im trying to use expectation-maximization to bootstrap an svm
classifier. for this to work, the classifier needs to return better
than random probabilities for its classification decisions. so not
being one to repeat work, i thought i would see if anyone is setting
on an implementation of AI::Categorizer::Learner::SVM that returns the
probabilities produced by libsvm.
any code or criticisms would be greatly appreciated.