Pattern Classification: A Unified View of Statistical and Neural Approaches - Hardcover

Schürmann, Jürgen

 
9780471135340: Pattern Classification: A Unified View of Statistical and Neural Approaches
Hardcover
ISBN 10: 0471135348 ISBN 13: 9780471135340
Verlag: Wiley-Interscience, 1996

Inhaltsangabe

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. 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.

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.

Über die Autorin bzw. den Autor

JÜRGEN SCHÜRMANN is head of the Pattern Understanding Group at the Daimler-Benz Research Center in Ulm, Germany, and teaches at the Technical University of Darmstadt.

Von der hinteren Coverseite

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. 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.

Aus dem Klappentext

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. 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.

„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.

Verlag
Wiley-Interscience
Erscheinungsdatum
1996
Sprache
Englisch
ISBN 10 
0471135348
ISBN 13 
9780471135340
Einband
Gebundene Ausgabe
Auflage
1
Anzahl der Seiten
392
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