Divide training , validation and testing data.
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How can I divide only training and validation data randomly and have a separate contingous block for testing data.
for eg. if I have 2000 target points. I want to have randomly selected points from first 1500 points for training and validation but for testing I want 1501 to 2000 target points.
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KSSV
2022-6-27
A = rand(2000,3) ; % your data
Test = A(1501:end,:) ; % take test continuously
A = A(1:1500,:) ; % pick the left data
A = A(randperm(1500,1500),:) ; % randomise the data
train_idx = round(70/100*1500) ; % 70% training
Train = A(1:train_idx,:) ;
Valid = A(train_idx+1:end,:) ;
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Image Analyst
2022-6-27
Depends on what kind of network training you're doing. If you're using trainNetwork and labels, then you can use imageDatastores and the function splitEachLabel
% Split the image data store into 80% for training, 10% for validation, and 10% for testing.
[trainingSet, validationSet, testSet] = splitEachLabel(imds, 0.8, 0.1);
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