Multiclass Learning at One-class Complexity
Szedmak, Sandor and Shawe-Taylor, John (2005) Multiclass Learning at One-class Complexity.
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Description/Abstract
We show in this paper the multiclass classification problem can be implemented in the maximum margin framework with the complexity of one binary Support Vector Machine. We show reducing the complexity does not involve diminishing performance but in some cases this approach can improve the classification accuracy. The multiclass classification is realized in the framework where the output labels are vector valued.
| Item Type: | Monograph (Technical Report) |
|---|---|
| Keywords: | Maximum margin learning, Hilbertian vector label, multiclass learning, Support vector machine |
| Divisions: | Faculty of Physical and Applied Science > Electronics and Computer Science |
| Item ID: | 261157 |
| Date Deposited: | 19 Aug 2005 |
| Last Modified: | 02 Mar 2012 00:47 |
| Contributors: | Szedmak, Sandor (Author) Shawe-Taylor, John (Author) |
| Date: | 2005 |
| Status: | Published |
| Further Information: | Google Scholar |
| URI: | http://eprints.soton.ac.uk/id/eprint/261157 |
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