MATLAB: How to choose number of hidden layers

neural network

Hi, I want to design a neural network with 3 input and 1 output. Samples are 21 Millions. For predictions and I don't know how many hidden layers and also the network parameters to use to get best results

Best Answer

When you call patternnet, pass it a vector of the sizes of the hidden layers.

https://www.mathworks.com/help/nnet/ref/patternnet.html

Related Solutions

MATLAB: How to calculate the error in Neural Network Back Propagation Network

Use as many defaults as possible

 MSEgoal = 0.01*mean(var(target',1))
 MinGrad = MSEgoal/100
 net = newff(input,target);
 net.trainParam.goal     = MSEgoal;
 net.trainParam.min_grad = MinGrad;
 [ net tr output error ] = train(net, input, target);

For details, search ANSWERS using the search word msegoal

Hope this helps.

Greg

Thank you for formally accepting my answer

Greg

MATLAB: What is the search range of a hidden layer size in a regression task

 [ I N ] = size(x)
 [ O N ] = size(t)
 Ntrn    = N - 2*round(0.15)*N) % default
 Ntrneq  = Ntrn*O  % No of training equations
 % No. of unknown weights for an I-H-O node topology
 Nw = (I+1)*H+(H+1)*O = (I+O+1)*H + O
 % To prevent more unknowns than equations 
Nw <= Ntrneq  <=>  H <= Hub  % upper bound
 Hub = floor( ( Ntrneq-O) / ( I + O + 1) ) 
 % Depending on your prior information and the size of Hub, 
 % choose Hmin, dH and Hmax to search
h = Hmin:dH:Hmax % 0 <= Hmin <= Hmax <= Hub

For each h candidate, design multiple nets. To keep the task manageable, I usually search 10 h candidates at a time with Ntrials = 10 designs per candidate to obtain 100 designs. Sometimes it may be necessary to start with a wide search followed by one or more narrow searches.

Don't forget to choose a repeatable initial random number seed so that you can reproduce any individual design.

Choose the smallest H that satisfies your training goal. For example: if the degree-of-freedom adjusted training Rsquare, R2trna, is greater than 0.995 then 99.5% of the training target variance is modeled by the net.

I have posted zillions of examples in the NEWSGROUP and ANSWERS. Search with one or more of

 greg neural h = Hmin:dH:Hmax  Ntrials R2trna

Hope this helps.

Thank you for formally accepting my answer

Greg

Best Answer

Related Solutions

MATLAB: How to calculate the error in Neural Network Back Propagation Network

MATLAB: What is the search range of a hidden layer size in a regression task

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