2
$\begingroup$

I'd like to know which exact version of svm is implemented in slearn. The references section on sklearn's svm page cites libsvm package and a paper from 1999 which is about comparing classification error rate and likelihood scores. The libsvm paper talks about the original svm paper by Vapnik. But I couldn't figure out which exact formulation of svm has been implemented.

The libsvm paper cites a paper titled Fast Training of Support Vector Machines Using Sequential Minimal Optimization that solves svm using a method called sequential minimal optimization. Is this the algorithm that sklearn actually calls under the hood or is it a different version of this method?

$\endgroup$
0
$\begingroup$

Yes - the implementation there is based on libsvm - which does indeed implement Platt's SMO - you can see the details in this paper.

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.