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A wrapper around the LIBLINEAR C/C++ library for machine learning (available at <https://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.
| Version: | 2.10-24 |
| Imports: | methods |
| Suggests: | SparseM, Matrix |
| Published: | 2024-09-13 |
| DOI: | 10.32614/CRAN.package.LiblineaR |
| Author: | Thibault Helleputte [cre, aut, cph], Jérôme Paul [aut], Pierre Gramme [aut] |
| Maintainer: | Thibault Helleputte <thibault.helleputte at dnalytics.com> |
| License: | GPL-2 |
| URL: | <https://dnalytics.com/software/liblinear/> |
| NeedsCompilation: | yes |
| Citation: | LiblineaR citation info |
| Materials: | README NEWS |
| In views: | MachineLearning |
| CRAN checks: | LiblineaR results |
| Reference manual: | LiblineaR.pdf |
| Package source: | LiblineaR_2.10-24.tar.gz |
| Windows binaries: | r-devel: LiblineaR_2.10-24.zip, r-release: LiblineaR_2.10-24.zip, r-oldrel: LiblineaR_2.10-24.zip |
| macOS binaries: | r-release (arm64): LiblineaR_2.10-24.tgz, r-oldrel (arm64): LiblineaR_2.10-24.tgz, r-release (x86_64): LiblineaR_2.10-24.tgz, r-oldrel (x86_64): LiblineaR_2.10-24.tgz |
| Old sources: | LiblineaR archive |
| Reverse depends: | LKT |
| Reverse imports: | ILoReg, kebabs, PrInCE, quanteda.textmodels, scBio, SIAMCAT, sweater |
| Reverse suggests: | flowml, mlr, parsnip, RSSL, tidyAML, vetiver |
Please use the canonical form https://CRAN.R-project.org/package=LiblineaR to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.