Time Series and input layer Error
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XTrain = dataTrainStandardized(1:end-1);
YTrain = dataTrainStandardized(2:end);
numFeatures = 1;
numResponses = 1;
numHiddenUnits = 200;
layers = [ ...
sequenceInputLayer(numFeatures)
lstmLayer(numHiddenUnits)
fullyConnectedLayer(numResponses)
regressionLayer];
options = trainingOptions('adam', ...
'MaxEpochs',250, ...
'GradientThreshold',1, ...
'InitialLearnRate',0.005, ...
'LearnRateSchedule','piecewise', ...
'LearnRateDropPeriod',125, ...
'LearnRateDropFactor',0.2, ...
'Verbose',0, ...
'Plots','training-progress');
net = trainNetwork(XTrain,YTrain,layers,options);
net = trainNetwork(XTrain,YTrain,layers,options); >>>> ***Error using trainNetwork (The training sequence are of feature dimention 5353 but the input layer expects sequences of feature dimention 1).
I'm trying to work a collegues code from a previous MLab version. Since I'm using R2019a, is there an issue with the DAGNetwork because it's crashing at "iThrowCNNException( e );
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Divya Gaddipati
2019-8-5
0 个投票
From the error you received, I can see that your input data is of size 5353.
But, from line 3 of your code, you are defining the input size (numFeatures) of your sequenceInputLayer as 1, whereas it should be defined as 5353.
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