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 evaulation
- Automatic parameter selection
- Probability estimates (logistic regression only)
- Weights for unbalanced data
- MATLAB/Octave, Java, Python, Ruby interfaces

WWW: https://www.csie.ntu.edu.tw/~cjlin/liblinear/