How to do a 10-fold cross validation without using built-in function in MATLAB? - matlab

Question

I try to do a 10 folds cross validation without using built-in function to train and recognize digit from 0-9 I have sample of 500 picture(50 for each digit to train and test.)
I try implement the answer MATLAB: 10 fold cross Validation without using existing functions and other websites but it didn't help that much. Mostly because I'm new to MATLAB so I don't know much about what I should do to tweak it.
This is the code I have so far.
c=zeros(10,size(x,2),size(x,3));
K=10;
k=10;
test= 1:50/K;
for fold =1:K
if(test(1)~=1)
train = x(1:test(1)-1,:,:);
if (test(5) ~=50)
train=[train ; x(test(end):50,:,:)];
end
else
train = x(test(1):50,:,:);
end
test = test+ones(1,50/K)*50/K;
end
for i =0:9
test=test+50/K*ones(1,5);
c(i+1,:,:)=cal_likelihood(x(1+i*50:50+i*50,:,:),50/k*(k-1));
end
Variable explanation
x is the 500x28x28 double where it keeps all 500 digit picture.
test is a test set.
train is a training set.
In order to do 10 folds cross validation I need to change training set like
1st fold : 1:5 for test,6:45 for train
2nd fold : 6:10 for test,1:5 11:50 for train and so on
The problem is I don't know how to shift the training set from one set to another like from 6:45 to 1:5 and 11:50. or Can I write a better loop than this?
PSS. If someone who answer this don't mind What does 500x28x28 double actually mean.

Answer 1

There are a few ways you could write this, some of which are easier to understand than others. Matlab is quite nice to write in as while expressions such as 1:3 evaluate to [1,2,3], the expression 1:0 evaluates to the empty set. So, it is very straightforward to generate the sets without having to use if statements.
I'd start off the loop as:
samples_per_digit=50;
block_sze=samples_per_digit/K;
for fold =1:K
test_ind = 1+(fold-1)*block_sze:fold*block_sze;
train_ind = [1:(fold-1)*block_sze, (fold*block_sze+1):samples_per_digit];
for i=0:9
train=x(train_ind+i*samples_per_digit,:,:);
test=x(test_ind+i*samples_per_digit,:,:);
% Perform training and validation in here for this fold of the digit i
You can verify that test_ind and train_ind correspond to the subsets of blocks of training and validation that you need. It is only in the innermost loop that these translate to the matrices corresponding to the digit images, using the value of i to compute the offset. Of course, if you wish, you can swap the order of the loops, computing all of the folds for a single digit. It all depends on how you wish to store your results.