LIBLINEAR is a linear classifier for data with millions of instances and features. It supports both logistic regression and L2-loss linear SVM using a trust region Newton method in C.-J. Lin, R. C. Weng, and S. S. Keerthi. Trust region Newton method for large-scale regularized logistic regression. Technical report, 2007. A short version appears in ICML 2007. Main features of LIBLINEAR include Same data format as LIBSVM and similar usage One-vs-the rest multi-class classification Cross validation for model selection Probability estimates (logistic regression only) Weights for unbalanced data