I've been searching the net for ~3 hours but I couldn't find a solution yet. I want to give a precomputed kernel to libsvm and classify a dataset, but: How can I generate a precomputed kernel? (for example, what is the basic precomputed kernel for Iris data?) In the libsvm documentation, it is stated that: For precomputed kernels, the first element of each instance must be the ID. For example, samples = [[1, 0, 0, 0, 0], [2, 0, 1, 0, 1], [3, 0, 0, 1, 1], [4, 0, 1, 1, 2]] problem = svm_problem(labels, samples) param = svm_parameter(kernel_type=PRECOMPUTED) What is a ID? There's no further details on that. Can I assign ID's sequentially? Any libsvm help and an example of precomputed kernels really appreciated.