K-fold cross validation CNN

Hi, I am trying to use K-fold cross validation with CNN, here is a part of my code

% Load the data
% split the data into two parts (Training and Testing)
% define the target output for the training
% for the CNN, how many layers want to use, for example (two Layers)

% K-fold cross validation
ind = crossvalindcrossvalind('Kfold',Train_Target,10);

for i = 1:10
    vali = (ind == i)'; 
    train = ~vali;
    
    % Split the data for Training and Validation
    Vali_data = Training_Data(:,vali);
    Train_data = Training_Data(:,train);
    
    % CNN Traning option
    options = trainingOptions('sgdm',...
    'InitialLearnRate',0.02, ...
    'ValidationData',{Vali_data, Vali_Target}, ...
    'Plots','training-progress');

    % Train Network
    net = trainNetwork(Train_data, Train_target, layers, options)  
end
    
% calculate the accurcy of the model using unseen data (Testing data)
YPredicted = classify(net,TestData);

Is this procedure right for using k-fold cross validation with cnn?

Thanks

[Anjuraj V.P.]

What does the variable ' Train_target ' implies?

[shelvi nur]

what this crossvalindcrossvalind ? because Unrecognized function or variable 'crossvalindcrossvalind'.

Answer 1

[linxin chen]

https://ww2.mathworks.cn/matlabcentral/fileexchange/71546-simple-deep-learning-algorithms-with-k-fold-cross-validation?requestedDomain=zh