Learning with kernels : support vector machines, regularization, optimization, and beyond
In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs -kernels, for a number of learning tasks. Ker...
Enregistré dans:
Auteurs principaux : | , |
---|---|
Format : | Livre |
Langue : | anglais |
Titre complet : | Learning with kernels : support vector machines, regularization, optimization, and beyond / Bernhard Schölkopf, Alexander J. Smola |
Publié : |
Cambridge (Mass.), London :
The MIT Press
, C 2002 |
Description matérielle : | 1 vol. (XVIII-626 p.) |
Collection : | Adaptative computation and machine learning series |
Sujets : |
Chargement en cours