<?xml version="1.0"?>
<!DOCTYPE rdf:RDF SYSTEM "http://dublincore.org/documents/2002/07/31/dcmes-xml/dcmes-xml-dtd.dtd" > 
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/">
 <rdf:Description>
  <dc:title>Linear Predictive Models Based On The Liblinear C/C++ Library</dc:title>
  <dc:subject>CRAN Task View: MachineLearning (http://CRAN.R-project.org/view=MachineLearning)</dc:subject>
  <dc:description>This R package is a wrapper around the liblinear C/C++
library for machine learning. LIBLINEAR is a linear classifier
for data with millions of instances and features. It supports
L2-regularized classifiers (such as L2-loss linear SVM, L1-loss
linear SVM, and logistic regression) as well as L1-regularized
classifiers (such as L2-loss linear SVM and logistic
regression). The main features of LiblineaR include multi-class
classification (one-vs-the rest, and Crammer &amp; Singer method),
cross validation for model selection, probability estimates
(logistic regression only) or weights for unbalanced data. The
estimation of the models is particularly fast as compared to
other libraries. For more information on the C/C++ liblinear
library itself, refer to R.-E. Fan, K.-W. Chang, C.-J. Hsieh,
X.-R. Wang, and C.-J. Lin. LIBLINEAR: A Library for Large
Linear Classification, Journal of Machine Learning Research
9(2008), 1871-1874, available at
http://www.csie.ntu.edu.tw/~cjlin/liblinear . The two first
blocks of the package version indicates which version of
liblinear is currently supported. For example: 1.32-14 means
that the package supports the version 1.32 of liblinear.</dc:description>
  <dc:type>Software</dc:type>
  <dc:creator>Thibault Helleputte &lt;thelleputte@gmail.com&gt;</dc:creator>
  <dc:contributor>Thibault Helleputte &lt;thelleputte@gmail.com&gt;</dc:contributor>
  <dc:rights>GPL-2</dc:rights>
  <dc:date>2011-04-23</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>http://CRAN.R-project.org/package=LiblineaR</dc:identifier>
 </rdf:Description>
</rdf:RDF>

