Boosting: Foundations and Algorithms (Adaptive Computation and Machine Learning series)

Valutazione media 3,88
( su 17 valutazioni fornite da Goodreads )
 
9780262526036: Boosting: Foundations and Algorithms (Adaptive Computation and Machine Learning series)

Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate "rules of thumb." A remarkably rich theory has evolved around boosting, with connections to a range of topics, including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical.

This book, written by the inventors of the method, brings together, organizes, simplifies, and substantially extends two decades of research on boosting, presenting both theory and applications in a way that is accessible to readers from diverse backgrounds while also providing an authoritative reference for advanced researchers. With its introductory treatment of all material and its inclusion of exercises in every chapter, the book is appropriate for course use as well. The book begins with a general introduction to machine learning algorithms and their analysis; then explores the core theory of boosting, especially its ability to generalize; examines some of the myriad other theoretical viewpoints that help to explain and understand boosting; provides practical extensions of boosting for more complex learning problems; and finally presents a number of advanced theoretical topics. Numerous applications and practical illustrations are offered throughout.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

About the Author:

Robert E. Schapire is Professor of Computer Science at Princeton University. Yoav Freund is Professor of Computer Science at the University of California, San Diego. For their work on boosting, Freund and Schapire received both the Gödel Prize in 2003 and the Kanellakis Theory and Practice Award in 2004.

Review:

Robert Schapire and Yoav Freund made a huge impact in machine and statistical learning with their invention of boosting, which has survived the test of time. There have been lively discussions about alternative explanations of why it works so well, and the jury is still out. This well-balanced book from the 'masters' covers boosting from all points of view, and gives easy access to the wealth of research that this field has produced.

(Trevor Hastie, Statistics Department, Stanford University)

Boosting has provided a platform for thinking about and designing machine learning algorithms for over 20 years. The simple and elegant idea behind boosting is a 'Mirror of Erised' that researchers view from many different perspectives. This book beautifully ties together these views, using the same limpid style found in Robert Schapire and Yoav Freund's original research papers. It's an important resource for machine learning research.

(John Lafferty, University of Chicago and Carnegie Mellon University)

An outstanding text, which provides an authoritative, self-contained, broadly accessible and very readable treatment of boosting methods, a widely applied family of machine learning algorithms pioneered by the authors. It nicely covers the spectrum from theory through methodology to applications.

(Peter Bartlett, University of California, Berkeley)

Boosting is an amazing machine learning algorithm of 'intelligence' with much success in practice. It allows a weak learner to adapt to the data at hand and become 'strong'; it seamlessly integrates statistical estimation and computation. In this book, Robert Schapire and Yoav Freund, two inventors of the field, present multiple, fascinating views of boosting to explain why and how it works.

(Bin Yu, University of California, Berkeley)

This excellent book is a mind-stretcher that should be read and reread, even by nonspecialists.

(Computing Reviews)

Boosting is, quite simply, one of the best-written books I've read on machine learning...

(The Bactra Review)

For those who wish to work in the area, it is a clear and insightful view of the subject that deserves a place in the canon of machine learning and on the shelves of those who study it.

(Giles Hooker Journal of the American Statistical Association)

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

I migliori risultati di ricerca su AbeBooks

1.

Robert E. Schapire; Yoav Freund
ISBN 10: 0262526034 ISBN 13: 9780262526036
Nuovi Quantità: 5
Da
GreatBookPrices
(Columbia, MD, U.S.A.)
Valutazione libreria
[?]

Descrizione libro Condizione libro: New. Codice libro della libreria 20281694-n

Maggiori informazioni su questa libreria | Fare una domanda alla libreria

Compra nuovo
EUR 22,34
Convertire valuta

Aggiungere al carrello

Spese di spedizione: EUR 2,29
In U.S.A.
Destinazione, tempi e costi

2.

Robert E. Schapire
ISBN 10: 0262526034 ISBN 13: 9780262526036
Nuovi Quantità: 1
Da
Book Park
(Southfield, MI, U.S.A.)
Valutazione libreria
[?]

