BSVM

Chih-Wei Hsu and Chih-Jen Lin

BSVM 2.08 released on June 18, 2012. We added Crammer and Singer multi-class SVM with squared hinge (L2) loss. We also supported precomputed kernel.

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)


Introduction

BSVM solves support vector machines (SVM) for the solution of large classification and regression problems. It includes the following methods

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.


Download BSVM

The current release (Version 2.08, June 2012) of BSVM can be obtained by downloading the 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: For MS Windows users, there are binary executable files in the windows directory after you unzip 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.


Additional Information

For additional information on BSVM, please see the following two papers


For information about how BSVM handles libear SVM, see However, if you would like to use linear kernel, we recommend LIBLINEAR instead.

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.


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