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.
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.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Da: HPB-Red, Dallas, TX, U.S.A.
Hardcover. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority! Codice articolo S_388415682
Quantità: 1 disponibili
Da: World of Books (was SecondSale), Montgomery, IL, U.S.A.
Condizione: Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc. Codice articolo 00094996537
Quantità: 1 disponibili
Da: ThriftBooks-Dallas, Dallas, TX, U.S.A.
Hardcover. Condizione: Fair. No Jacket. Readable copy. Pages may have considerable notes/highlighting. ~ ThriftBooks: Read More, Spend Less. Codice articolo G0262017180I5N00
Quantità: 1 disponibili
Da: GoldBooks, Denver, CO, U.S.A.
Condizione: new. Codice articolo 91S50_51_0262017180
Quantità: 1 disponibili