I'm attempting to generate some one-to-rest weight vectors for a multi-class SVC for feature selection purposes. However, I'm current using one of the several LibSVM ports, which inherently performs one-to-one in multi-class classifications.

The columns of the sv_conf output does not appear to me to be duals of one-to-rest classifications. But is there a way to re-construct one-to-rest feature weights from the output of one-to-one classifications, or I'd have to run several one-to-one and obtain the weight vectors separately for each class?

  • $\begingroup$ Too much specific jargon is being used. The question is so focused it has more to do with interpreting a specific program than interpreting statistics, methods or anything relating to this site. If the question can be made into one that asks something about interpretation of a statistical method as opposed to a specific computer software, that should be done. $\endgroup$
    – Carl
    Apr 7, 2017 at 1:23
  • $\begingroup$ I have re-focused the question; please review if it's still off-topic. $\endgroup$
    – John M.
    Apr 7, 2017 at 19:16
  • $\begingroup$ Better, and since you seem to have someone answering you, I have suggested reopening. $\endgroup$
    – Carl
    Apr 7, 2017 at 19:41

1 Answer 1


If you do one-to-one classification mode, there is no single weight vector; there are $\binom{m}{2}$ if you have $m$ classes. You can reconstruct each of those vectors from the appropriate entries of sv_coef, though.

  • $\begingroup$ What I'm not so sure about extracting these sv_coef entries is, because every one-to-one classifier has two SVs, do I need to extract the sv_coef entries for both SVs, and if so, how do I combine the results? I saw at least one literature (e1071's internals) that would sum both SVs' * sv_coef from the same classifier, but I haven't seen this elsewhere. $\endgroup$
    – John M.
    Apr 6, 2017 at 17:31

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