Pattern Classification – A Unified View of Statistical and Neural Approaches

Pattern ClassificationA Unified View of Statistical and Neural Approaches\nAuthor(s): Jrgen Schrmann\nFormat: Hardback\nPublisher: John Wiley & Sons Inc, United States\nImprint: Wiley-Interscience\nISBN-13: 9780471135340, 978-0471135340\nSynopsis\nPATTERN 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 sea.