A Statistical Approach to Neural Networks for Pattern Recognition

Description

This book presents a statistical treatment of the Multilayer Perceptron (MLP), which is the most widely used of the neural network models, in a language that is familiar to practicing statisticians. Questions arise when statisticians are first confronted with such a model, and this book's aim is to provide thorough answers. The following are a few questions that are considered in this book and are explored: how robust is the model to outliers, could the model be made more robust, which points will have a high leverage, what are good starting values for the fitting algorithm, etc. Discussions include the use of MLP models with spatial data as well as the influence and sensitivity curves of the MLP. The question of why the MLP is a (fairly) robust model is answered and modifications to make it very robust are considered.










http://rapidshare.com/files/146245627/Neural_Network.rar

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1. Ebooks list page : 1921
2. Pattern Recognition with Neural Networks in C
3. Neural Networks and Pattern Recognition
4. Pattern Recognition and Neural Networks
5. Neural Networks for Pattern Recognition
6. Neural Networks for Pattern Recognition
7. Introduction to Pattern Recognition - Statistical, Structural, Neural & Fuzzy Logic Approaches
8. Neural Networks and Pattern Recognition (repost)
9. Pattern Recognition Using Neural and Functional Networks
10. Neural Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern Recognition
11. [share_ebook] Neural Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern Recognition
12. Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing: An Evolutionary Approach for Neural Networks and Fuzzy Systems (Studies in Fuzziness and Soft Computing)
13. Statistical Pattern Recognition, 2nd Edition
14. Random Graphs for Statistical Pattern Recognition
15. [share_ebook] Random Graphs for Statistical Pattern Recognition
16. Keinosuke Fukunaga - Introduction to Statistical Pattern Recognition