On Thursday, February 26, 2015 at 8:41:26 AM UTC-8, Sturla Molden wrote: > If you are doing SVM regression with scikit-learn you are using libSVM. > There is a CUDA accelerated version of this C library here: > http://mklab.iti.gr/project/GPU-LIBSVM > > You can presumably reuse the wrapping code from scikit-learn. > > Sturla
Hi Sturla, I recognize your name from the scikit-learn mailing list. If you look a few posts above yours in this thread, I am aware of gpu-libsvm. I don't know if I'm up to the task of reusing the scikit-learn wrapping code, but I am giving that option some serious thought. It isn't clear to me that gpu-libsvm can handle both SVM and SVR, and I have need of both algorithms. My training data sets are around 5000 vectors long. IF that graph on the gpu-libsvm web page is any indication of what I can expect from my own data (I note that they didn't specify the GPU card they're using), I might realize a 20x increase in speed. -- https://mail.python.org/mailman/listinfo/python-list
