MSVMpack

MSVMpack: a multi-class support vector machine package. This paper describes MSVMpack, an open source software package dedicated to our generic model of multi-class support vector machine. All four multi-class support vector machines (M-SVMs) proposed so far in the literature appear as instances of this model. MSVMpack provides for them the first unified implementation and offers a convenient basis to develop other instances. This is also the first parallel implementation for M-SVMs. The package consists in a set of command-line tools with a callable library. The documentation includes a tutorial, a user’s guide and a developer’s guide.

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References in zbMATH (referenced in 8 articles , 1 standard article )

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  1. Breschi, Valentina; Piga, Dario; Bemporad, Alberto: Piecewise affine regression via recursive multiple least squares and multicategory discrimination (2016)
  2. van den Burg, Gerrit J. J.; Groenen, Patrick J. F.: GenSVM: a generalized multiclass support vector machine (2016)
  3. Didiot, Emmanuel; Lauer, Fabien: Efficient optimization of multi-class support vector machines with MSVMpack (2015)
  4. Guo, Husheng; Wang, Wenjian: An active learning-based SVM multi-class classification model (2015)
  5. Murua, Alejandro; Wicker, Nicolas: Kernel-based mixture models for classification (2015)
  6. Rodriguez-Lujan, Irene; Huerta, Ramon: A Fisher consistent multiclass loss function with variable margin on positive examples (2015)
  7. Djuric, Nemanja; Lan, Liang; Vucetic, Slobodan; Wang, Zhuang: BudgetedSVM: a toolbox for scalable SVM approximations (2013)
  8. Lauer, Fabien; Guermeur, Yann: MSVMpack: a multi-class support vector machine package (2011)