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. thanks, alan gibson
