network object custom weights initialization

Question

Fabiano Veglianti 2023-4-14

0
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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1947443-network-object-custom-weights-initialization

回答： Neha 2023-5-5

Xprostate_data.mat

在 MATLAB Online 中打开

I'm having trouble understanding the network object.

Question: How can I initialize the weights with a custom function?

So far, I've understood that I need to set ffnet.initFcn = 'initLay' to enable the layers init functions; then I need to set for each layer i ffnet.layers{i}.initFcn='initwb' to enable the weights init functions; but how should I continue this?

ffnet.initFcn = 'initLay';
for layer_index=1:size(ffnet.layers, 1)
    ffnet.layers{layer_index}.initFcn = 'initwb';
end

What is the signature of a well design weights initialization function?

This is the code I produced so far, but I don't think you will need, anyway I will post it:

clear all
close all
load('Xprostate_data.mat')
X=Xprostate(:,1:8);
Y=table2array(Xprostate(:,9));
ind=table2array(Xprostate(:,10));
n=size(X,1);
Xp = zscore(table2array(X));
Xtrain=Xp(ind==1,:); Ytrain=Y(ind==1);   %dataset for training
Xtest=Xp(ind==0,:); Ytest=Y(ind==0);     %dataset for test
%%% 
ffnet = feedforwardnet(netconf);
ffnet = train(ffnet, Xtrain', Ytrain');
ffnet.trainFcn = 'traingd';
ffnet.trainParam.lr = 0.001;
net.initFcn = 'initLay'; %initLay 
for layer_index=1:size(net.layers, 1)
    net.layers{layer_index}.initFcn = 'initwb';
    
end
ffnet = init(ffnet);
ffnet = train(ffnet, Xtrain', Ytrain');
function weights = randomNormalWeights(sz, mean, std)
weights = mean + randn(sz) * std;
end

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Answer 1

Neha 2023-5-5

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https://ww2.mathworks.cn/matlabcentral/answers/1947443-network-object-custom-weights-initialization#answer_1229639

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Hi Fabiano,

It is my understanding that you need to initialize the weights using a custom initialization function. Please refer to the code given below:

[icRows,icCols]=size(ffnet.inputConnect);
[lcRows,lcCols]=size(ffnet.layerConnect);
for i=1:icRows
    for j=1:icCols
        if ffnet.inputConnect(i,j)==1
            ffnet.IW{i,j}= randomNormalWeights(ffnet.inputWeights{i,j}.size,1,1); %matrix of size ffnet.inputWeights{i,j}.size, here: 10x8 (number of layersxnumber of inputs)
        end
    end
end
for i=1:lcRows
    for j=1:lcCols
        if ffnet.layerConnect(i,j)==1
            ffnet.LW{i,j}=randomNormalWeights(ffnet.layerWeights{i,j}.size,1,1); %matrix of size ffnet.layerWeights{i,j}.size, here: 10x1
        end
    end
end