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set labels for classifier deep learning toolbox

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jg
jg el 10 de Mayo de 2020
Comentada: Wiktor el 20 de Mzo. de 2024
Where do i set the labels for supervised training?
[XTrain,YTrain] = digitTrain4DArrayData;
idx = randperm(size(XTrain,4),1000);
XValidation = XTrain(:,:,:,idx);
XTrain(:,:,:,idx) = [];
YValidation = YTrain(idx);
YTrain(idx) = [];
layers = [
fullyConnectedLayer(4096,"Name","fc6","BiasInitializer","ones","WeightsInitializer","ones")
reluLayer("Name","relu6")
dropoutLayer(0.5,"Name","dropout6")
fullyConnectedLayer(4096,"Name","fc7")
reluLayer("Name","relu7")
dropoutLayer(0.5,"Name","dropout7")
fullyConnectedLayer(4096,"Name","fc8")
softmaxLayer("Name","softmax")
classificationLayer("Name","classoutput")];
plot(layerGraph(layers));
net = trainNetwork(XTrain,YTrain,layers,options);

Respuestas (1)

Ankriti Sachan
Ankriti Sachan el 13 de Mayo de 2020
By setting the labels for supervised training, I am assuming that you want to ask how to train the dataset with the labeled data.
I guess you are already following this documentation - https://www.mathworks.com/help/deeplearning/ref/trainnetwork.html
For the function,
net = trainNetwork(X,Y,layers,options), it is mentioned that
X = Training data
Y = Labels of the data that you are training the model with
layers = Neural network layers
option = Training options.
So I guess ‘Y’ is the variable that you are looking for.
  1 comentario
Wiktor
Wiktor el 20 de Mzo. de 2024
Hi! If I have augmentedImageDatastore created from imageDatadtore with defined Labels to every element, can I skip "Y" in trainNetwork function?

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