Project details for MSVMpack

Logo JMLR MSVMpack 1.5

by lauerfab - July 3, 2014, 16:02:49 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ]

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Description:

MSVMpack is dedicated to multi-class support vector machines (M-SVM), which can handle more than two classes without relying on decomposition methods, and implements the four M-SVM models from the literature: Weston and Watkins M-SVM, Crammer and Singer M-SVM, Lee, Lin and Wahba M-SVM, and the M-SVM2 of Guermeur and Monfrini.

MSVMpack provides the first parallel implementation of M-SVMs and use vectorized kernel functions depending on the data type for faster computations.

The software is based on two command-line tools, but also provides a full library (C API) to include its functionalities in other programs and a Matlab interface. Templates are provided to ease the addition of custom kernels.

Changes to previous version:
  • Windows binaries are now included (by Emmanuel Didiot)
  • MSVMpack can now be compiled on Windows (by Emmanuel Didiot)
  • Fixed polynomial kernel
  • Minor bug fixes
BibTeX Entry: Download
Corresponding Paper BibTeX Entry: Download
URL: Project Homepage
JMLR MLOSS PaperURL: JMLR-MLOSS Paper Homepage
Supported Operating Systems: Linux, Macosx, Windows
Data Formats: Ascii, Matlab
Tags: Kernel, Svm, Support Vector Machines, Parallel, Msvm, Multiclass Support Vector Machine, Server
Archive: download here

Other available revisons

Version Changelog Date
1.5
  • Windows binaries are now included (by Emmanuel Didiot)
  • MSVMpack can now be compiled on Windows (by Emmanuel Didiot)
  • Fixed polynomial kernel
  • Minor bug fixes
July 3, 2014, 16:02:49
1.4
  • Added parallelized k-Fold cross validation ('-cv k' option in trainmsvm)
  • Cache size now defaults to the maximum amount of memory
  • Minor bug fixes for the Matlab interface
August 30, 2013, 10:40:35
1.3
  • Added Matlab interface.
April 23, 2013, 10:44:37
1.2
  • Added MSVMpack Server and Web interface
  • Now becomes platform-independent at the client side
  • Can import files in LibSVM data format and raw matrix format
  • Model is saved periodically during training
February 7, 2013, 13:25:44
1.1
  • Possibility to choose different values of C for different classes (useful for unbalanced data sets)
  • Sets the number of working threads at runtime (through the command-line option '-t')
  • Builds on Mac OS X
  • Small changes in the model files
  • Several bug fixes
October 25, 2011, 14:24:21
1.0

Bibtex entry of the corresponding JMLR paper.

July 10, 2011, 12:09:12

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