Descrizione libro Condizione libro: New. Brand New Book. Codice libro della libreria 0262526034BYR

Maggiori informazioni su questa libreria | Fare una domanda alla libreria

Compra nuovo
EUR 24,69
Convertire valuta

Aggiungere al carrello

Spese di spedizione: GRATIS
In U.S.A.
Destinazione, tempi e costi

3.

Robert E. Schapire, Yoav Freund
Editore: MIT Press Ltd, United States (2014)
ISBN 10: 0262526034 ISBN 13: 9780262526036
Nuovi Paperback Quantità: 1
Da
The Book Depository
(London, Regno Unito)
Valutazione libreria
[?]

Descrizione libro MIT Press Ltd, United States, 2014. Paperback. Condizione libro: New. Language: English . Brand New Book. Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate rules of thumb. A remarkably rich theory has evolved around boosting, with connections to a range of topics, including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical. This book, written by the inventors of the method, brings together, organizes, simplifies, and substantially extends two decades of research on boosting, presenting both theory and applications in a way that is accessible to readers from diverse backgrounds while also providing an authoritative reference for advanced researchers. With its introductory treatment of all material and its inclusion of exercises in every chapter, the book is appropriate for course use as well.The book begins with a general introduction to machine learning algorithms and their analysis; then explores the core theory of boosting, especially its ability to generalize; examines some of the myriad other theoretical viewpoints that help to explain and understand boosting; provides practical extensions of boosting for more complex learning problems; and finally presents a number of advanced theoretical topics. Numerous applications and practical illustrations are offered throughout. Codice libro della libreria AAU9780262526036

Maggiori informazioni su questa libreria | Fare una domanda alla libreria

Compra nuovo
EUR 27,72
Convertire valuta

Aggiungere al carrello

Spese di spedizione: GRATIS
Da: Regno Unito a: U.S.A.
Destinazione, tempi e costi

4.

Robert E. Schapire, Yoav Freund
Editore: MIT Press Ltd, United States (2014)
ISBN 10: 0262526034 ISBN 13: 9780262526036
Nuovi Paperback Quantità: 1
Da
The Book Depository US
(London, Regno Unito)
Valutazione libreria
[?]

Descrizione libro MIT Press Ltd, United States, 2014. Paperback. Condizione libro: New. Language: English . Brand New Book. Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate rules of thumb. A remarkably rich theory has evolved around boosting, with connections to a range of topics, including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical.This book, written by the inventors of the method, brings together, organizes, simplifies, and substantially extends two decades of research on boosting, presenting both theory and applications in a way that is accessible to readers from diverse backgrounds while also providing an authoritative reference for advanced researchers. With its introductory treatment of all material and its inclusion of exercises in every chapter, the book is appropriate for course use as well. The book begins with a general introduction to machine learning algorithms and their analysis; then explores the core theory of boosting, especially its ability to generalize; examines some of the myriad other theoretical viewpoints that help to explain and understand boosting; provides practical extensions of boosting for more complex learning problems; and finally presents a number of advanced theoretical topics. Numerous applications and practical illustrations are offered throughout. Codice libro della libreria AAU9780262526036

Maggiori informazioni su questa libreria | Fare una domanda alla libreria

Compra nuovo
EUR 27,80
Convertire valuta

Aggiungere al carrello

Spese di spedizione: GRATIS
Da: Regno Unito a: U.S.A.
Destinazione, tempi e costi

5.

Schapire, Robert E., Freund, Yoav
Editore: The MIT Press (2014)
ISBN 10: 0262526034 ISBN 13: 9780262526036
Nuovi Brossura Quantità: 4
Valutazione libreria
[?]

Descrizione libro The MIT Press, 2014. Condizione libro: New. Series: Adaptive Computation and Machine Learning Series. Num Pages: 544 pages, 77 b&w illus. BIC Classification: UMB; UYA; UYQM. Category: (P) Professional & Vocational. Dimension: 181 x 230 x 24. Weight in Grams: 854. . 2014. Paperback. . . . . . Codice libro della libreria V9780262526036

Maggiori informazioni su questa libreria | Fare una domanda alla libreria

Compra nuovo
EUR 28,49
Convertire valuta

Aggiungere al carrello

Spese di spedizione: GRATIS
Da: Irlanda a: U.S.A.
Destinazione, tempi e costi

6.

