BSVM 2.09 released on December 15, 2018.
The two multi-class implementations included after BSVM 2.01 are two of the five methods compared in the following paper: A comparison on methods for multi-class support vector machines . (However, there is one difference: In the paper kernel caches stored numbers in double precision but in this release cached values are in single precision)
The current implementation borrows the structure of libsvm. Similar options are also adopted. For the bound-constrained formulation for classification and regression, BSVM uses a decomposition method. BSVM uses a simple working set selection which leads to faster convergences for difficult cases. The use of a special implementation of the opmization solver TRON allows BSVM to stably identify bounded variables.
The current release (Version 2.09, December 2018)
can be obtained by
zip file that contains the software.
The README file
contains instructions on how
to install the software.
Please e-mail us if you have problems
to download the file.
Note that BSVM is provided "as is" without express or implied warranty. This software can be freely used for research purpose. Use for commercial purposes is expressly prohibited without contacting the authors.
For additional information on BSVM, please see the following two papers
For information about multi-class implementations, see
If you have any problems using BSVM, we are happy to provide help. Please send comments and suggestions to Chih-Jen Lin.
Acknowledgments: The authors thank Chih-Chung Chang for many helpful disussions and comments. Part of the software implementation also benifited from his help. BSVM 2.06 was prepared by Rong-En Fan. BSVM 2.07, 2.08 were prepared by Ching-Pei Lee.