LIBLINEAR: A Library for Large Linear Classification

LIBLINEAR is an open source library for large-scale linear classification. It supports logistic regression and linear support vector machines. We provide easy-to-use command-line tools and library calls for users and developers. Comprehensive documents are available for both beginners and advanced users. Experiments demonstrate that LIBLINEAR is very efficient on large sparse data sets.

[1]  Zellig S. Harris,et al.  Distributional Structure , 1954 .

[2]  Gerard Salton,et al.  On the Specification of Term Values in Automatic Indexing , 1973 .

[3]  Zellig S. Harris,et al.  Distributional Structure , 1954 .

[4]  Bernhard E. Boser,et al.  A training algorithm for optimal margin classifiers , 1992, COLT '92.

[5]  Chih-Jen Lin,et al.  Asymptotic Behaviors of Support Vector Machines with Gaussian Kernel , 2003, Neural Computation.

[6]  Yiming Yang,et al.  RCV1: A New Benchmark Collection for Text Categorization Research , 2004, J. Mach. Learn. Res..

[7]  Koby Crammer,et al.  On the Learnability and Design of Output Codes for Multiclass Problems , 2002, Machine Learning.

[8]  Thorsten Joachims,et al.  Training linear SVMs in linear time , 2006, KDD '06.

[9]  Chih-Jen Lin,et al.  Generalized Bradley-Terry Models and Multi-Class Probability Estimates , 2006, J. Mach. Learn. Res..

[10]  Yoram Singer,et al.  Pegasos: primal estimated sub-gradient solver for SVM , 2007, ICML '07.

[11]  Chih-Jen Lin,et al.  Trust region Newton methods for large-scale logistic regression , 2007, ICML '07.

[12]  Chih-Jen Lin,et al.  A dual coordinate descent method for large-scale linear SVM , 2008, ICML '08.

[13]  Chih-Jen Lin,et al.  A Practical Guide to Support Vector Classication , 2008 .

[14]  Chih-Jen Lin,et al.  A sequential dual method for large scale multi-class linear svms , 2008, KDD.

[15]  Cho-Jui Hsieh,et al.  Coordinate Descent Method for Large-scale L 2-loss Linear SVM , 2008 .

[16]  Chih-Jen Lin,et al.  Trust Region Newton Method for Logistic Regression , 2008, J. Mach. Learn. Res..

[17]  Paul Tseng,et al.  A coordinate gradient descent method for nonsmooth separable minimization , 2008, Math. Program..

[18]  Trevor Hastie,et al.  Regularization Paths for Generalized Linear Models via Coordinate Descent. , 2010, Journal of statistical software.

[19]  Chih-Jen Lin,et al.  A Comparison of Optimization Methods and Software for Large-scale L1-regularized Linear Classification , 2010, J. Mach. Learn. Res..

[20]  Chih-Jen Lin,et al.  Dual coordinate descent methods for logistic regression and maximum entropy models , 2011, Machine Learning.

[21]  Guo-Xun Yuan.  A Comparison of Optimization Methods for Large-scale L 1-regularized Linear Classification , 2010 .