Pattern Classification : A Unified View of Statistical and Neural Approaches
Editorial Reviews
Book Description
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.
Book Info
Provides a unified view of statistical and neural approaches. Sheds new light on the relationship between seemingly unrelated approaches to pattern recognition. DLC: Pattern recognition systems.
Pattern Classification : A Unified View of Statistical and Neural Approaches
Pattern Classification: A Unified View of Statistical and Neural Approaches,Jürgen Schürmann,Wiley-Interscience,0471135348,Computer Books: General,Computers,Computers - Languages / Programming,Data Processing - Optical Data Processing,General,Neural Computing,Neural Networks,Neural networks (Computer scie,Neural networks (Computer science),Pattern Recognition,Pattern perception,Pattern recognition systems,Programming Languages - General,Statistical decision,Computers / Optical Data Processing,Mathematics for scientists & engineers,Probability & statistics
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