Error in running one-dimensional CNN regression model

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Marvin
Marvin 2023-5-17
回答： Prasannavenkatesh 2023-6-18
Hi,
I'm new to training a CNN regression model, and I need to build one to predict temperature time series data using climate proxy data.
I'm not sure what are functions of various layers, so I'm building a simple CNN model first.
For example, I've temperature time series of length 100 (Y_train=100x1 double) and 45 climate proxy data (X_train=45x100 double), so the input feature number is 45.
I've set my CNN model architecture as follows:
function y_pred = cnn(X_train, X_val, Y_train)
layers = [sequenceInputLayer(45,'MinLength',100)
convolution1dLayer(2,10)
reluLayer
maxPooling1dLayer(2,'Stride',2)
reluLayer
fullyConnectedLayer(1)
reluLayer
regressionLayer];
options = trainingOptions('sgdm', ...
MaxEpochs=500, ...
Verbose=false, ...
Plots='none');
net = trainNetwork(X_train, Y_train, layers, options);
y_pred = predict(net, X_val);
end
When I ran the code, it produces this error message:
I'm unsure where I've done wrong.

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回答（1 个）

Prasannavenkatesh
Prasannavenkatesh 2023-6-18
Hi Marvin,
To solve the error of incompatible input and output sequence lengths, you can try replacing the first layer, i.e, the sequence input layer to sequenceInputLayer(45,'MinLength',1). Hope this solves your problem.

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