Fastest SVM implementation

More of a general question. I’m running an rbf SVM for predictive modeling. I think my current program definitely needs a bit of a speed up. I use scikit learn with a coarse to fine grid search + cross validation.

Each SVM run takes around a minute, but with all the iterations, I’m still finding it too slow. Assuming I eventually multi thread the cross validation part over multiple cores, any recommendations on speeding up my program? Any faster implementations of SVMs? I’ve heard of some GPU SVMs, but haven’t digged into it much. Any users and is it faster?

Answer

Google’s Sofia algorithm contains an extremely fast implementation of a linear SVM. It’s one of the fastest SVMs out there, but I think it only supports classification, and only supports linear SVMs.

There’s even an R package!

Attribution
Source : Link , Question Author : tomas , Answer Author : Zach

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