Advances in Large-Margin Classifiers (Neural Information Processing)

Bartlett, Peter J.; Sch�lkopf, Bernhard; Schuurmans, Dale; Smola, Alex J.

ISBN 10: 0262194481 ISBN 13: 9780262194488

Editorial: The MIT Press

Idioma: Ingl�s

Condici�n: Nuevo Encuadernaci�n de tapa dura

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Descripci�n

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Detalles bibliogr�ficos

T�tulo

Advances in Large-Margin Classifiers (Neural Information Processing)

Editor

The MIT Press

Idioma

Ingl�s

ISBN 10

0262194481

ISBN 13

9780262194488

Encuadernaci�n

Hardcover

Estado

New

Estado de la sobrecubierta

New

Cat�logos de vendedores

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Sinopsis

The book provides an overview of recent developments in large margin classifiers, examines connections with other methods (e.g., Bayesian inference), and identifies strengths and weaknesses of the method, as well as directions for future research.

The concept of large margins is a unifying principle for the analysis of many different approaches to the classification of data from examples, including boosting, mathematical programming, neural networks, and support vector machines. The fact that it is the margin, or confidence level, of a classification�that is, a scale parameter�rather than a raw training error that matters has become a key tool for dealing with classifiers. This book shows how this idea applies to both the theoretical analysis and the design of algorithms. The book provides an overview of recent developments in large margin classifiers, examines connections with other methods (e.g., Bayesian inference), and identifies strengths and weaknesses of the method, as well as directions for future research. Among the contributors are Manfred Opper, Vladimir Vapnik, and Grace Wahba.

Acerca de los autores

Alexander J. Smola is Senior Principal Researcher and Machine Learning Program Leader at National ICT Australia/Australian National University, Canberra.

Bernhard Sch�lkopf is Director at the Max Planck Institute for Intelligent Systems in T�bingen, Germany. He is coauthor of Learning with Kernels (2002) and is a coeditor of Advances in Kernel Methods: Support Vector Learning (1998), Advances in Large-Margin Classifiers (2000), and Kernel Methods in Computational Biology (2004), all published by the MIT Press.

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Descripci�n de la librer�a

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