This post is a bit old, but many people still seem interested. So just a short update: Nowadays I would use Python and scikit-learn to do this. Here is an example of how to do cross-validation for SVMs in scikit-learn.Scikit-learn even downloads MNIST for you. MNIST is, for better or worse, one of the standard benchmarks for machine learning and is also widely used in then neural networks community as a toy vision problem.Just for the unlikely case that anyone is not familiar with it:It is a dataset of handwritten digits, 0-9, in black on white background.It looks something like this:There are 60000 training and 10000 test images, each 28x28 gray scale.There are roughly the same number of examples of each category in the test and training datasets.I used it in some papers myself even though there are some reasons why it is a little weird.Some not-so-obvious (or maybe they are) facts are:- The images actually contain a 20x20 patch of digit and where padded to …