How to divide the data using "divideblock" for training and testing , excluding validation dataset in NAR network for time series prediction.
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I am using NAR network for time series prediction. I have to divide my datset of 133 time points into training and tetsing dataset uisng "divideblock". I want first 106 points for training and the rest for testing. I am getting the error "Attempted to access valInd(0); index must be a positive integer or logical.
Error in divideblock>divide_indices testInd = (1:numTest)+valInd(end);
Error in divideblock [out1,out2,out3] = divide_indices(in1,params);".
Here is my code:
targetSeries = tonndata(untitled,false,false);
feedbackDelays = 1:1; hiddenLayerSize = 10; net = narnet(feedbackDelays,hiddenLayerSize);
net.inputs{1}.processFcns = {'removeconstantrows','mapminmax'}; [inputs,inputStates,layerStates,targets] = preparets(net,{},{},targetSeries);
net.divideFcn = 'divideblock'; [trainInd,valInd,testInd] = divideblock(133,0.8,0,0.2)
net.divideMode = 'time'; % Divide up every value net.divideParam.trainRatio = 80/100; net.divideParam.valRatio = 0/100; net.divideParam.testRatio = 20/100;
net.trainFcn = 'trainlm'; % Levenberg-Marquardt
net.performFcn = 'mse'; % Mean squared error
net.plotFcns = {'plotperform','plottrainstate','plotresponse','ploterrcorr', 'plotinerrcorr'};
[net,tr] = train(net,inputs,targets,inputStates,layerStates);
outputs = net(inputs,inputStates,layerStates);
errors = gsubtract(targets,outputs);
performance = perform(net,targets,outputs)
trainTargets = gmultiply(targets,tr.trainMask);
valTargets = gmultiply(targets,tr.valMask);
testTargets = gmultiply(targets,tr.testMask);
trainPerformance = perform(net,trainTargets,outputs)
valPerformance = perform(net,valTargets,outputs)
testPerformance = perform(net,testTargets,outputs)
view(net)
netc = closeloop(net); [xc,xic,aic,tc] = preparets(netc,{},{},targetSeries); yc = netc(xc,xic,aic); perfc = perform(net,tc,yc)
nets = removedelay(net);
[xs,xis,ais,ts] = preparets(nets,{},{},targetSeries);
ys = nets(xs,xis,ais);
closedLoopPerformance = perform(net,tc,yc)
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Antworten (1)
Kazi Tamaddun
am 17 Mai 2018
Bearbeitet: Kazi Tamaddun
am 17 Mai 2018
Your valRatio cannot be zero. You can make your testRatio to be zero if you want.
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