I have a data set with 2400 samples and 10,000 features. All the data is binary (+1 or -1). I need to run it past an SVM algorithm so I could compare my algorithm to it. However, I know not much about SVMs or which package to use. I tried reading about to so I could implement one, but it’s way over my head, and I need to get from it is the weights vector. I’m a windows user and I’ve got my implementation in Java. I could export my data into a text file with 1s and 0s. I have access to MatLab, but something tells me it will be extremely slow and won’t really run on my 1.6ghz 2gb RAM laptop (and I need it to) fast enough. I have to run the algorithm a couple hundred times to get accurate results.
I’m really just looking for a quick and easy to understand library or SVM implementation that I can use in my case.
Thank you all. Feel free to ask any additional questions to assist me better.
I ended up using a JNI for SVN light that can be found here: http://www.mpi-inf.mpg.de/~mtb/svmlight/
Didn’t take long to figure out how to use it and it’s surprisingly fast (seconds).