Advances in kernel methods
support vector learning
Edición de la obra Advances in kernel methods
| Autor | Alexander J. Smola |
|---|---|
| Editorial | MIT Press, Philomel Books, The MIT Press |
| Fecha de publicación | 1999 |
| Lugar | Cambridge, Mass |
| Idioma | inglés |
| Páginas | 376 |
| ISBN-10 | 0262194163 |
| OCLC | 44957981, 39706960, 39706952 |
| LCCN | 98040302, 98040403 |
| 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.