From Statistics to Neural Networks: Theory and Pattern Recognition Applications (NATO ASI Series / Computer and Systems Sciences) [Hardcover]

Vladimir Cherkassky (Editor), Jerome H. Friedman (Editor), Harry Wechsler (Editor)

Book Description

ISBN-10: 3540581995 | ISBN-13: 978-3540581994 | Publication Date: March 31, 1996 | Edition: 1

This volume provides a unified approach to the study of predictive learning, i.e., generalization from examples. It contains an up-to-date review and in-depth treatment of major issues and methods related to predictive learning in statistics, Artificial Neural Networks (ANN), and pattern recognition. Topics range from theoretical modeling and adaptive computational methods to empirical comparisons between statistical and ANN methods, and applications. Most contributions fall into one of the three themes: unified framework for the study of predictive learning in statistics and ANNs; similarities and differences between statistical and ANN methods for nonparametric estimation (learning); and fundamental connections between artificial and biological learning systems.

Product Details

• Hardcover: 394 pages
• Publisher: Springer; 1 edition (March 31, 1996)
• Language: English
• ISBN-10: 3540581995
• ISBN-13: 978-3540581994

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