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In den WarenkorbZustand: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.
Anbieter: Antiquariat Renner OHG, Albstadt, Deutschland
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Hardcover. Zustand: Sehr gut. N.Y., Wiley (1996). gr.8°. Many figs. XVII, 373 p. Hardbound. In very good condition.
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24 cm. original hardcover. xviii,374 pp. ills. references. index. -very good. 725g.
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Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 392 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
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Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
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In den WarenkorbGebunden. Zustand: New. JUeRGEN SCHUeRMANN is head of the Pattern Understanding Group at the Daimler-Benz Research Center in Ulm, Germany, and teaches at the Technical University of Darmstadt.PATTERN CLASSIFICATIONa unified view of statistical and neural approachesThe product of.
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 271,20
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In den WarenkorbHardcover. Zustand: Brand New. 1st edition. 392 pages. 9.75x6.75x1.00 inches. In Stock.
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In den WarenkorbZustand: New. PATTERN CLASSIFICATION a unified view of statistical and neural approaches The product of years of research and practical experience in pattern classification, this book offers a theory-based engineering perspective on neural networks and statistical pattern classification. Num Pages: 392 pages, Illustrations. BIC Classification: PBT; UYAM; UYQP. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 242 x 168 x 27. Weight in Grams: 720. . 1996. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Neuware - PATTERN CLASSIFICATIONa unified view of statistical and neural approachesThe product of years of research and practical experience in pattern classification, this book offers a theory-based engineering perspective on neural networks and statistical pattern classification. Pattern Classification sheds new light on the relationship between seemingly unrelated approaches to pattern recognition, including statistical methods, polynomial regression, multilayer perceptron, and radial basis functions. Important topics such as feature selection, reject criteria, classifier performance measurement, and classifier combinations are fully covered, as well as material on techniques that, until now, would have required an extensive literature search to locate. A full program of illustrations, graphs, and examples helps make the operations and general properties of different classification approaches intuitively understandable.Offering a lucid presentation of complex applications and their algorithms, Pattern Classification is an invaluable resource for researchers, engineers, and graduate students in this rapidly developing field.