Divide training , validation and testing data.

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.

Answer 1

[KSSV]

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,:) ; 

[Sujith Jacob]

thank you for the help

[KSSV]

Thanks is accepting/ votinng the answer... :)

Answer 2

[Image Analyst]

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);