Advances in Kernel Methods
Support Vector Learning
Edición de la obra Advances in kernel methods
| Autor | Christopher J. C. Burges, Alexander J. Smola, Bernhard Schölkopf |
|---|---|
| Editorial | MIT Press |
| Fecha de publicación | 1999 |
| Idioma | inglés |
| ISBN-13 | 9780585128290 |
| Número de Cutter | B955a |
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.