Input shape for the LSTM model
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Train dataset X has a shape of 1x50000 and each of 50000 elements has 5x1 data. Train dataset Y also has a shape of 1x50000 and each elements has 1x1 data. I wonder if the shape of the two datasets are valid to train lstm model like below because it keeps giving me an error msg " Invalid training data. Responses must be a matrix of numeric responses, or a N-by-1 cell array of sequences, where N is the number of sequences. The feature dimension of all sequences must be the same.
numFeatures = 5;
numHiddenUnits = 200;
numClasses = 1;
layers = [ ...
sequenceInputLayer(numFeatures)
lstmLayer(numHiddenUnits)
dropoutLayer(0.5)
fullyConnectedLayer(numClasses)
regressionLayer];
options = trainingOptions('adam', ...
'MaxEpochs',50, ...
'ValidationData',{test_x, test_y}, ...
'GradientThreshold',1, ...
'Verbose',1, ...
'Shuffle','never', ...
'ExecutionEnvironment','gpu', ...
'Plots','training-progress');
net = trainNetwork(train_x, train_y, layers, options);
Thank you for help in advance.
1 comentario
KSSV
el 28 de Jul. de 2021
Check the given working examples in the doc and try to understand. Did you try to run given examples?
Respuestas (1)
Prince Kumar
el 7 de Sept. de 2021
Your train dataset X and Y should have dimension 50000x1.
Refer the example in this article. It has a sequence classification example.
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