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diff --git a/science/liblinear/pkg-descr b/science/liblinear/pkg-descr
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 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/