Covering pattern classification methods, "Combining Classifiers: Ideas and Methods" focuses on the important and widely studied issue of how to combine several classifiers together in order to achieve improved recognition performance. It is one of the first books to provide unified, coherent, and expansive coverage of the topic and as such will be welcomed by those involved in the area. With case studies that bring the text alive and demonstrate 'real-world' applications it is destined to become essential reading.
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LUDMILA I. KUNCHEVA is a Senior Lecturer in the School of Informatics at the University of Wales, Bangor, UK.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Etat : good. Supports Goodwill of Silicon Valley job training programs. The cover and pages are in Good condition! Any other included accessories are also in Good condition showing use. Use can include some highlighting and writing, page and cover creases as well as other types visible wear. N° de réf. du vendeur GWSVV.0471210781.G
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Vendeur : Better World Books Ltd, Dunfermline, Royaume-Uni
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Vendeur : Optimon Books, Gravesend, KENT, Royaume-Uni
Hardcover. Etat : Good. A unified, coherent, and expansive treatment of current classifier ensemble methodsMail sorting, medical test reading, military target recognition, signature verification, meteorological forecast, DNA matching, fingerprint recognition. These are just a few of the areas requiring reliable, precise pattern recognition. Although in the past, pattern recognition has focused on designing single classifiers, recently the focus has been on combining several classifiers and getting a consensus of results for greater accuracy. This interest in combining classifiers has grown astronomically in recent years, evolving into a rich and dynamic, if loosely structured, discipline. Combining Pattern Classifiers: Methods and Algorithms represents the first attempt to provide a comprehensive survey of this fastgrowing field. In a clear and straightforward manner, the author provides a muchneeded road map through a multifaceted and often controversial subject while effectively organizing and systematizing the current state of the art. Covering a broad range of methodologies, algorithms, and theories, the text addresses such questions as: Why should we combine classifiers? What are the current approaches for building classifier ensembles? What fusion methods can we use? How do we measure diversity in a classifier ensemble and is diversity really a key factor to its success? Replete with case studies and realworld applications, this groundbreaking text will be of interest to academics and researchers in the field seeking both new classification tools and new uses for the old ones. Copyright © John Wiley. N° de réf. du vendeur 461101
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Vendeur : Feldman's Books, Menlo Park, CA, Etats-Unis
Hardcover. Etat : Fine. 1st Edition. No Markings. N° de réf. du vendeur 045202
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Etat : Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,750grams, ISBN:9780471210788. N° de réf. du vendeur 8236116
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Vendeur : Buchpark, Trebbin, Allemagne
Etat : Sehr gut. Zustand: Sehr gut | Seiten: 376 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar. N° de réf. du vendeur 1687289/2
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