ASVM is a fast technique for training linear support vector machines (SVMs), based on an active set approach which results in very fast running times. For example, it has been used to classify a dataset with 4 million points and 32 features in only 38 minutes on a 400 Mhz Pentium II. For more information, see our paper Active Support Vector Machines.

SVMs are an optimization based approach for solving machine learning problems. For an introduction to SVMs, you may want to look at this tutorial.

The software is free for academic use. For commercial use, please contact Dave Musicant.

Click here to download the software. The software consists of:

• A stand-alone executable to do training
• A stand-alone executable to do testing
• A mexfile for use in the MATLAB environment

No additional software whatsoever is required to use these tools.

If you publish any work based on ASVM, please cite both the software and the paper on which it is based. Here are recommended LaTeX bibliography entries:

@misc{asvm,
author = "D. R. Musicant",
title = {{ASVM Software:} Active Set Support Vector Machine Classification Software},
year = 2000,
institution = {Computer Sciences Department, University of Wisconsin, Madison},
note = { www.cs.wisc.edu/$\sim$musicant/asvm/.}}

@techreport{mm:00,
author = "O. L. Mangasarian and David R. Musicant",
title = "Active Support Vector Machine Classification",
institution = "Data Mining Institute, Computer Sciences Department, University of Wisconsin",
month = {April},
year = 2000,
number = {00-04},
address = "Madison, Wisconsin",
note={ftp://ftp.cs.wisc.edu/pub/dmi/tech-reports/00-04.ps}}