Do we need to reinitialized the weight using "init(net)" to reinitialized the weights in ANN training loop?
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Hi, i need help on whether should re-initialized the weight when looping the training for different neurons number? will the training function re-initialized the weight by defautlt? the code i used are as follows. thank you very much.
N = [5 10 15 20 25 30 35 40 45 50 55 60];
trainFcn = 'trainlm'; % Levenberg-Marquardt backpropagation.
%name the ANN NNxxpts
NNVFBRReal200_5_to_60_all = cell(length(N),1) ;
P = zeros(length(N),1) ;
for i = 1:length(N)
% Create a Fitting Network & set number of neurons
hiddenLayerSize = N(i);
net = init(net);
net = fitnet(hiddenLayerSize,trainFcn);
net.performFcn = 'mse'; % Mean Squared Error
% Choose Plot Functions
net.plotFcns = {'plotperform','plottrainstate','ploterrhist', ...
'plotregression'};
[net,tr] = train(net,X,T);
nntraintool
NNVFBRReal200_5_to_60_all{i} = net ;
testX = X(:,tr.testInd);
testT = T(:,tr.testInd);
testY = net(testX);
perf = mse(net,testT,testY) ;
P(i) = perf ;
end as i encountered very high MSE when using trainBr. as below.
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/197932/image.jpeg)
please help. however , in another case, it only occured at neurons = 35
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/197933/image.jpeg)
Please help. thanks
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