From Statistics to Neural Networks
Vladimir Cherkassky · 1994
על הספר
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.
פרטי הספר
- שנה
- 1994
- שפה
- English
- סדרה
- NATO ASI Series, Series F: Computer and Systems Sciences -- 136
- הוצאה
- Springer Berlin Heidelberg
- מהדורות
- 4
- עמודים
- 394
- ISBN
- 9783642791192
מקור הנתונים: Wikidata