I’m curious how much faster your SVM implementation ran, when compared to LibSVM (or more specifically LibLinear). Any published details?
Our SVM implementation is not significantly faster than the libSVM one, since we don’t have any algorithmic improvement on that yet. We are more careful when it comes to memory. We do have though a version of our SVM that runs in the bagging (aka bootstrap) mode with the help of hadoop. This one is more scalable as you would expect. If you really need a scalable classifier with good performance, I would recommend our Nonparametric Bayes one (aka Kernel discriminant analysis) which is very fast and has the same (sometime better) performance than SVM (see kde). You can also use the classic nearest neighbor classifier which is faster but a less accurate (not that much), for more information see Neighbors (Nearest, Farthest, Range, k, Classification).
