Abstract
Data pre-processing always plays a key role in learning algorithm performance. In this research we consider data pre-processing by normalization for Support Vector Machines (SVMs). We examine the normalization affect across 112 classification problems with SVM using the rbf kernel. We observe a significant classification improvement due to normalization. Finally we suggest a rule based method to find when normalization is necessary for a specific classification problem. The best normalization method is also automatically selected by SVM itself.
Original language | English |
---|---|
Title of host publication | AI 2006: Advances in Artificial Intelligence, Proceedings of 19th Australian Joint Conference on Artificial Intelligence |
Editors | Alfred Hofmann |
Place of Publication | Germany |
Publisher | Springer |
Pages | 362 - 371 |
Number of pages | 10 |
Volume | 4304 |
ISBN (Print) | 978-3-540-49787-5 |
Publication status | Published - 2006 |
Externally published | Yes |
Event | Australasian Joint Conference on Artificial Intelligence 2006 - Hobart, Australia Duration: 4 Dec 2006 → 8 Dec 2006 Conference number: 19th https://link.springer.com/book/10.1007/11941439 (Proceedings) |
Conference
Conference | Australasian Joint Conference on Artificial Intelligence 2006 |
---|---|
Abbreviated title | AI 2006 |
Country/Territory | Australia |
City | Hobart |
Period | 4/12/06 → 8/12/06 |
Internet address |
|