Error using trainNetwork - invalid training data

layers = [
    sequenceInputLayer(27)
    bilstmLayer(100,"OutputMode","last")
    fullyConnectedLayer(3);
    softmaxLayer();
    classificationLayer()
    ];
options = trainingOptions("adam", ...
    "MaxEpochs",250, ...
    "InitialLearnRate",0.005, ...
    "GradientThreshold",1, ...
    "Shuffle","every-epoch", ...
    "Plots","training-progress", ...
    "LearnRateDropPeriod",200,...
    "LearnRateSchedule","piecewise");

The network I used is written above. And I tried to use net = trainNetwork(XTrain,YTrain,layers,options); to train this network. But it seems never work (I have converted table to cell before training). The training data is attached. The XTrain data is a 33750 x 27 predictor and YTrain is a 33750 x 1 respond. I intend to use this network to classify these data (predictors in X map into categories in Y). Could anyone show me how to get going? I am quite deserate by now.

[KSSV]

How did you load and arrange XTRain, YTrain. Show us the complete code.

[Jinyang Du]

I just used

x = readtable('XTrain.csv');
y = readtable('YTrain.csv');
XTrain = table2cell(x);
YTrain = table2cell(y);

net = trainNetwork(XTrain,YTrain,layers,options);

Answer 1

[KSSV]

x = readtable('XTrain.csv');
y = readtable('YTrain.csv');
XTrain = table2array(x);
YTrain = table2array(y);

XTrain = num2cell(XTrain,2) ; 
XTrain = cellfun(@transpose,XTrain,'UniformOutput',false) ;
YTrain = categorical(YTrain) ; 

layers = [
    sequenceInputLayer(27)
    bilstmLayer(100,"OutputMode","last")
    fullyConnectedLayer(3);
    softmaxLayer();
    classificationLayer()
    ];
options = trainingOptions("adam", ...
    "MaxEpochs",250, ...
    "InitialLearnRate",0.005, ...
    "GradientThreshold",1, ...
    "Shuffle","every-epoch", ...
    "Plots","training-progress", ...
    "LearnRateDropPeriod",200,...
    "LearnRateSchedule","piecewise");

net = trainNetwork(XTrain,YTrain,layers,options);

[Jinyang Du]

omg thank you so much！！！

[KSSV]

Thanks is accepting/ voting the answer. :)