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| -rw-r--r-- | science/liblinear/pkg-descr | 18 |
1 files changed, 7 insertions, 11 deletions
diff --git a/science/liblinear/pkg-descr b/science/liblinear/pkg-descr index e9f2edc6176d..b0dc747b819b 100644 --- a/science/liblinear/pkg-descr +++ b/science/liblinear/pkg-descr @@ -1,17 +1,13 @@ LIBLINEAR is a linear classifier for data with millions of instances and -features. It supports both logistic regression and L2-loss linear SVM using a -trust region Newton method in - -C.-J. Lin, R. C. Weng, and S. S. Keerthi. Trust region Newton method -for large-scale regularized logistic regression. Technical report, 2007. -A short version appears in ICML 2007. +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 and similar usage -One-vs-the rest multi-class classification -Cross validation for model selection -Probability estimates (logistic regression only) -Weights for unbalanced data +- Same data format as LIBSVM and similar usage +- One-vs-the rest multi-class classification +- Cross validation for model selection +- Probability estimates (logistic regression only) +- Weights for unbalanced data WWW: http://www.csie.ntu.edu.tw/~cjlin/liblinear/ |