Deep Learning Layers to increase training accuracy

Question

Jahetbe 2022-2-22

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https://ww2.mathworks.cn/matlabcentral/answers/1655920-deep-learning-layers-to-increase-training-accuracy

评论： Jahetbe 2022-2-23

Hi everyones.

I want to use DL for modeling a problem with 6 inputs and one output.

I've used the following layers but I cannot increase the model accuracy not only for unseen samples but also for training samples.

I've check different structures and try to generated a complex model as much as possible to get at least good results in training stages

numHiddenNeuron = 100;

layers = [

featureInputLayer(numFeatures,'Normalization','rescale-symmetric')

fullyConnectedLayer(numHiddenNeuron)

reluLayer('Name','relu')

batchNormalizationLayer

fullyConnectedLayer(numOut)

regressionLayer('Name','regression')];

I would be appreciated it if you could help me.

Regards,

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Answer 1

yanqi liu 2022-2-23

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https://ww2.mathworks.cn/matlabcentral/answers/1655920-deep-learning-layers-to-increase-training-accuracy#answer_902365

在 MATLAB Online 中打开

yes，sir，may be add some dropoutLayer in net Layers，such as

numHiddenNeuron = 100;
layers = [
            featureInputLayer(numFeatures,'Normalization','rescale-symmetric')
            fullyConnectedLayer(numHiddenNeuron)
            reluLayer('Name','relu')
            batchNormalizationLayer
            dropoutLayer
            fullyConnectedLayer(numOut)
            regressionLayer('Name','regression')];
% or
layers = [ ...
    sequenceInputLayer(numFeatures)
    lstmLayer(100,'OutputMode','sequence')
    dropoutLayer(0.3)
    lstmLayer(50,'OutputMode','sequence')
    dropoutLayer(0.2)
    fullyConnectedLayer(numOut)
    regressionLayer];