I have a problem in the trainNetwork for Xtrain and Ytrain it gives me X and Y must have the same number of observations.
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mahmoud Bassiouni
el 4 de Abr. de 2018
Respondida: mahmoud Bassiouni
el 27 de Mzo. de 2019
XTrain = importdata('C:\Users\m7mod\Documents\MATLAB\TrainM.mat'); % size of XTrain = 9 * 44 YTrain = categorical([1 1 1 1 0 0 0 0 0]'); % size of YTrain = 9 * 1 layers = [ ... imageInputLayer([44 1]) convolution2dLayer(5,20) reluLayer fullyConnectedLayer(10) softmaxLayer classificationLayer()] options = trainingOptions('sgdm'); XNew = zeros(size(XTrain,1),1,1,size(XTrain,2)); XNew(:,1,1,:) = XTrain(:,:); net = trainNetwork(XNew,YTrain',layers,options);
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Ameer Hamza
el 24 de Abr. de 2018
Editada: Ameer Hamza
el 24 de Abr. de 2018
You are facing the problem because you are trying to use imageInputLayer and convolution2dLayer which will only work if your input sample have at least 2 non-singleton dimensions (i.e. m*n and m*n*k will work but 1*m or m*1 will not work). For a single dimension data (as in your case 1*44), you can use sequenceInputLayers. For your case, if you can change the layers combination as shown in following script snippet the code will work
XTrain = importdata('C:\Users\m7mod\Documents\MATLAB\TrainM.mat'); % size of XTrain = 9 * 44
YTrain = categorical([1 1 1 1 0 0 0 0 0]'); % size of YTrain = 9 * 1
layers = [ ...
sequenceInputLayer(44)
fullyConnectedLayer(2)
softmaxLayer
classificationLayer];
options = trainingOptions('sgdm');
net = trainNetwork(XTrain',YTrain',layers,options);
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Ameer Hamza
el 24 de Abr. de 2018
The documentation page state that it was introduced in 2017b.
If you are using earlier version then you can use fitnet and train as
XTrain = importdata('C:\Users\m7mod\Documents\MATLAB\TrainM.mat'); % size of XTrain = 9 * 44 YTrain = [1 1 1 1 0 0 0 0 0]'; % size of YTrain = 9 * 1 net = fitnet([10 10]); net = train(net, XTrain',YTrain');
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