's output is 4*1 vector of resemblance to each digit above BUT: How many neurons should be in the hidden layer ? I know that the amount of hidden layer neurons strongly affects the performance of the algorithm,so if anybody knows the answer please tell me !
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the cyclist
el 31 de Ag. de 2012
I am not an expert in NN, but I know a little. One possibility, if you have enough data, would be to separate your data into a training set and a validation set. Then, train different networks with different numbers of neurons in the hidden layer (using the training set only), and see which one performs best on the validation set.
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Christos
el 31 de Ag. de 2012
i agree with the cyclist. of course its not my field but in theory you have to test some networks and also try different activation functions in the hidden layer.
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