Training Neural Networks using Multi-Class output

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Anirudh Roy 2020-11-23

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https://ww2.mathworks.cn/matlabcentral/answers/658793-training-neural-networks-using-multi-class-output

评论： Anirudh Roy 2020-12-5

The Deep Learning toolbox supports classification based training (from feature based data) for ony 1 label per sample. I have a MxD training set (D number of features and M number of samples). Each output should be characterized by 'T' number of labels (ie final output MxT). My question is how do i get around this limitation ? (The labels are mutually exclusive)

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Answer 1

Raynier Suresh 2020-12-1

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https://ww2.mathworks.cn/matlabcentral/answers/658793-training-neural-networks-using-multi-class-output#answer_561418

One way to obtain multiple labels for a single sample is to branch the network and have multiple classification layers or regression layers.

Refer the below link for designing and training multi-output networks :

https://www.mathworks.com/help/deeplearning/ug/train-network-with-multiple-outputs.html#responsive_offcanvas

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Anirudh Roy 2020-12-5

Branching isnt probably ging to solve my problem, stacking of classification layer would. But yeah i get the idea, ill have to customize the whole thing (loop and layer)

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