Precomputed Kernels with LibSVM in Python

Posted by Lyyli on Stack Overflow See other posts from Stack Overflow or by Lyyli
Published on 2010-03-19T01:32:12Z Indexed on 2010/03/19 1:41 UTC
Read the original article Hit count: 519

Filed under:
|
|

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.

© Stack Overflow or respective owner

Related posts about libsvm

Related posts about python