I have a cell array of dimension tIN{2000,1} and each element in the cell array is a 100x21 the ouput to that is tOUT{2000,1} with each element also of dimensino 100x21
when training I get the error 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.
How do I fix this?
Error in CONv (line 23)
net = trainNetwork(tIN,tOUT,lgraph,options);
The current code is:
% Define Network Layers
layers = [sequenceInputLayer([100,21,1],'Name','input')
sequenceFoldingLayer('Name','fold')
convolution2dLayer(5,20,'Name','Conv')
maxPooling2dLayer([4 4],'Stride',2,'Name','max')
sequenceUnfoldingLayer('Name','unfold')
flattenLayer('Name','flat')
lstmLayer(100,'Name','lstm','OutputMode','Sequence')
dropoutLayer(0.2,'Name','drop')
fullyConnectedLayer(1,'Name','fc2')
regressionLayer('Name','output')];
lgraph = layerGraph(layers);
lgraph = connectLayers(lgraph,'fold/miniBatchSize','unfold/miniBatchSize');
%Training Options
options = trainingOptions('adam', ...
'InitialLearnRate',0.0001, ....
'ExecutionEnvironment','cpu', ...
'MaxEpochs',100, ...
'Plots','training-progress','Shuffle','every-epoch','L2Regularization',0.0005);
net = trainNetwork(tIN,tOUT,lgraph,options);
