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我正在面對在MATLAB中運行龐大數據集的問題NN Toolbox-問題是 - >當我使用trainlm算法時，NN Toolbox無法運行數據並顯示內存不足錯誤，但對於其他算法則不存在內存問題。這是爲什麼？而且，當我把隱藏的神經元超過15個時，它也顯示出內存不足。如何解決這類問題？還有一件事：我把10％，45％，45％的數據劃分爲訓練驗證和測試，但是在運行代碼之後，我發現在工作空間裏它執行了25％的訓練數據，37％的數據用於驗證，和37％的數據用於測試目的。如何解決這個問題？MATLAB中的內存不足錯誤NN工具箱和訓練數據集中的數據分割問題
有沒有人有想法如何解決這類問題？我很樂意收到意見和任何建議。謝謝。
我在我的電腦上使用MATLAB的R2010b中的版本，其在Windows 7
這裏運行是我用於「訓練」之前訓練數據集
EX_355 = xlsread('Training Dataset.xlsx','B2:B435106');
EX_532 = xlsread('Training Dataset.xlsx','C2:C435106');
BA_355 = xlsread('Training Dataset.xlsx','D2:D435106');
BA_532 = xlsread('Training Dataset.xlsx','E2:E435106');
BA_1064 = xlsread('Training Dataset.xlsx','F2:F435106');
Reff = xlsread('Training Dataset.xlsx','G2:G435106');
Input(1,:) = EX_355;
Input(2,:) = EX_532;
Input(3,:) = BA_355;
Input(4,:) = BA_532;
Input(5,:) = BA_1064;
Target(1,:) = Reff;
net = feedforwardnet;
net = configure(net,Input,Target);
net = init(net);
inputs = Input;
targets = Target;
hiddenLayerSize = 10;
net = fitnet(hiddenLayerSize);
net.inputs{1}.processFcns = {'removeconstantrows','mapminmax'};
net.outputs{2}.processFcns = {'removeconstantrows','mapminmax'};
net.divideFcn = 'dividerand';
net.divideMode = 'sample';
net.divideParam.trainRatio = 10/100;
net.divideParam.valRatio = 45/100;
net.divideParam.testRatio = 45/100;
net.trainFcn = 'trainlm';
net.performFcn = 'mse';
net.plotFcns = {'plotperform','plottrainstate','ploterrhist', ... 'plotregression', 'plotfit'};
[net,tr] = train(net,inputs,targets);
outputs = net(inputs);
errors = gsubtract(targets,outputs);
performance = perform(net,targets,outputs)
trainTargets = targets .* tr.trainMask{1};
valTargets = targets .* tr.valMask{1};
testTargets = targets .* tr.testMask{1};
net.trainParam.epochs;
net.trainParam.time;
net.trainParam.goal;
net.trainParam.min_grad;
net.trainParam.mu_max;
net.trainParam.max_fail;
net.trainParam.show;