Question

I’ve written a Matlab script for classification. When I execute this I’m getting Out Of Memory error.

for i =1:size(Y)  
    if(predictions(i) ~= clasL(find(ismember(mydata,X(i)),'rows')))  
        error = error+1;  
    end  
end

In the above code Y and predictions are vectors of dimension 19928. And mydata and X are 19928*62061 and 12819*62061 matrices. When I execute the following code I’m getting the following error

Error using  == 
Out of memory. Type HELP MEMORY for your options.

Error in ismember (line 62)
            tf = (a == s);

Error in myinit (line 105)
if(predictions(i) ~= clasL(find(ismember(mydata,X(i)),1)))

How to overcome this? Please help me.
Thanks

Answer 1

First try running ulimit on the MATLAB process so it can use as much memory as is available.

Second, I think you want to switch the order of arguments to ismember:

ismember(X(i, :), mydata, 'rows')

Third, you don’t need the extra find function if you change the order of arguments. You would then simply do this (inside the loop):

[~, idx] = ismember(X(i, :), mydata, 'rows')
if (idx > 0 && predictions(i) ~= clasL(idx))
    error = error+1;  
end 

Fourth, to save on time, you can run ismember just once for all the rows in X (no loop) and then find the number of errors in a vectorized manner:

[~, idxs] = ismember(X, mydata, 'rows')
error = sum(predictions(idxs > 0) ~= clasL(idxs > 0))