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.

Accepted Answer

KSSV on 27 Jun 2022
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,:) ;

More Answers (1)

Image Analyst
Image Analyst on 27 Jun 2022
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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