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ATOMS : libsvm and liblinear details

libsvm and liblinear

Libraries for SVM and large-scale linear classification
(21369 downloads for this version - 77831 downloads for all versions)
Details
Version
1.5
Authors
Holger Nahrstaedt
Chih-Chung Chang
Chih-Jen Lin
Owner Organization
Technische Universitaet Berlin
Maintainers
Administrator ATOMS
Holger Nahrstaedt
Chin Luh Tan
License
Creation Date
August 30, 2019
Source created on
Scilab 6.0.x
Binaries available on
Scilab 6.0.x:
Linux 64-bit Windows 64-bit
Install command
--> atomsInstall("libsvm")
Description
 This tool provides a simple interface to LIBSVM, a library for support vector
machines (http://www.csie.ntu.edu.tw/~cjlin/libsvm).
It is very easy to use as
the usage and the way of specifying parameters are the same as that of LIBSVM.
This tool provides also a simple interface to LIBLINEAR, a library for
large-scale regularized linear classification (http://www.csie.ntu.edu.tw/~cjlin/liblinear).
 It is very easy to use as the usage and the way of specifying parameters are
the same as that of LIBLINEAR.
This Toolbox is compatible with the NaN-toolbox!
Changelog
============
1.5.0
 - module fixed to work with Scilab 6
 - libsvmread fixed
 - some bugs fixed in the help file examples
1.4.5
 - libsvm_loadmodel and libsvm_savemodel fixed
 - st_deviation renamed to stdev
1.4.4
 - 2nu-SVM added http://www.ece.rice.edu/~md/np_svm.php
 - LIBLINEAR is updated to 1.94
 - LIBSVM is updated to 3.20
 - some bugfixes
 - The crossvalidation (libsvm_svmtrain with "-v 5") result is now a
vector with [Cross Validation Accuracy, Positive Cross Validation Accuracy,
Negative Cross Validation Accuracy]
1.4.3
 - Depreated stack-c function were removed
1.4.2
 - new functions libsvm_savemodel and libsvm_loadmodel
1.4.1
 - buxfix for getpath
 - help files fixed for libsvm_linpredict and libsvm_lintrain
 - path operations are replaced by fullfile
1.4.0
 - unit tests for libsvmwrite and libsvmread
 - fix issues 805, 806, 808, 809, 813, 814, 
 - renaming of the following functions:
 *svmtrain > libsvm_svmtrain
 *svmpredict > libsvm_svmpredict
 *train > libsvm_lintrain
 *predict > libsvm_linpredict
 *svmconfmat > libsvm_confmat
 *svmgrid > libsvm_grid
 *svmgridlinear > libsvm_gridlinear
 *svmnormalize > libsvm_normalize
 *svmpartest > libsvm_partest
 *svmrocplot > libsvm_rocplot
 *svmscale > libsvm_scale
 *svmtoy > libsvm_toy
1.3.1
 - compatible with scilab-5.4.0-beta-1 and scilab-5.4.0-alpha-1 or lower
1.3
 - compatible with scilab-5.4.0-beta-1
 - incompatible with scilab-5.4.0-alpha-1 and lower
 - fix several bugs in examples
 - fix precomputed kernel bug in svmtrain
 - LIBLINEAR is updated to 1.91
 - LIBSVM is updated to 3.12
1.2.2
 - some bug fixes
 - help files improved
1.2.1
 - svmtoy added
 - improved error handling in sci_gateway
 - improved help files
 - bug in performance demo removed
1.2
 - the Nan-Toolbox 1.3 is compatible to this toolbox now!
 - improved help-files
 - improved demos
 - LIBLINEAR with optional instance weight support
1.1
 - improved demos
 - works under Windows
 - new function: svmnormalize 
1.0
 - first release of libsvm - toolbox
This interface was initially written by Jun-Cheng Chen, Kuan-Jen Peng,
Chih-Yuan Yang and Chih-Huai Cheng from Department of Computer
Science, National Taiwan University. 
It was converted to Scilab 5.3 by Holger Nahrstaedt from TU Berlin.
If you find this tool useful, please cite LIBSVM as follows
Chih-Chung Chang and Chih-Jen Lin, LIBSVM : a library for support
vector machines. ACM Transactions on Intelligent Systems and
Technology, 2:27:1--27:27, 2011. Software available at
http://www.csie.ntu.edu.tw/~cjlin/libsvm
Please cite LIBLINEAR as follows
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.Software available at
http://www.csie.ntu.edu.tw/~cjlin/liblinear
 
Files (4)
[348.18 kB]
Linux 64-bit binary for Scilab 6.0.x
Upload date : 2019年08月30日 15:26:19
MD5 : 9296a45a46f50624474b596b7b5968ea
SHA1 : ea23a96164f0aceb44245c2109ba54e799bc0cea
Downloads : 9427
 
[253.03 kB]
Source code archive
Upload date : 2019年08月30日 15:25:42
MD5 : e1b48154a256c1d40de0aceedab029df
SHA1 : 946df58baa015675fbc3773a3e26f1988f36828e
Downloads : 858
 
[350.94 kB]
Windows 64-bit binary for Scilab 6.0.x
Upload date : 2019年08月30日 15:26:05
MD5 : fad4781945ec439a580fb189dc65bede
SHA1 : 8b5b48ec8c27dd9600e4f366320ad8d3584997f8
Downloads : 10075
 
[57.13 kB]
Miscellaneous file
Upload date : 2019年08月30日 15:25:42
MD5 : b26c8fe4e1c54b1f8cfd43548647dd5c
SHA1 : 3525f471482c6a274a29ca5f20cd244598ee7f7f
Downloads : 1009
 
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