A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability, 31, Band 31) - Hardcover

Devroye, Luc; Györfi, Laszlo; Lugosi, Gabor

Hardcover

ISBN 10: 0387946187 ISBN 13: 9780387946184

Verlag: Springer, 1996

Inhaltsangabe

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.

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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, tree 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 zur Ausgabe

• Verlag: Springer
• Erscheinungsdatum: 1996
• Sprache: Englisch
• ISBN 10: 0387946187
• ISBN 13: 9780387946184
• Einband: Gebundene Ausgabe
• Anzahl der Seiten: 653
• Kontakt zum Hersteller: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3; Heidelberg; 69115; Deutschland