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Subject: Re: Question about number of layers in ANN
Date: Thu, 29 Oct 2009 08:24:06 +0000 (UTC)
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"Kloser " <kcfcheung@gmail.com> wrote in message <hcbiur$5g7$1@fred.mathworks.com>...
> Dear All
> I want to know, in Neural Networks, whether more layers will promise higher accuracy for classification?
> I have tried using two networks to classify some images into classes. There are 100 variables in each sample, meaning that there are 100 input nodes. And for the Networks, The 1-layer network have 60 output nodes, and the 2-layers network have 20 hidden nodes in the hidden layers and 60 output nodes. 
> But I found that the accuracy in the 1-layer network is higher than that in the 2-layer. I expected that the 2-layer may have higher accuracy because there are more parameters, so I am wondering whether there are bugs in my implementation. But I can't find any bugs up to now.
> So can anyone tell me if that is my wrong expectation or other reasons so I have this result? And what is the relationship between the numbers of layers and the accuracy? How should I judge the optimal numbers of layers for neural networks?
> Thank you

If you have more layers, you will have a higher accuracy for classification, but only if you have an extended training set.

If you can't train your neural network on enough inputs, adding layers won't help, on the contrary.