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 Machines provides a selection of numerous real-world applications, such as bioinformatics, text categorization, pattern recognition, and object detection, written by leading experts in their respective fields.

Riassunto

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 their respective fields.

Dettagli sul prodotto

• Con la collaborazione di: Lipo Wang (Editore), Lip Wang (Editore)
• Editore: Springer, Berlin
• Contenuto: Libro
• Forma del prodotto: Tascabile
• Data pubblicazione: 13.10.2010
• Categoria: Scienze naturali, medicina, informatica, tecnica > Informatica, EDP > Informatica
• EAN: 9783642063688
• ISBN: 978-3-642-06368-8
• Numero di pagine: 431
• Illustrazioni: X, 431 p.
• Dimensioni (della confezione): 15.9 x 2.2 x 23.7 cm
• Peso (della confezione): 668 g
• Serie: Studies in Fuzziness and Soft Computing > 177; Studies in Fuzziness and Soft Computing
• Categorie: C, Model, Künstliche Intelligenz, Artificial Intelligence, Mustererkennung, Mathematik für Ingenieure, engineering, Theory of Computation, pattern recognition, Mathematical and Computational Engineering, Computers, Engineering mathematics, Automated Pattern Recognition, Mathematical theory of computation, Applied mathematics, Mathematical and Computational Engineering Applications, Maths for engineers, proving