Layers argument must be an array of layers or a layer graph.

XTrain = xlsread('R1_all_data.xlsx',1,'A1:G3788')';
YTrain = xlsread('R1_all_data.xlsx',1, 'H1:H3788')';
XTest = xlsread('R2_all_data.xlsx',1, 'A1:G3788')';
YTest = xlsread('R2_all_data.xlsx',1, 'H1:H3788')';
inputSize = 3788;
numResponses = 1;
numHiddenUnits = 5000;
layers = { sequenceInputLayer(inputSize)
    
lstmLayer(numHiddenUnits)

fullyConnectedLayer(numResponses)

regressionLayer  };
opts = trainingOptions('adam', 'MaxEpochs', 1000, 'GradientThreshold', 0.01, 'InitialLearnRate',0.0001);
net = trainNetwork(XTrain,YTrain,layers,opts);
YPred1=predict(net,XTest)

[Matt J]

You have posted only code. Do you have a question about it? If you are getting error messages please copy/paste them.

Answer 1

[Krishna]

Hello PRAMOD,

It appears that the issue you're encountering stems from an improper initialization of the layers object. The mistake was made by using curly braces {} to initialize:

layers = { sequenceInputLayer(inputSize)

lstmLayer(numHiddenUnits)

fullyConnectedLayer(numResponses)

regressionLayer }

Instead, you should initialize using square brackets [] like this:

layers = [ sequenceInputLayer(inputSize)

lstmLayer(numHiddenUnits)

fullyConnectedLayer(numResponses)

regressionLayer ]

I hope this correction resolves your problem.