Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10339652 | Computer Networks | 2005 | 21 Pages |
Abstract
The proposed techniques, based on the Support Vector Machine paradigm, have been implemented and compared, on the same data set, with other approaches considered in scientific literature. Tests performed in a real-world environment show that results are comparable, with the advantage of a low algorithmic complexity in the normal operating phase. Moreover, the algorithm is particularly suitable for classification, where it outperforms the other techniques.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Networks and Communications
Authors
Mauro Brunato, Roberto Battiti,