LIBLINEAR is a linear classifier for data with millions of instances and features. It supports L2-regularized logistic regression (LR), L2-loss linear SVM, and L1-loss linear SVM.
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 interfaces
E. Baykan, M. Henzinger, L. Marian, und I. Weber. WWW '09: Proceedings of the 18th international conference on World wide web, Seite 1109--1110. New York, NY, USA, ACM, (2009)
B. Krause, C. Schmitz, A. Hotho, und G. Stumme. AIRWeb '08: Proceedings of the 4th international workshop on Adversarial information retrieval on the web, Seite 61--68. New York, NY, USA, ACM, (2008)
B. Krause, C. Schmitz, A. Hotho, und G. Stumme. AIRWeb '08: Proceedings of the 4th International Workshop on Adversarial Information Retrieval on the Web, Seite 61--68. New York, NY, USA, ACM, (April 2008)
C. Veres. Natural Language Processing and Information Systems, Volume 3999 von Lecture Notes in Computer Science, Seite 58--69. Berlin/Heidelberg, Springer, (2006)
B. Krause, C. Schmitz, A. Hotho, und G. Stumme. AIRWeb '08: Proceedings of the 4th international workshop on Adversarial information retrieval on the web, Seite 61--68. New York, NY, USA, ACM, (2008)
C. Basu, H. Hirsh, und W. Cohen. AAAI '98/IAAI '98: Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence, Seite 714--720. Menlo Park, CA, USA, American Association for Artificial Intelligence, (1998)