Please help how to divide big feature vector data into training and testing set for face verification.

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I am working on age invariant face verification.
I have 665 feature vector(dimension 665 x 10548) for intra personal pairs with class 1 in one variable.
Similarly 6000 feature vector (dimension is 6000 x 10548) for extra personal pairs with Class -1 in another variable.
Now i want to divide these feature vectors into tarining and testing dataset.(3 cross validation using SVM)
Please tell me any matlab code which do this job automaticaly.

Accepted Answer

Image Analyst
Image Analyst on 3 Apr 2015
Brett from The Mathworks has 2 face recognition apps in his File Exchange ht<tp://www.mathworks.com/matlabcentral/fileexchange/index?term=authorid%3A911
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Image Analyst
Image Analyst on 4 Apr 2015
It took all your data and randomly assigned them to either a training set or a testing set. As far as "how" - it was by the code, especially this line:
indexes = randi([0 1], rows, 1);
chinnurocks
chinnurocks on 22 Aug 2016
Hey... I have 100 subject database out of which 50 are male and 50 are female. Each subject has 6 images. I just took 1 image per subject i.e 100 images. I just extracted 100 feature vectors and able to cross validate the data. But, I want to utilise all the images of a subject.
So, if I take 6 images of a subject. I would get 600 images and I can cross validate. But, it would not give a correct result as it would divide images from the same subject into testing and training at a time.
So, what I was thinking is that 6 feature vectors which i obtain from a subject should go to either testing or training data. But, I am unable to implement it. How to fix it ? Need your help.

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