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./math/liblinear, Library for large linear classification
[
Branch: CURRENT, Version: 2.49, Package name: liblinear-2.49, Maintainer: cheusov
LIBLINEAR is a linear classifier for data with millions of instances
and features. It supports
L2-regularized classifiers
L2-loss linear SVM, L1-loss linear SVM, and logistic regression (LR)
L1-regularized classifiers (after version 1.4)
L2-loss linear SVM and logistic regression (LR)
L2-regularized support vector regression (after version 1.9)
L2-loss linear SVR and L1-loss linear SVR.
Main features of LIBLINEAR include
Same data format as LIBSVM, our general-purpose SVM solver,
and also similar usage
Multi-class classification: 1) one-vs-the rest, 2) Crammer & Singer
Cross validation for model selection
Probability estimates (logistic regression only)
Weights for unbalanced data
MATLAB/Octave, Java, Python, Ruby interfaces
Required to build:
[pkgtools/cwrappers]
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./math/liblinear, Library for large linear classification
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Branch: CURRENT, Version: 2.49, Package name: liblinear-2.49, Maintainer: cheusov
LIBLINEAR is a linear classifier for data with millions of instances
and features. It supports
L2-regularized classifiers
L2-loss linear SVM, L1-loss linear SVM, and logistic regression (LR)
L1-regularized classifiers (after version 1.4)
L2-loss linear SVM and logistic regression (LR)
L2-regularized support vector regression (after version 1.9)
L2-loss linear SVR and L1-loss linear SVR.
Main features of LIBLINEAR include
Same data format as LIBSVM, our general-purpose SVM solver,
and also similar usage
Multi-class classification: 1) one-vs-the rest, 2) Crammer & Singer
Cross validation for model selection
Probability estimates (logistic regression only)
Weights for unbalanced data
MATLAB/Octave, Java, Python, Ruby interfaces
Required to build:
[pkgtools/cwrappers]
Master sites:
Filesize: 72.613 KBVersion history: (Expand)
- (2025-10-24) Package has been reborn
- (2025-10-24) Package deleted from pkgsrc
- (2025-07-15) Package has been reborn
- (2025-07-15) Package deleted from pkgsrc
- (2025-05-29) Updated to version: liblinear-2.49
- (2025-01-05) Updated to version: liblinear-2.48
CVS history: (Expand)
| 2025-05-29 09:20:57 by Adam Ciarcinski | Files touched by this commit (2) | |
Log message: liblinear: updated to 2.49 2.49 We continue to improve the Python interface. |
| 2025-01-05 10:12:32 by Adam Ciarcinski | Files touched by this commit (3) | |
Log message: liblinear: updated to 2.48 2.48 Unknown changes |
| 2024-02-05 22:11:45 by Adam Ciarcinski | Files touched by this commit (4) | |
Log message: liblinear: updated to 2.47 Version 2.47 released on July 9, 2023. We fix some minor bugs. |
| 2021-10-26 12:56:13 by Nia Alarie | Files touched by this commit (458) |
Log message: math: Replace RMD160 checksums with BLAKE2s checksums All checksums have been double-checked against existing RMD160 and SHA512 hashes |
| 2021-10-07 16:28:36 by Nia Alarie | Files touched by this commit (458) |
Log message: math: Remove SHA1 hashes for distfiles |
| 2021-04-16 08:48:04 by Adam Ciarcinski | Files touched by this commit (2) | |
Log message: liblinear: updated to 2.43 Version 2.43 Installing the Python interface through PyPI is supported. Version 2.42 For dual CD solvers (logistic/l2 losses but not l1 loss), if a maximal number of \ iterations is reached, LIBLINEAR directly switches to run a primal Newton \ solver. |
| 2020-10-28 20:32:33 by Adam Ciarcinski | Files touched by this commit (3) | |
Log message: liblinear: updated to 2.41 Version 2.41 released on July 29, 2020 (some bug fixes of version 2.40). Version 2.40 released on July 22, 2020. A new solver: dual coordinate descent method for linear one-class SVM; see the paper The Newton solver is updated to have faster training speed; see the release note A new option -R to allow users not to regularize bias (when -B 1 is used) |
| 2017-11-15 23:12:56 by Thomas Klausner | Files touched by this commit (1) |
Log message: liblinear: follow redirects |
