Support Vector Machines

Name: Support Vector Machines
Brand: Springer-Verlag New York Inc.
SKU: 9780387772417
Price: 951.46 PLN
Availability: InStock

Autor: Ingo Steinwart, Andreas Christmann

Język:

Oprawa: Twarda

Wydawca: Springer-Verlag New York Inc.

Dostępność: Dostępna u dostawcy

Wysyłamy za 10-13 dni

951.46 zł

This book explains the principles that make support vector machines (SVMs) a successful modelling an...

Informacje o książce

Autor

Ingo Steinwart, Andreas Christmann

Język

Angielski

Oprawa

Książka - Twarda

Data wydania

2008

strony

601

EAN

9780387772417

ISBN

0387772413

Enbook ID

02105825

Wydawca

Springer-Verlag New York Inc.

Waga

1054

Wymiary

163 x 241 x 38

Pełny opis

This book explains the principles that make support vector machines (SVMs) a successful modelling and prediction tool for a variety of applications. The authors present the basic ideas of SVMs together with the latest developments and current research questions in a unified style. They identify three reasons for the success of SVMs: their ability to learn well with only a very small number of free parameters, their robustness against several types of model violations and outliers, and their computational efficiency compared to several other methods.The book provides a unique in-depth treatment of both fundamental and recent material on SVMs that so far has been scattered in the literature. The book can thus serve as both a basis for graduate courses and an introduction for statisticians, mathematicians, and computer scientists. It further provides a valuable reference for researchers working in the field. The book covers all important topics concerning support vector machines such as: loss functions and their role in the learning process; reproducing kernel Hilbert spaces and their properties; a thorough statistical analysis that uses both traditional uniform bounds and more advanced localized techniques based on Rademacher averages and Talagrand's inequality; a detailed treatment of classification and regression; a detailed robustness analysis; and a description of some of the most recent implementation techniques. To make the book self-contained, an extensive appendix is added which provides the reader with the necessary background from statistics, probability theory, functional analysis, convex analysis, and topology.

Możesz być zainteresowany

Klienci, którzy kupili tę książkę, kupili również

Najczęściej wyszukiwane

Categories

Authors

Publishers

Produkty

Produkty

Najczęściej wyszukiwane

Categories

Authors

Publishers

Produkty

Produkty

Support Vector Machines

Informacje o książce

Pełny opis

Możesz być zainteresowany

Klienci, którzy kupili tę książkę, kupili również