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Error using trainNetwork - invalid training data

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Jinyang Du
Jinyang Du 2021 年 7 月 29 日
コメント済み: KSSV 2021 年 7 月 29 日
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.
  2 件のコメント
Jinyang Du
Jinyang Du 2021 年 7 月 29 日
I just used
x = readtable('XTrain.csv');
y = readtable('YTrain.csv');
XTrain = table2cell(x);
YTrain = table2cell(y);
net = trainNetwork(XTrain,YTrain,layers,options);

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KSSV
KSSV 2021 年 7 月 29 日
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);
  2 件のコメント
KSSV
KSSV 2021 年 7 月 29 日
Thanks is accepting/ voting the answer. :)

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