After converting my data into a combined datastore, I tried training a deep neural network with the architecture shown below but the error " Error forming mini-batch for network input "sequence_prop". Data interpreted with format "CBT". To specify a different format, use the InputDataFormats option.
Error in netPaperv4 net = trainnet(dsTrain, net, "mse", options);
Caused by:
Batch dimension of datastore must match the format batch dimension (2)." occurred.
Here a datastore preview: 1×2 cell array
{[-0.2964 -0.2723 0 0.3049 0.1613 -0.9312]} {[2.2746]}
I want to combine three different sequence inputs (the goal is time series forecasting, not image classification: my inputs are all time-depending sequences) : two of size 1 and the other of size 4 to predict a single output (size 1).
Can anyone help me solve this? I can provide code if needed.After converting my data into a combined datastore, I tried training a deep neural network with the architecture shown below but the error " Error forming mini-batch for network input "sequence_prop". Data interpreted with format "CBT". To specify a different format, use the InputDataFormats option.
Error in netPaperv4 net = trainnet(dsTrain, net, "mse", options);
Caused by:
Batch dimension of datastore must match the format batch dimension (2)." occurred.
Here a datastore preview: 1×2 cell array
{[-0.2964 -0.2723 0 0.3049 0.1613 -0.9312]} {[2.2746]}
I want to combine three different sequence inputs (the goal is time series forecasting, not image classification: my inputs are all time-depending sequences) : two of size 1 and the other of size 4 to predict a single output (size 1).
Can anyone help me solve this? I can provide code if needed. After converting my data into a combined datastore, I tried training a deep neural network with the architecture shown below but the error " Error forming mini-batch for network input "sequence_prop". Data interpreted with format "CBT". To specify a different format, use the InputDataFormats option.
Error in netPaperv4 net = trainnet(dsTrain, net, "mse", options);
Caused by:
Batch dimension of datastore must match the format batch dimension (2)." occurred.
Here a datastore preview: 1×2 cell array
{[-0.2964 -0.2723 0 0.3049 0.1613 -0.9312]} {[2.2746]}
I want to combine three different sequence inputs (the goal is time series forecasting, not image classification: my inputs are all time-depending sequences) : two of size 1 and the other of size 4 to predict a single output (size 1).
Can anyone help me solve this? I can provide code if needed. deep neural network, deep learning, time series forecasting, database, time series MATLAB Answers — New Questions

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