MATLAB: How i could use too large data sets in neural networks ?

neural networkregression

I'm using neural networks in making regression and I want to use it in training large data sets with output data more than the input >> in the below code I've got an input of [12*480] and the output is a [1*905] cell array each cell has a matrix of [12*3], each time I run the code it gives me an errors that "Output data size does not match net.outputs{2}.size", please help me for repairing this error, thanx in advance.
A=[];
for j=1:905
k=rand(12,3);
A=[A,{k}]
end
P= rand(12,480)'
net=newff(minmax(P), [20,5], {'tansig','purelin'},'trainlm');
net.trainParam.show = 50; 
net.trainParam.lr = 0.05;
net.trainParam.epochs =1000; 
net.trainParam.goal = 1e-3; 
Nets=[];
for bi=1:905
  T=A{:,bi}';
  net1=train(net,P,T);
  Nets=[Nets,{net1}];
end
at the end of the simulation the variable Nets should have 905 model each with [12*3] network

Best Answer

In https://www.mathworks.com/matlabcentral/answers/77741-newff-create-a-feed-forward-backpropagation-network-obsoleted-in-r2010b-nnet-7-0 Greg Heath says that the syntax of newff that you are using is "very obsolete"
You should consider recoding in terms of the newer function newfit()
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