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Diffstat (limited to 'science/liblinear/pkg-descr')
| -rw-r--r-- | science/liblinear/pkg-descr | 24 |
1 files changed, 15 insertions, 9 deletions
diff --git a/science/liblinear/pkg-descr b/science/liblinear/pkg-descr index f765f91d8913..fbf26fa3b5ff 100644 --- a/science/liblinear/pkg-descr +++ b/science/liblinear/pkg-descr @@ -1,14 +1,20 @@ 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), L1-regularized classifiers -(L2-loss linear SVM and logistic regression). +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 and similar usage -- One-vs-the rest and Crammer & Singer multi-class classification -- Cross validation for model selection +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: http://www.csie.ntu.edu.tw/~cjlin/liblinear/ +WWW: https://www.csie.ntu.edu.tw/~cjlin/liblinear/ |