math/liblinear 2.50 NetBSD

LIBLINEAR is a linear classifier for data with millions of instances and features. It supports L2-regularized classifiers L2-loss linear SVM, L1-loss linear SVM, and logistic regression (LR) L1-regularized classifiers (after version 1.4) L2-loss linear SVM and logistic regression (LR) L2-regularized support vector regression (after version 1.9) L2-loss linear SVR and L1-loss linear SVR. Main features of LIBLINEAR include Same data format as LIBSVM, our general-purpose SVM solver, and also similar usage Multi-class classification: 1) one-vs-the rest, 2) Crammer & Singer Cross validation for model selection Probability estimates (logistic regression only) Weights for unbalanced data MATLAB/Octave, Java, Python, Ruby interfaces