Support Vector Machines represent a group of supervised learning classifiers that will try to predict the outcome of a feature set. I don't want to bore you with the details but I would recommend that you read Ilya's post about SVMs. It's very informative and it will give you the basics of what you need to understand to get started.
In my case, I've been working on a fairly large scale text classification problem at work when I realized that SVMs would be perfect for the job. Unfortunately, for our needs the current state of Ruby support for SVMs wasn't where we needed it to be.
I am happy to introduce rb-libsvm to the world!
While I can't take credit for the entire gem myself, I did help clean up some pieces of the codebase and gemify the code to make it possible to install from Rubygems.
Basic Usage Example:
As for the future plans for this gem, one of the biggest features I can think of building would be the Marshaling of the Libsvm::Model object. This would be a big performance win since you wouldn't have to re-train the classifier. If you have any other ideas for features, I'd be happy to hear about them.
WHO AM I?
I'm Rimas Silkaitis, a mild mannered Ruby dev living in San Francisco. I like building stuff for the web and am particularly interested in machine learning. I also own a set of turntables.