Robert E. Schapire, Yoav Freund
Editore: MIT Press 2014-02-11, Cambridge, Mass. (2014)
ISBN 10: 0262526034 ISBN 13: 9780262526036
Nuovi paperback Quantità: 1
Da
Blackwell's
(Oxford, OX, Regno Unito)
Valutazione libreria
[?]

Descrizione libro MIT Press 2014-02-11, Cambridge, Mass., 2014. paperback. Condizione libro: New. Codice libro della libreria 9780262526036

Maggiori informazioni su questa libreria | Fare una domanda alla libreria

Compra nuovo
EUR 25,60
Convertire valuta

Aggiungere al carrello

Spese di spedizione: EUR 3,39
Da: Regno Unito a: U.S.A.
Destinazione, tempi e costi

7.

Schapire, Robert E., Freund, Yoav
Editore: The MIT Press
ISBN 10: 0262526034 ISBN 13: 9780262526036
Nuovi Brossura Quantità: 4
Da
Kennys Bookstore
(Olney, MD, U.S.A.)
Valutazione libreria
[?]

Descrizione libro The MIT Press. Condizione libro: New. Series: Adaptive Computation and Machine Learning Series. Num Pages: 544 pages, 77 b&w illus. BIC Classification: UMB; UYA; UYQM. Category: (P) Professional & Vocational. Dimension: 181 x 230 x 24. Weight in Grams: 854. . 2014. Paperback. . . . . Books ship from the US and Ireland. Codice libro della libreria V9780262526036

Maggiori informazioni su questa libreria | Fare una domanda alla libreria

Compra nuovo
EUR 29,85
Convertire valuta

Aggiungere al carrello

Spese di spedizione: GRATIS
In U.S.A.
Destinazione, tempi e costi

8.

Robert E. Schapire
ISBN 10: 0262526034 ISBN 13: 9780262526036
Nuovi Quantità: 3
Da
BooksForStudent
(West Bloomfield, MI, U.S.A.)
Valutazione libreria
[?]

Descrizione libro Condizione libro: New. Brand New Book In Mint condition. Shipping with Trackable Method. No APO/FPO Addresses Please. Codice libro della libreria 9780262526036NHS

Maggiori informazioni su questa libreria | Fare una domanda alla libreria

Compra nuovo
EUR 29,85
Convertire valuta

Aggiungere al carrello

Spese di spedizione: GRATIS
In U.S.A.
Destinazione, tempi e costi

9.

Robert E. Schapire
Editore: MIT Press (2014)
ISBN 10: 0262526034 ISBN 13: 9780262526036
Nuovi Quantità: 4
Da
Books2Anywhere
(Fairford, GLOS, Regno Unito)
Valutazione libreria
[?]

Descrizione libro MIT Press, 2014. PAP. Condizione libro: New. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Codice libro della libreria BB-9780262526036

Maggiori informazioni su questa libreria | Fare una domanda alla libreria

Compra nuovo
EUR 21,09
Convertire valuta

Aggiungere al carrello

Spese di spedizione: EUR 10,18
Da: Regno Unito a: U.S.A.
Destinazione, tempi e costi

10.

Robert E. Schapire; Yoav Freund
ISBN 10: 0262526034 ISBN 13: 9780262526036
Nuovi Quantità: 3
Da
BWB
(Valley Stream, NY, U.S.A.)
Valutazione libreria
[?]

Descrizione libro Condizione libro: New. Depending on your location, this item may ship from the US or UK. Codice libro della libreria 97802625260360000000

Maggiori informazioni su questa libreria | Fare una domanda alla libreria

Compra nuovo
EUR 33,08
Convertire valuta

Aggiungere al carrello

Spese di spedizione: GRATIS
In U.S.A.
Destinazione, tempi e costi

Vedi altre copie di questo libro

Vedi tutti i risultati per questo libro