LIBLINEAR System
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See: Linear Classification System, LIBSVM, Linear Classification Algorithm.
References
2012
- http://www.csie.ntu.edu.tw/~cjlin/liblinear/
- 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
- LIBLINEAR is a linear classifier for data with millions of instances and features. It supports
2008
- (Fan et al., 2008) ⇒ Rong-En Fan, Kai-Wei Chang, Cho-Jui Hsieh, Xiang-Rui Wang, and Chih-Jen Lin. (2008). “LIBLINEAR: A Library for Large Linear Classification.” In: The Journal of Machine Learning Research, 9