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Hardcover - 9780387946184
149,79 €
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Beschreibung
Pattern recognition presents one of the most significant challenges for scientists and engineers, and many different approaches have been proposed. The aim of this book is to provide a self-contained account of probabilistic analysis of these approaches. The book includes a discussion of distance measures, nonparametric methods based on kernels or nearest neighbors, Vapnik-Chervonenkis theory, epsilon entropy, parametric classification, error estimation, free classifiers, and neural networks. Wherever possible, distribution-free properties and inequalities are derived. A substantial portion of the results or the analysis is new. Over 430 problems and exercises complement the material.
Details
| Verlag | Springer US |
| Ersterscheinung | 22. November 2013 |
| Maße | 23.5 cm x 15.5 cm |
| Gewicht | 984 Gramm |
| Format | Softcover |
| ISBN-13 | 9781461268772 |
| Seiten | 638 |
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