
Advances in Kernel Methods
Support Vector Learning
Edición de la obra Advances in kernel methods
| Autor | Alexander J. Smola |
|---|---|
| Editorial | The MIT Press |
| Fecha de publicación | December 18, 1998 |
| Idioma | inglés |
| Páginas | 386 |
| Formato | Hardcover |
| ISBN-13 | 9780262194167 |
| ISBN-10 | 0262194163 |
| Número de Cutter | S666a |
The Support Vector Machine is a powerful new learning algorithm for solving a variety of learning and function estimation problems, such as pattern recognition, regression estimation, and operator inversion. The impetus for this collection was a workshop on Support Vector Machines held at the 1997 NIPS conference. The contributors, both university researchers and engineers developing applications for the corporate world, form a Who's Who of this exciting new area.