L1 and L2 Regularization for matlab

Hi Guys

I would like to know how to add regularization L1 & L2 for following layers to reduce overfitting

 imageInputLayer([32 32 3],"Name","imageinput")
    convolution2dLayer([5 5],32,"Name","conv","BiasLearnRateFactor",2,"Padding",[2 2 2 2],"WeightsInitializer","narrow-normal")
    batchNormalizationLayer
    maxPooling2dLayer([3 3],"Name","maxpool","Stride",[2 2])
    preluLayer(20,'prelu')
    averagePooling2dLayer([3 3],"Name","avgpool","Stride",[2 2])
    fullyConnectedLayer(2,"Name","fc_rcnn","BiasL2Factor",1,"BiasLearnRateFactor",10,"WeightLearnRateFactor",20,"WeightsInitializer","narrow-normal")
    dropoutLayer(0.65,'Name','drop1')
    softmaxLayer("Name","softmax")
    classificationLayer("Name","classoutput")];

Answer 1

[Divya Gaddipati]

You can set the L2 regularization for selected layers using the setl2factor function.

You can refer to the following link for more understanding:

https://www.mathworks.com/help/deeplearning/ref/nnet.cnn.layer.layer.setl2factor.html