Support Vector Machines: Theory and Applications
The support vector machine (SVM) has become one of the standard tools for machine learning and data mining. This carefully edited volume presents the state of the art of the mathematical foundation of SVM in statistical learning theory, as well as novel algorithms and applications. Support Vector Ma...
| Συγγραφή απο Οργανισμό/Αρχή: | |
|---|---|
| Άλλοι συγγραφείς: | |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Berlin, Heidelberg :
Springer Berlin Heidelberg,
2005.
|
| Σειρά: | Studies in Fuzziness and Soft Computing,
177 |
| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
| Περίληψη: | The support vector machine (SVM) has become one of the standard tools for machine learning and data mining. This carefully edited volume presents the state of the art of the mathematical foundation of SVM in statistical learning theory, as well as novel algorithms and applications. Support Vector Machines provides a selection of numerous real-world applications, such as bioinformatics, text categorization, pattern recognition, and object detection, written by leading experts in the respective fields. |
|---|---|
| Φυσική περιγραφή: | X, 431 p. online resource. |
| ISBN: | 9783540323846 |
| ISSN: | 1434-9922 ; |
