LiblineaR: Linear Predictive Models Based on the LIBLINEAR C/C++ Library

A wrapper around the LIBLINEAR C/C++ library for machine learning (available at http://www.csie.ntu.edu.tw/~cjlin/liblinear). LIBLINEAR is a simple library for solving large-scale regularized linear classification and regression. It currently supports L2-regularized classification (such as logistic regression, L2-loss linear SVM and L1-loss linear SVM) as well as L1-regularized classification (such as L2-loss linear SVM and logistic regression) and L2-regularized support vector regression (with L1- or L2-loss). The main features of LiblineaR include multi-class classification (one-vs-the rest, and Crammer & 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.

AuthorThibault Helleputte <thibault.helleputte@dnalytics.com>; Pierre Gramme <pierre.gramme@dnalytics.com>
Date of publication2015-02-04 08:28:04
MaintainerThibault Helleputte <thibault.helleputte@dnalytics.com>
LicenseGPL-2
Version1.94-2
http://dnalytics.com/liblinear/

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Files in this package

LiblineaR
LiblineaR/COPYING
LiblineaR/inst
LiblineaR/inst/CITATION
LiblineaR/tests
LiblineaR/tests/testLiblineaR.R
LiblineaR/tests/RSquared.R
LiblineaR/src
LiblineaR/src/Makevars
LiblineaR/src/trainLinear.c
LiblineaR/src/tron.h
LiblineaR/src/tron.cpp
LiblineaR/src/linear.h
LiblineaR/src/predictLinear.c
LiblineaR/src/linear.cpp
LiblineaR/NAMESPACE
LiblineaR/NEWS
LiblineaR/R
LiblineaR/R/heuristicC.R LiblineaR/R/predict.R LiblineaR/R/LiblineaR.R
LiblineaR/MD5
LiblineaR/README
LiblineaR/DESCRIPTION
LiblineaR/man
LiblineaR/man/predict.LiblineaR.Rd LiblineaR/man/LiblineaR.Rd LiblineaR/man/heuristicC.Rd

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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