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authorrafan <rafan@FreeBSD.org>2008-06-03 10:29:39 +0800
committerrafan <rafan@FreeBSD.org>2008-06-03 10:29:39 +0800
commit1d402e861d47341a5ca31269d50e0c7758e07044 (patch)
tree9e23e1f8c1459cc2312d7e102f27c4ad94896029 /science
parent6b6ca4602e80ac894f18a438ad8cf2696f3e7347 (diff)
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- Update pkg-descr for recent updates
Diffstat (limited to 'science')
-rw-r--r--science/liblinear/pkg-descr18
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/