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Advances in Large-Margin Classifiers (Neural Information Processing series) - Hardcover

 
9780262194488: Advances in Large-Margin Classifiers (Neural Information Processing series)
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Reseña del editor:
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.
Biografía del autor:
Alexander J. Smola is Senior Principal Researcher and Machine Learning Program Leader at National ICT Australia/Australian National University, Canberra. Bernhard Schoelkopf is Director at the Max Planck Institute for Intelligent Systems in Tubingen, 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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Smola, Alexander J
Verlag: A Bradford Book (2000)
ISBN 10: 0262194481 ISBN 13: 9780262194488
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Buchbeschreibung Hardcover. Zustand: new. 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. Bestandsnummer des Verkäufers DADAX0262194481

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Bartlett, Peter J.; Schölkopf, Bernhard; Schuurmans, Dale; Smola, Alex J.
Verlag: The MIT Press (2000)
ISBN 10: 0262194481 ISBN 13: 9780262194488
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Buchbeschreibung Hardcover. Zustand: New. Zustand des Schutzumschlags: New. Brand New! The interior pages are clean and unmarked. Electronic delivery tracking will be issued free of charge. Bestandsnummer des Verkäufers 03714

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Bartlett, Peter J. (Editor); Schölkopf, Bernhard (Editor); Schuurmans, Dale (Editor); Smola, Alex J. (Editor)
ISBN 10: 0262194481 ISBN 13: 9780262194488
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Buchbeschreibung Hardcover. Zustand: New. Zustand des Schutzumschlags: New. First Edition. Brand New in Brand New dust jacket. Electronic delivery tracking will be issued free of charge. Bestandsnummer des Verkäufers 08936

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Bartlett, Peter J. (Editor); Schölkopf, Bernhard (Editor); Schuurmans, Dale (Editor); Smola, Alex J. (Editor)
ISBN 10: 0262194481 ISBN 13: 9780262194488
Neu Hardcover Erstausgabe Anzahl: 1
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Buchbeschreibung Hardcover. Zustand: New. Zustand des Schutzumschlags: New. First Edition. Brand New in Brand New dust jacket. Electronic delivery tracking will be issued free of charge. Bestandsnummer des Verkäufers 08937

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