# split data to train,test and validation

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REMYA K on 15 Nov 2020
Commented: Adam Danz on 16 Nov 2020
I want to split my data into train and test in a ratio of 70:30,further I want to split my train data into train and validation in a ratio of 60:10. I want 5 folds of such train,test and validation data combination but test data should be same in all 5 folds.
How can I solve this ?
Can any one help me.
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### Answers (1)

Adam Danz on 15 Nov 2020
If you have the Statistics and Machine Learning toolbox, use cvpartition.
Otherwise, randperm to create indicies that separate the test and training sets.
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Adam Danz on 16 Nov 2020
For example, let's say I want to split up vector "data" into 70/30 training/test sets.
data = rand(1,1000);
trainIdx = randperm(numel(data), round(numel(data)*.7));
testIdx = find(~ismember(1:numel(data), trainIdx));
trainIdx and testIdx are indices of the 'data' vector without overlap. To confirm that,
isequal(sort([trainIdx,testIdx]), 1:numel(data))
ans = logical
1
The training set will roughly cover 70% while the test set will roughly cover 30%. To confirm that,
[numel(trainIdx)/numel(data), numel(testIdx)/numel(data)]
ans = 1×2
0.7000 0.3000

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